Chapter 12 Functions and Operators
Prev		Next

Chapter 12 Functions and Operators

Table of Contents

Expressions can be used at several points in SQL statements, such as in the ORDER BY or HAVING clauses of SELECT statements, in the WHERE clause of a SELECT, DELETE, or UPDATE statement, or in SET statements. Expressions can be written using literal values, column values, NULL, built-in functions, stored functions, user-defined functions, and operators. This chapter describes the functions and operators that are permitted for writing expressions in MySQL. Instructions for writing stored functions and user-defined functions are given in Section 23.2, “Using Stored Routines (Procedures and Functions)”, and Section 28.4, “Adding New Functions to MySQL”. See Section 9.2.4, “Function Name Parsing and Resolution”, for the rules describing how the server interprets references to different kinds of functions.

An expression that contains NULL always produces a NULL value unless otherwise indicated in the documentation for a particular function or operator.

Note

By default, there must be no whitespace between a function name and the parenthesis following it. This helps the MySQL parser distinguish between function calls and references to tables or columns that happen to have the same name as a function. However, spaces around function arguments are permitted.

You can tell the MySQL server to accept spaces after function names by starting it with the --sql-mode=IGNORE_SPACE option. (See Section 5.1.10, “Server SQL Modes”.) Individual client programs can request this behavior by using the CLIENT_IGNORE_SPACE option for mysql_real_connect(). In either case, all function names become reserved words.

For the sake of brevity, most examples in this chapter display the output from the mysql program in abbreviated form. Rather than showing examples in this format:

mysql> SELECT MOD(29,9);
+-----------+
| mod(29,9) |
+-----------+
|         2 |
+-----------+
1 rows in set (0.00 sec)

This format is used instead:

mysql> SELECT MOD(29,9);
        -> 2

12.1 Function and Operator Reference

Table 12.1 Functions and Operators

Name	Description
`ABS()`	Return the absolute value
`ACOS()`	Return the arc cosine
`ADDDATE()`	Add time values (intervals) to a date value
`ADDTIME()`	Add time
`AES_DECRYPT()`	Decrypt using AES
`AES_ENCRYPT()`	Encrypt using AES
`AND`, `&&`	Logical AND
`ANY_VALUE()`	Suppress ONLY_FULL_GROUP_BY value rejection
`ASCII()`	Return numeric value of left-most character
`ASIN()`	Return the arc sine
`=`	Assign a value (as part of a `SET` statement, or as part of the `SET` clause in an `UPDATE` statement)
`:=`	Assign a value
`ASYMMETRIC_DECRYPT()`	Decrypt ciphertext using private or public key
`ASYMMETRIC_DERIVE()`	Derive symmetric key from asymmetric keys
`ASYMMETRIC_ENCRYPT()`	Encrypt cleartext using private or public key
`ASYMMETRIC_SIGN()`	Generate signature from digest
`ASYMMETRIC_VERIFY()`	Verify that signature matches digest
`ATAN()`	Return the arc tangent
`ATAN2()`, `ATAN()`	Return the arc tangent of the two arguments
`AVG()`	Return the average value of the argument
`BENCHMARK()`	Repeatedly execute an expression
`BETWEEN ... AND ...`	Check whether a value is within a range of values
`BIN()`	Return a string containing binary representation of a number
`BIN_TO_UUID()`	Convert binary UUID to string
`BINARY`	Cast a string to a binary string
`BIT_AND()`	Return bitwise AND
`BIT_COUNT()`	Return the number of bits that are set
`BIT_LENGTH()`	Return length of argument in bits
`BIT_OR()`	Return bitwise OR
`BIT_XOR()`	Return bitwise XOR
`&`	Bitwise AND
`~`	Bitwise inversion
`\|`	Bitwise OR
`^`	Bitwise XOR
`CAN_ACCESS_COLUMN()`	Internal use only
`CAN_ACCESS_DATABASE()`	Internal use only
`CAN_ACCESS_TABLE()`	Internal use only
`CAN_ACCESS_VIEW()`	Internal use only
`CASE`	Case operator
`CAST()`	Cast a value as a certain type
`CEIL()`	Return the smallest integer value not less than the argument
`CEILING()`	Return the smallest integer value not less than the argument
`CHAR()`	Return the character for each integer passed
`CHAR_LENGTH()`	Return number of characters in argument
`CHARACTER_LENGTH()`	Synonym for CHAR_LENGTH()
`CHARSET()`	Return the character set of the argument
`COALESCE()`	Return the first non-NULL argument
`COERCIBILITY()`	Return the collation coercibility value of the string argument
`COLLATION()`	Return the collation of the string argument
`COMPRESS()`	Return result as a binary string
`CONCAT()`	Return concatenated string
`CONCAT_WS()`	Return concatenate with separator
`CONNECTION_ID()`	Return the connection ID (thread ID) for the connection
`CONV()`	Convert numbers between different number bases
`CONVERT()`	Cast a value as a certain type
`CONVERT_TZ()`	Convert from one time zone to another
`COS()`	Return the cosine
`COT()`	Return the cotangent
`COUNT()`	Return a count of the number of rows returned
`COUNT(DISTINCT)`	Return the count of a number of different values
`CRC32()`	Compute a cyclic redundancy check value
`CREATE_ASYMMETRIC_PRIV_KEY()`	Create private key
`CREATE_ASYMMETRIC_PUB_KEY()`	Create public key
`CREATE_DH_PARAMETERS()`	Generate shared DH secret
`CREATE_DIGEST()`	Generate digest from string
`CUME_DIST()`	Cumulative distribution value
`CURDATE()`	Return the current date
`CURRENT_DATE()`, `CURRENT_DATE`	Synonyms for CURDATE()
`CURRENT_ROLE()`	Returns the current active roles
`CURRENT_TIME()`, `CURRENT_TIME`	Synonyms for CURTIME()
`CURRENT_TIMESTAMP()`, `CURRENT_TIMESTAMP`	Synonyms for NOW()
`CURRENT_USER()`, `CURRENT_USER`	The authenticated user name and host name
`CURTIME()`	Return the current time
`DATABASE()`	Return the default (current) database name
`DATE()`	Extract the date part of a date or datetime expression
`DATE_ADD()`	Add time values (intervals) to a date value
`DATE_FORMAT()`	Format date as specified
`DATE_SUB()`	Subtract a time value (interval) from a date
`DATEDIFF()`	Subtract two dates
`DAY()`	Synonym for DAYOFMONTH()
`DAYNAME()`	Return the name of the weekday
`DAYOFMONTH()`	Return the day of the month (0-31)
`DAYOFWEEK()`	Return the weekday index of the argument
`DAYOFYEAR()`	Return the day of the year (1-366)
`DECODE()`	Decodes a string encrypted using ENCODE()
`DEFAULT()`	Return the default value for a table column
`DEGREES()`	Convert radians to degrees
`DENSE_RANK()`	Rank of current row within its partition, without gaps
`DES_DECRYPT()`	Decrypt a string
`DES_ENCRYPT()`	Encrypt a string
`DIV`	Integer division
`/`	Division operator
`ELT()`	Return string at index number
`ENCODE()`	Encode a string
`ENCRYPT()`	Encrypt a string
`=`	Equal operator
`<=>`	NULL-safe equal to operator
`EXP()`	Raise to the power of
`EXPORT_SET()`	Return a string such that for every bit set in the value bits, you get an on string and for every unset bit, you get an off string
`EXTRACT()`	Extract part of a date
`ExtractValue()`	Extracts a value from an XML string using XPath notation
`FIELD()`	Return the index (position) of the first argument in the subsequent arguments
`FIND_IN_SET()`	Return the index position of the first argument within the second argument
`FIRST_VALUE()`	Value of argument from first row of window frame
`FLOOR()`	Return the largest integer value not greater than the argument
`FORMAT()`	Return a number formatted to specified number of decimal places
`FOUND_ROWS()`	For a SELECT with a LIMIT clause, the number of rows that would be returned were there no LIMIT clause
`FROM_BASE64()`	Decode to a base-64 string and return result
`FROM_DAYS()`	Convert a day number to a date
`FROM_UNIXTIME()`	Format Unix timestamp as a date
`GeomCollection()`	Construct geometry collection from geometries
`GeometryCollection()`	Construct geometry collection from geometries
`GET_DD_COLUMN_PRIVILEGES()`	Internal use only
`GET_DD_CREATE_OPTIONS()`	Internal use only
`GET_DD_INDEX_SUB_PART_LENGTH()`	Internal use only
`GET_FORMAT()`	Return a date format string
`GET_LOCK()`	Get a named lock
`>`	Greater than operator
`>=`	Greater than or equal operator
`GREATEST()`	Return the largest argument
`GROUP_CONCAT()`	Return a concatenated string
`GROUPING()`	Distinguish super-aggregate ROLLUP rows from regular rows
`GTID_SUBSET()`	Return true if all GTIDs in subset are also in set; otherwise false.
`GTID_SUBTRACT()`	Return all GTIDs in set that are not in subset.
`HEX()`	Return a hexadecimal representation of a decimal or string value
`HOUR()`	Extract the hour
`ICU_VERSION()`	ICU library version
`IF()`	If/else construct
`IFNULL()`	Null if/else construct
`IN()`	Check whether a value is within a set of values
`INET_ATON()`	Return the numeric value of an IP address
`INET_NTOA()`	Return the IP address from a numeric value
`INET6_ATON()`	Return the numeric value of an IPv6 address
`INET6_NTOA()`	Return the IPv6 address from a numeric value
`INSERT()`	Insert a substring at the specified position up to the specified number of characters
`INSTR()`	Return the index of the first occurrence of substring
`INTERNAL_AUTO_INCREMENT()`	Internal use only
`INTERNAL_AVG_ROW_LENGTH()`	Internal use only
`INTERNAL_CHECK_TIME()`	Internal use only
`INTERNAL_CHECKSUM()`	Internal use only
`INTERNAL_DATA_FREE()`	Internal use only
`INTERNAL_DATA_LENGTH()`	Internal use only
`INTERNAL_DD_CHAR_LENGTH()`	Internal use only
`INTERNAL_GET_COMMENT_OR_ERROR()`	Internal use only
`INTERNAL_GET_VIEW_WARNING_OR_ERROR()`	Internal use only
`INTERNAL_INDEX_COLUMN_CARDINALITY()`	Internal use only
`INTERNAL_INDEX_LENGTH()`	Internal use only
`INTERNAL_KEYS_DISABLED()`	Internal use only
`INTERNAL_MAX_DATA_LENGTH()`	Internal use only
`INTERNAL_TABLE_ROWS()`	Internal use only
`INTERNAL_UPDATE_TIME()`	Internal use only
`INTERVAL()`	Return the index of the argument that is less than the first argument
`IS`	Test a value against a boolean
`IS_FREE_LOCK()`	Whether the named lock is free
`IS_IPV4()`	Whether argument is an IPv4 address
`IS_IPV4_COMPAT()`	Whether argument is an IPv4-compatible address
`IS_IPV4_MAPPED()`	Whether argument is an IPv4-mapped address
`IS_IPV6()`	Whether argument is an IPv6 address
`IS NOT`	Test a value against a boolean
`IS NOT NULL`	NOT NULL value test
`IS NULL`	NULL value test
`IS_USED_LOCK()`	Whether the named lock is in use; return connection identifier if true
`IS_UUID()`	Whether argument is a valid UUID
`ISNULL()`	Test whether the argument is NULL
`JSON_ARRAY()`	Create JSON array
`JSON_ARRAY_APPEND()`	Append data to JSON document
`JSON_ARRAY_INSERT()`	Insert into JSON array
`JSON_ARRAYAGG()`	Return result set as a single JSON array
`->`	Return value from JSON column after evaluating path; equivalent to JSON_EXTRACT().
`JSON_CONTAINS()`	Whether JSON document contains specific object at path
`JSON_CONTAINS_PATH()`	Whether JSON document contains any data at path
`JSON_DEPTH()`	Maximum depth of JSON document
`JSON_EXTRACT()`	Return data from JSON document
`->>`	Return value from JSON column after evaluating path and unquoting the result; equivalent to JSON_UNQUOTE(JSON_EXTRACT()).
`JSON_INSERT()`	Insert data into JSON document
`JSON_KEYS()`	Array of keys from JSON document
`JSON_LENGTH()`	Number of elements in JSON document
`JSON_MERGE()` (deprecated 8.0.3)	Merge JSON documents, preserving duplicate keys. Deprecated synonym for JSON_MERGE_PRESERVE()
`JSON_MERGE_PATCH()`	Merge JSON documents, replacing values of duplicate keys
`JSON_MERGE_PRESERVE()`	Merge JSON documents, preserving duplicate keys
`JSON_OBJECT()`	Create JSON object
`JSON_OBJECTAGG()`	Return result set as a single JSON object
`JSON_PRETTY()`	Prints a JSON document in human-readable format, with each array element or object member printed on a new line, indented two spaces with respect to its parent.
`JSON_QUOTE()`	Quote JSON document
`JSON_REMOVE()`	Remove data from JSON document
`JSON_REPLACE()`	Replace values in JSON document
`JSON_SEARCH()`	Path to value within JSON document
`JSON_SET()`	Insert data into JSON document
`JSON_STORAGE_FREE()`	Freed space within binary representation of a JSON column value following a partial update
`JSON_STORAGE_SIZE()`	Space used for storage of binary representation of a JSON document; for a JSON column, the space used when the document was inserted, prior to any partial updates
`JSON_TABLE()`	Returns data from a JSON expression as a relational table
`JSON_TYPE()`	Type of JSON value
`JSON_UNQUOTE()`	Unquote JSON value
`JSON_VALID()`	Whether JSON value is valid
`LAG()`	Value of argument from row lagging current row within partition
`LAST_DAY`	Return the last day of the month for the argument
`LAST_INSERT_ID()`	Value of the AUTOINCREMENT column for the last INSERT
`LAST_VALUE()`	Value of argument from last row of window frame
`LCASE()`	Synonym for LOWER()
`LEAD()`	Value of argument from row leading current row within partition
`LEAST()`	Return the smallest argument
`LEFT()`	Return the leftmost number of characters as specified
`<<`	Left shift
`LENGTH()`	Return the length of a string in bytes
`<`	Less than operator
`<=`	Less than or equal operator
`LIKE`	Simple pattern matching
`LineString()`	Construct LineString from Point values
`LN()`	Return the natural logarithm of the argument
`LOAD_FILE()`	Load the named file
`LOCALTIME()`, `LOCALTIME`	Synonym for NOW()
`LOCALTIMESTAMP`, `LOCALTIMESTAMP()`	Synonym for NOW()
`LOCATE()`	Return the position of the first occurrence of substring
`LOG()`	Return the natural logarithm of the first argument
`LOG10()`	Return the base-10 logarithm of the argument
`LOG2()`	Return the base-2 logarithm of the argument
`LOWER()`	Return the argument in lowercase
`LPAD()`	Return the string argument, left-padded with the specified string
`LTRIM()`	Remove leading spaces
`MAKE_SET()`	Return a set of comma-separated strings that have the corresponding bit in bits set
`MAKEDATE()`	Create a date from the year and day of year
`MAKETIME()`	Create time from hour, minute, second
`MASTER_POS_WAIT()`	Block until the slave has read and applied all updates up to the specified position
`MATCH`	Perform full-text search
`MAX()`	Return the maximum value
`MBRContains()`	Whether MBR of one geometry contains MBR of another
`MBRCoveredBy()`	Whether one MBR is covered by another
`MBRCovers()`	Whether one MBR covers another
`MBRDisjoint()`	Whether MBRs of two geometries are disjoint
`MBREquals()`	Whether MBRs of two geometries are equal
`MBRIntersects()`	Whether MBRs of two geometries intersect
`MBROverlaps()`	Whether MBRs of two geometries overlap
`MBRTouches()`	Whether MBRs of two geometries touch
`MBRWithin()`	Whether MBR of one geometry is within MBR of another
`MD5()`	Calculate MD5 checksum
`MICROSECOND()`	Return the microseconds from argument
`MID()`	Return a substring starting from the specified position
`MIN()`	Return the minimum value
`-`	Minus operator
`MINUTE()`	Return the minute from the argument
`MOD()`	Return the remainder
`%`, `MOD`	Modulo operator
`MONTH()`	Return the month from the date passed
`MONTHNAME()`	Return the name of the month
`MultiLineString()`	Contruct MultiLineString from LineString values
`MultiPoint()`	Construct MultiPoint from Point values
`MultiPolygon()`	Construct MultiPolygon from Polygon values
`NAME_CONST()`	Causes the column to have the given name
`NOT`, `!`	Negates value
`NOT BETWEEN ... AND ...`	Check whether a value is not within a range of values
`!=`, `<>`	Not equal operator
`NOT IN()`	Check whether a value is not within a set of values
`NOT LIKE`	Negation of simple pattern matching
`NOT REGEXP`	Negation of REGEXP
`NOW()`	Return the current date and time
`NTH_VALUE()`	Value of argument from N-th row of window frame
`NTILE()`	Bucket number of current row within its partition.
`NULLIF()`	Return NULL if expr1 = expr2
`OCT()`	Return a string containing octal representation of a number
`OCTET_LENGTH()`	Synonym for LENGTH()
`\|\|`, `OR`	Logical OR
`ORD()`	Return character code for leftmost character of the argument
`PASSWORD()`	Calculate and return a password string
`PERCENT_RANK()`	Percentage rank value
`PERIOD_ADD()`	Add a period to a year-month
`PERIOD_DIFF()`	Return the number of months between periods
`PI()`	Return the value of pi
`+`	Addition operator
`Point()`	Construct Point from coordinates
`Polygon()`	Construct Polygon from LineString arguments
`POSITION()`	Synonym for LOCATE()
`POW()`	Return the argument raised to the specified power
`POWER()`	Return the argument raised to the specified power
`QUARTER()`	Return the quarter from a date argument
`QUOTE()`	Escape the argument for use in an SQL statement
`RADIANS()`	Return argument converted to radians
`RAND()`	Return a random floating-point value
`RANDOM_BYTES()`	Return a random byte vector
`RANK()`	Rank of current row within its partition, with gaps
`REGEXP`	Whether string matches regular expression
`REGEXP_INSTR()`	Starting index of substring matching regular expression
`REGEXP_LIKE()`	Whether string matches regular expression
`REGEXP_REPLACE()`	Replace substrings matching regular expression
`REGEXP_SUBSTR()`	Return substring matching regular expression
`RELEASE_ALL_LOCKS()`	Releases all current named locks
`RELEASE_LOCK()`	Releases the named lock
`REPEAT()`	Repeat a string the specified number of times
`REPLACE()`	Replace occurrences of a specified string
`REVERSE()`	Reverse the characters in a string
`RIGHT()`	Return the specified rightmost number of characters
`>>`	Right shift
`RLIKE`	Whether string matches regular expression
`ROLES_GRAPHML()`	Returns a GraphML document representing memory role subgraphs
`ROUND()`	Round the argument
`ROW_COUNT()`	The number of rows updated
`ROW_NUMBER()`	Number of current row within its partition
`RPAD()`	Append string the specified number of times
`RTRIM()`	Remove trailing spaces
`SCHEMA()`	Synonym for DATABASE()
`SEC_TO_TIME()`	Converts seconds to 'HH:MM:SS' format
`SECOND()`	Return the second (0-59)
`SESSION_USER()`	Synonym for USER()
`SHA1()`, `SHA()`	Calculate an SHA-1 160-bit checksum
`SHA2()`	Calculate an SHA-2 checksum
`SIGN()`	Return the sign of the argument
`SIN()`	Return the sine of the argument
`SLEEP()`	Sleep for a number of seconds
`SOUNDEX()`	Return a soundex string
`SOUNDS LIKE`	Compare sounds
`SPACE()`	Return a string of the specified number of spaces
`SQRT()`	Return the square root of the argument
`ST_Area()`	Return Polygon or MultiPolygon area
`ST_AsBinary()`, `ST_AsWKB()`	Convert from internal geometry format to WKB
`ST_AsGeoJSON()`	Generate GeoJSON object from geometry
`ST_AsText()`, `ST_AsWKT()`	Convert from internal geometry format to WKT
`ST_Buffer()`	Return geometry of points within given distance from geometry
`ST_Buffer_Strategy()`	Produce strategy option for ST_Buffer()
`ST_Centroid()`	Return centroid as a point
`ST_Contains()`	Whether one geometry contains another
`ST_ConvexHull()`	Return convex hull of geometry
`ST_Crosses()`	Whether one geometry crosses another
`ST_Difference()`	Return point set difference of two geometries
`ST_Dimension()`	Dimension of geometry
`ST_Disjoint()`	Whether one geometry is disjoint from another
`ST_Distance()`	The distance of one geometry from another
`ST_Distance_Sphere()`	Minimum distance on earth between two geometries
`ST_EndPoint()`	End Point of LineString
`ST_Envelope()`	Return MBR of geometry
`ST_Equals()`	Whether one geometry is equal to another
`ST_ExteriorRing()`	Return exterior ring of Polygon
`ST_GeoHash()`	Produce a geohash value
`ST_GeomCollFromText()`, `ST_GeometryCollectionFromText()`, `ST_GeomCollFromTxt()`	Return geometry collection from WKT
`ST_GeomCollFromWKB()`, `ST_GeometryCollectionFromWKB()`	Return geometry collection from WKB
`ST_GeometryN()`	Return N-th geometry from geometry collection
`ST_GeometryType()`	Return name of geometry type
`ST_GeomFromGeoJSON()`	Generate geometry from GeoJSON object
`ST_GeomFromText()`, `ST_GeometryFromText()`	Return geometry from WKT
`ST_GeomFromWKB()`, `ST_GeometryFromWKB()`	Return geometry from WKB
`ST_InteriorRingN()`	Return N-th interior ring of Polygon
`ST_Intersection()`	Return point set intersection of two geometries
`ST_Intersects()`	Whether one geometry intersects another
`ST_IsClosed()`	Whether a geometry is closed and simple
`ST_IsEmpty()`	Placeholder function
`ST_IsSimple()`	Whether a geometry is simple
`ST_IsValid()`	Whether a geometry is valid
`ST_LatFromGeoHash()`	Return latitude from geohash value
`ST_Latitude()`	Return latitude of Point
`ST_Length()`	Return length of LineString
`ST_LineFromText()`, `ST_LineStringFromText()`	Construct LineString from WKT
`ST_LineFromWKB()`, `ST_LineStringFromWKB()`	Construct LineString from WKB
`ST_LongFromGeoHash()`	Return longitude from geohash value
`ST_Longitude()`	Return longitude of Point
`ST_MakeEnvelope()`	Rectangle around two points
`ST_MLineFromText()`, `ST_MultiLineStringFromText()`	Construct MultiLineString from WKT
`ST_MLineFromWKB()`, `ST_MultiLineStringFromWKB()`	Construct MultiLineString from WKB
`ST_MPointFromText()`, `ST_MultiPointFromText()`	Construct MultiPoint from WKT
`ST_MPointFromWKB()`, `ST_MultiPointFromWKB()`	Construct MultiPoint from WKB
`ST_MPolyFromText()`, `ST_MultiPolygonFromText()`	Construct MultiPolygon from WKT
`ST_MPolyFromWKB()`, `ST_MultiPolygonFromWKB()`	Construct MultiPolygon from WKB
`ST_NumGeometries()`	Return number of geometries in geometry collection
`ST_NumInteriorRing()`, `ST_NumInteriorRings()`	Return number of interior rings in Polygon
`ST_NumPoints()`	Return number of points in LineString
`ST_Overlaps()`	Whether one geometry overlaps another
`ST_PointFromGeoHash()`	Convert geohash value to POINT value
`ST_PointFromText()`	Construct Point from WKT
`ST_PointFromWKB()`	Construct Point from WKB
`ST_PointN()`	Return N-th point from LineString
`ST_PolyFromText()`, `ST_PolygonFromText()`	Construct Polygon from WKT
`ST_PolyFromWKB()`, `ST_PolygonFromWKB()`	Construct Polygon from WKB
`ST_Simplify()`	Return simplified geometry
`ST_SRID()`	Return spatial reference system ID for geometry
`ST_StartPoint()`	Start Point of LineString
`ST_SwapXY()`	Return argument with X/Y coordinates swapped
`ST_SymDifference()`	Return point set symmetric difference of two geometries
`ST_Touches()`	Whether one geometry touches another
`ST_Union()`	Return point set union of two geometries
`ST_Validate()`	Return validated geometry
`ST_Within()`	Whether one geometry is within another
`ST_X()`	Return X coordinate of Point
`ST_Y()`	Return Y coordinate of Point
`STATEMENT_DIGEST()`	Compute statement digest hash value
`STATEMENT_DIGEST_TEXT()`	Compute normalized statement digest
`STD()`	Return the population standard deviation
`STDDEV()`	Return the population standard deviation
`STDDEV_POP()`	Return the population standard deviation
`STDDEV_SAMP()`	Return the sample standard deviation
`STR_TO_DATE()`	Convert a string to a date
`STRCMP()`	Compare two strings
`SUBDATE()`	Synonym for DATE_SUB() when invoked with three arguments
`SUBSTR()`	Return the substring as specified
`SUBSTRING()`	Return the substring as specified
`SUBSTRING_INDEX()`	Return a substring from a string before the specified number of occurrences of the delimiter
`SUBTIME()`	Subtract times
`SUM()`	Return the sum
`SYSDATE()`	Return the time at which the function executes
`SYSTEM_USER()`	Synonym for USER()
`TAN()`	Return the tangent of the argument
`TIME()`	Extract the time portion of the expression passed
`TIME_FORMAT()`	Format as time
`TIME_TO_SEC()`	Return the argument converted to seconds
`TIMEDIFF()`	Subtract time
`*`	Multiplication operator
`TIMESTAMP()`	With a single argument, this function returns the date or datetime expression; with two arguments, the sum of the arguments
`TIMESTAMPADD()`	Add an interval to a datetime expression
`TIMESTAMPDIFF()`	Subtract an interval from a datetime expression
`TO_BASE64()`	Return the argument converted to a base-64 string
`TO_DAYS()`	Return the date argument converted to days
`TO_SECONDS()`	Return the date or datetime argument converted to seconds since Year 0
`TRIM()`	Remove leading and trailing spaces
`TRUNCATE()`	Truncate to specified number of decimal places
`UCASE()`	Synonym for UPPER()
`-`	Change the sign of the argument
`UNCOMPRESS()`	Uncompress a string compressed
`UNCOMPRESSED_LENGTH()`	Return the length of a string before compression
`UNHEX()`	Return a string containing hex representation of a number
`UNIX_TIMESTAMP()`	Return a Unix timestamp
`UpdateXML()`	Return replaced XML fragment
`UPPER()`	Convert to uppercase
`USER()`	The user name and host name provided by the client
`UTC_DATE()`	Return the current UTC date
`UTC_TIME()`	Return the current UTC time
`UTC_TIMESTAMP()`	Return the current UTC date and time
`UUID()`	Return a Universal Unique Identifier (UUID)
`UUID_SHORT()`	Return an integer-valued universal identifier
`UUID_TO_BIN()`	Convert string UUID to binary
`VALIDATE_PASSWORD_STRENGTH()`	Determine strength of password
`VALUES()`	Defines the values to be used during an INSERT
`VAR_POP()`	Return the population standard variance
`VAR_SAMP()`	Return the sample variance
`VARIANCE()`	Return the population standard variance
`VERSION()`	Return a string that indicates the MySQL server version
`WAIT_FOR_EXECUTED_GTID_SET()`	Wait until the given GTIDs have executed on slave.
`WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS()`	Wait until the given GTIDs have executed on slave.
`WEEK()`	Return the week number
`WEEKDAY()`	Return the weekday index
`WEEKOFYEAR()`	Return the calendar week of the date (1-53)
`WEIGHT_STRING()`	Return the weight string for a string
`XOR`	Logical XOR
`YEAR()`	Return the year
`YEARWEEK()`	Return the year and week

12.2 Type Conversion in Expression Evaluation

When an operator is used with operands of different types, type conversion occurs to make the operands compatible. Some conversions occur implicitly. For example, MySQL automatically converts numbers to strings as necessary, and vice versa.

mysql> SELECT 1+'1';
        -> 2
mysql> SELECT CONCAT(2,' test');
        -> '2 test'

It is also possible to convert a number to a string explicitly using the CAST() function. Conversion occurs implicitly with the CONCAT() function because it expects string arguments.

mysql> SELECT 38.8, CAST(38.8 AS CHAR);
        -> 38.8, '38.8'
mysql> SELECT 38.8, CONCAT(38.8);
        -> 38.8, '38.8'

See later in this section for information about the character set of implicit number-to-string conversions, and for modified rules that apply to CREATE TABLE ... SELECT statements.

The following rules describe how conversion occurs for comparison operations:

If one or both arguments are NULL, the result of the comparison is NULL, except for the NULL-safe <=> equality comparison operator. For NULL <=> NULL, the result is true. No conversion is needed.
If both arguments in a comparison operation are strings, they are compared as strings.
If both arguments are integers, they are compared as integers.
Hexadecimal values are treated as binary strings if not compared to a number.
If one of the arguments is a TIMESTAMP or DATETIME column and the other argument is a constant, the constant is converted to a timestamp before the comparison is performed. This is done to be more ODBC-friendly. This is not done for the arguments to IN(). To be safe, always use complete datetime, date, or time strings when doing comparisons. For example, to achieve best results when using BETWEEN with date or time values, use CAST() to explicitly convert the values to the desired data type.
A single-row subquery from a table or tables is not considered a constant. For example, if a subquery returns an integer to be compared to a DATETIME value, the comparison is done as two integers. The integer is not converted to a temporal value. To compare the operands as DATETIME values, use CAST() to explicitly convert the subquery value to DATETIME.
If one of the arguments is a decimal value, comparison depends on the other argument. The arguments are compared as decimal values if the other argument is a decimal or integer value, or as floating-point values if the other argument is a floating-point value.
In all other cases, the arguments are compared as floating-point (real) numbers.

For information about conversion of values from one temporal type to another, see Section 11.3.7, “Conversion Between Date and Time Types”.

Comparison of JSON values takes place at two levels. The first level of comparison is based on the JSON types of the compared values. If the types differ, the comparison result is determined solely by which type has higher precedence. If the two values have the same JSON type, a second level of comparison occurs using type-specific rules. For comparison of JSON and non-JSON values, the non-JSON value is converted to JSON and the values compared as JSON values. For details, see Comparison and Ordering of JSON Values.

The following examples illustrate conversion of strings to numbers for comparison operations:

mysql> SELECT 1 > '6x';
        -> 0
mysql> SELECT 7 > '6x';
        -> 1
mysql> SELECT 0 > 'x6';
        -> 0
mysql> SELECT 0 = 'x6';
        -> 1

For comparisons of a string column with a number, MySQL cannot use an index on the column to look up the value quickly. If str_col is an indexed string column, the index cannot be used when performing the lookup in the following statement:

SELECT * FROM tbl_name WHERE str_col=1;

The reason for this is that there are many different strings that may convert to the value 1, such as '1', ' 1', or '1a'.

Comparisons that use floating-point numbers (or values that are converted to floating-point numbers) are approximate because such numbers are inexact. This might lead to results that appear inconsistent:

mysql> SELECT '18015376320243458' = 18015376320243458;
        -> 1
mysql> SELECT '18015376320243459' = 18015376320243459;
        -> 0

Such results can occur because the values are converted to floating-point numbers, which have only 53 bits of precision and are subject to rounding:

mysql> SELECT '18015376320243459'+0.0;
        -> 1.8015376320243e+16

Furthermore, the conversion from string to floating-point and from integer to floating-point do not necessarily occur the same way. The integer may be converted to floating-point by the CPU, whereas the string is converted digit by digit in an operation that involves floating-point multiplications.

The results shown will vary on different systems, and can be affected by factors such as computer architecture or the compiler version or optimization level. One way to avoid such problems is to use CAST() so that a value is not converted implicitly to a float-point number:

mysql> SELECT CAST('18015376320243459' AS UNSIGNED) = 18015376320243459;
        -> 1

For more information about floating-point comparisons, see Section B.5.4.8, “Problems with Floating-Point Values”.

The server includes dtoa, a conversion library that provides the basis for improved conversion between string or DECIMAL values and approximate-value (FLOAT/DOUBLE) numbers:

Consistent conversion results across platforms, which eliminates, for example, Unix versus Windows conversion differences.
Accurate representation of values in cases where results previously did not provide sufficient precision, such as for values close to IEEE limits.
Conversion of numbers to string format with the best possible precision. The precision of dtoa is always the same or better than that of the standard C library functions.

Because the conversions produced by this library differ in some cases from non-dtoa results, the potential exists for incompatibilities in applications that rely on previous results. For example, applications that depend on a specific exact result from previous conversions might need adjustment to accommodate additional precision.

The dtoa library provides conversions with the following properties. D represents a value with a DECIMAL or string representation, and F represents a floating-point number in native binary (IEEE) format.

F -> D conversion is done with the best possible precision, returning D as the shortest string that yields F when read back in and rounded to the nearest value in native binary format as specified by IEEE.
D -> F conversion is done such that F is the nearest native binary number to the input decimal string D.

These properties imply that F -> D -> F conversions are lossless unless F is -inf, +inf, or NaN. The latter values are not supported because the SQL standard defines them as invalid values for FLOAT or DOUBLE.

For D -> F -> D conversions, a sufficient condition for losslessness is that D uses 15 or fewer digits of precision, is not a denormal value, -inf, +inf, or NaN. In some cases, the conversion is lossless even if D has more than 15 digits of precision, but this is not always the case.

Implicit conversion of a numeric or temporal value to string produces a value that has a character set and collation determined by the character_set_connection and collation_connection system variables. (These variables commonly are set with SET NAMES. For information about connection character sets, see Section 10.4, “Connection Character Sets and Collations”.)

This means that such a conversion results in a character (nonbinary) string (a CHAR, VARCHAR, or LONGTEXT value), except in the case that the connection character set is set to binary. In that case, the conversion result is a binary string (a BINARY, VARBINARY, or LONGBLOB value).

For integer expressions, the preceding remarks about expression evaluation apply somewhat differently for expression assignment; for example, in a statement such as this:

CREATE TABLE t SELECT integer_expr;

In this case, the table in the column resulting from the expression has type INT or BIGINT depending on the length of the integer expression. If the maximum length of the expression does not fit in an INT, BIGINT is used instead. The length is taken from the max_length value of the SELECT result set metadata (see Section 27.7.5, “C API Data Structures”). This means that you can force a BIGINT rather than INT by use of a sufficiently long expression:

CREATE TABLE t SELECT 000000000000000000000;

12.3 Operators

12.3.1 Operator Precedence
12.3.2 Comparison Functions and Operators
12.3.3 Logical Operators
12.3.4 Assignment Operators

Table 12.2 Operators

Name	Description
`AND`, `&&`	Logical AND
`=`	Assign a value (as part of a `SET` statement, or as part of the `SET` clause in an `UPDATE` statement)
`:=`	Assign a value
`BETWEEN ... AND ...`	Check whether a value is within a range of values
`BINARY`	Cast a string to a binary string
`&`	Bitwise AND
`~`	Bitwise inversion
`\|`	Bitwise OR
`^`	Bitwise XOR
`CASE`	Case operator
`DIV`	Integer division
`/`	Division operator
`=`	Equal operator
`<=>`	NULL-safe equal to operator
`>`	Greater than operator
`>=`	Greater than or equal operator
`IS`	Test a value against a boolean
`IS NOT`	Test a value against a boolean
`IS NOT NULL`	NOT NULL value test
`IS NULL`	NULL value test
`->`	Return value from JSON column after evaluating path; equivalent to JSON_EXTRACT().
`->>`	Return value from JSON column after evaluating path and unquoting the result; equivalent to JSON_UNQUOTE(JSON_EXTRACT()).
`<<`	Left shift
`<`	Less than operator
`<=`	Less than or equal operator
`LIKE`	Simple pattern matching
`-`	Minus operator
`%`, `MOD`	Modulo operator
`NOT`, `!`	Negates value
`NOT BETWEEN ... AND ...`	Check whether a value is not within a range of values
`!=`, `<>`	Not equal operator
`NOT LIKE`	Negation of simple pattern matching
`NOT REGEXP`	Negation of REGEXP
`\|\|`, `OR`	Logical OR
`+`	Addition operator
`REGEXP`	Whether string matches regular expression
`>>`	Right shift
`RLIKE`	Whether string matches regular expression
`SOUNDS LIKE`	Compare sounds
`*`	Multiplication operator
`-`	Change the sign of the argument
`XOR`	Logical XOR

12.3.1 Operator Precedence

Operator precedences are shown in the following list, from highest precedence to the lowest. Operators that are shown together on a line have the same precedence.

INTERVAL
BINARY, COLLATE
!
- (unary minus), ~ (unary bit inversion)
^
*, /, DIV, %, MOD
-, +
<<, >>
&
|
= (comparison), <=>, >=, >, <=, <, <>, !=, IS, LIKE, REGEXP, IN
BETWEEN, CASE, WHEN, THEN, ELSE
NOT
AND, &&
XOR
OR, ||
= (assignment), :=

The precedence of = depends on whether it is used as a comparison operator (=) or as an assignment operator (=). When used as a comparison operator, it has the same precedence as <=>, >=, >, <=, <, <>, !=, IS, LIKE, REGEXP, and IN. When used as an assignment operator, it has the same precedence as :=. Section 13.7.5.1, “SET Syntax for Variable Assignment”, and Section 9.4, “User-Defined Variables”, explain how MySQL determines which interpretation of = should apply.

For operators that occur at the same precedence level within an expression, evaluation proceeds left to right, with the exception that assignments evaluate right to left.

The meaning of some operators depends on the SQL mode:

By default, || is a logical OR operator. With PIPES_AS_CONCAT enabled, || is string concatenation, with a precedence between ^ and the unary operators.
By default, ! has a higher precedence than NOT. With HIGH_NOT_PRECEDENCE enabled, ! and NOT have the same precedence.

See Section 5.1.10, “Server SQL Modes”.

The precedence of operators determines the order of evaluation of terms in an expression. To override this order and group terms explicitly, use parentheses. For example:

mysql> SELECT 1+2*3;
        -> 7
mysql> SELECT (1+2)*3;
        -> 9

12.3.2 Comparison Functions and Operators

Table 12.3 Comparison Operators

Name	Description
`BETWEEN ... AND ...`	Check whether a value is within a range of values
`COALESCE()`	Return the first non-NULL argument
`=`	Equal operator
`<=>`	NULL-safe equal to operator
`>`	Greater than operator
`>=`	Greater than or equal operator
`GREATEST()`	Return the largest argument
`IN()`	Check whether a value is within a set of values
`INTERVAL()`	Return the index of the argument that is less than the first argument
`IS`	Test a value against a boolean
`IS NOT`	Test a value against a boolean
`IS NOT NULL`	NOT NULL value test
`IS NULL`	NULL value test
`ISNULL()`	Test whether the argument is NULL
`LEAST()`	Return the smallest argument
`<`	Less than operator
`<=`	Less than or equal operator
`LIKE`	Simple pattern matching
`NOT BETWEEN ... AND ...`	Check whether a value is not within a range of values
`!=`, `<>`	Not equal operator
`NOT IN()`	Check whether a value is not within a set of values
`NOT LIKE`	Negation of simple pattern matching
`STRCMP()`	Compare two strings

Comparison operations result in a value of 1 (TRUE), 0 (FALSE), or NULL. These operations work for both numbers and strings. Strings are automatically converted to numbers and numbers to strings as necessary.

The following relational comparison operators can be used to compare not only scalar operands, but row operands:

=  >  <  >=  <=  <>  !=

The descriptions for those operators later in this section detail how they work with row operands. For additional examples of row comparisons in the context of row subqueries, see Section 13.2.11.5, “Row Subqueries”.

Some of the functions in this section return values other than 1 (TRUE), 0 (FALSE), or NULL. LEAST() and GREATEST() are examples of such functions; Section 12.2, “Type Conversion in Expression Evaluation”, describes the rules for comparison operations performed by these and similar functions for determining their return values.

Note

In previous versions of MySQL, when evaluating an expression containing LEAST() or GREATEST(), the server attempted to guess the context in which the function was used, and to coerce the function's arguments to the data type of the expression as a whole. For example, the arguments to LEAST("11", "45", "2") are evaluated and sorted as strings, so that this expression returns "11". In MySQL 8.0.3 and earlier, when evaluating the expression LEAST("11", "45", "2") + 0, the server converted the arguments to integers (anticipating the addition of integer 0 to the result) before sorting them, thus returning 2.

Beginning with MySQL 8.0.4, the server no longer attempts to infer context in this fashion. Instead, the function is executed using the arguments as provided, performing data type conversions to one or more of the arguments if and only if they are not all of the same type. Any type coercion mandated by an expression that makes use of the return value is now performed following function execution. This means that, in MySQl 8.0.4 and later, LEAST("11", "45", "2") + 0 evaluates to "11" + 0 and thus to integer 11. (Bug #83895, Bug #25123839)

To convert a value to a specific type for comparison purposes, you can use the CAST() function. String values can be converted to a different character set using CONVERT(). See Section 12.10, “Cast Functions and Operators”.

By default, string comparisons are not case-sensitive and use the current character set. The default is utf8mb4.

=

Equal:

mysql> SELECT 1 = 0;
        -> 0
mysql> SELECT '0' = 0;
        -> 1
mysql> SELECT '0.0' = 0;
        -> 1
mysql> SELECT '0.01' = 0;
        -> 0
mysql> SELECT '.01' = 0.01;
        -> 1

For row comparisons, (a, b) = (x, y) is equivalent to:

(a = x) AND (b = y)

<=>
NULL-safe equal. This operator performs an equality comparison like the = operator, but returns 1 rather than NULL if both operands are NULL, and 0 rather than NULL if one operand is NULL.
The <=> operator is equivalent to the standard SQL IS NOT DISTINCT FROM operator.
```
mysql> SELECT 1 <=> 1, NULL <=> NULL, 1 <=> NULL;
 -> 1, 1, 0
mysql> SELECT 1 = 1, NULL = NULL, 1 = NULL;
 -> 1, NULL, NULL
```
For row comparisons, (a, b) <=> (x, y) is equivalent to:
```
(a <=> x) AND (b <=> y)
```

<>, !=

Not equal:

mysql> SELECT '.01' <> '0.01';
        -> 1
mysql> SELECT .01 <> '0.01';
        -> 0
mysql> SELECT 'zapp' <> 'zappp';
        -> 1

For row comparisons, (a, b) <> (x, y) and (a, b) != (x, y) are equivalent to:

(a <> x) OR (b <> y)

<=

Less than or equal:

mysql> SELECT 0.1 <= 2;
        -> 1

For row comparisons, (a, b) <= (x, y) is equivalent to:

(a < x) OR ((a = x) AND (b <= y))

<

Less than:

mysql> SELECT 2 < 2;
        -> 0

For row comparisons, (a, b) < (x, y) is equivalent to:

(a < x) OR ((a = x) AND (b < y))

>=

Greater than or equal:

mysql> SELECT 2 >= 2;
        -> 1

For row comparisons, (a, b) >= (x, y) is equivalent to:

(a > x) OR ((a = x) AND (b >= y))

>

Greater than:

mysql> SELECT 2 > 2;
        -> 0

For row comparisons, (a, b) > (x, y) is equivalent to:

(a > x) OR ((a = x) AND (b > y))

IS boolean_value
Tests a value against a boolean value, where boolean_value can be TRUE, FALSE, or UNKNOWN.
```
mysql> SELECT 1 IS TRUE, 0 IS FALSE, NULL IS UNKNOWN;
        -> 1, 1, 1
```
IS NOT boolean_value
Tests a value against a boolean value, where boolean_value can be TRUE, FALSE, or UNKNOWN.
```
mysql> SELECT 1 IS NOT UNKNOWN, 0 IS NOT UNKNOWN, NULL IS NOT UNKNOWN;
        -> 1, 1, 0
```
IS NULL
Tests whether a value is NULL.
```
mysql> SELECT 1 IS NULL, 0 IS NULL, NULL IS NULL;
        -> 0, 0, 1
```
To work well with ODBC programs, MySQL supports the following extra features when using IS NULL:
- If sql_auto_is_null variable is set to 1, then after a statement that successfully inserts an automatically generated AUTO_INCREMENT value, you can find that value by issuing a statement of the following form:
```
SELECT * FROM tbl_name WHERE auto_col IS NULL
```
  If the statement returns a row, the value returned is the same as if you invoked the LAST_INSERT_ID() function. For details, including the return value after a multiple-row insert, see Section 12.14, “Information Functions”. If no AUTO_INCREMENT value was successfully inserted, the SELECT statement returns no row.
  The behavior of retrieving an AUTO_INCREMENT value by using an IS NULL comparison can be disabled by setting sql_auto_is_null = 0. See Section 5.1.7, “Server System Variables”.
  The default value of sql_auto_is_null is 0.
- For DATE and DATETIME columns that are declared as NOT NULL, you can find the special date '0000-00-00' by using a statement like this:
```
SELECT * FROM tbl_name WHERE date_column IS NULL
```
  This is needed to get some ODBC applications to work because ODBC does not support a '0000-00-00' date value.
  See Obtaining Auto-Increment Values, and the description for the FLAG_AUTO_IS_NULL option at Connector/ODBC Connection Parameters.

IS NOT NULL

Tests whether a value is not NULL.

mysql> SELECT 1 IS NOT NULL, 0 IS NOT NULL, NULL IS NOT NULL;
        -> 1, 1, 0

expr BETWEEN min AND max
If expr is greater than or equal to min and expr is less than or equal to max, BETWEEN returns 1, otherwise it returns 0. This is equivalent to the expression (min <= expr AND expr <= max) if all the arguments are of the same type. Otherwise type conversion takes place according to the rules described in Section 12.2, “Type Conversion in Expression Evaluation”, but applied to all the three arguments.
```
mysql> SELECT 2 BETWEEN 1 AND 3, 2 BETWEEN 3 and 1;
 -> 1, 0
mysql> SELECT 1 BETWEEN 2 AND 3;
 -> 0
mysql> SELECT 'b' BETWEEN 'a' AND 'c';
 -> 1
mysql> SELECT 2 BETWEEN 2 AND '3';
 -> 1
mysql> SELECT 2 BETWEEN 2 AND 'x-3';
 -> 0
```
For best results when using BETWEEN with date or time values, use CAST() to explicitly convert the values to the desired data type. Examples: If you compare a DATETIME to two DATE values, convert the DATE values to DATETIME values. If you use a string constant such as '2001-1-1' in a comparison to a DATE, cast the string to a DATE.
expr NOT BETWEEN min AND max
This is the same as NOT (expr BETWEEN min AND max).
COALESCE(value,...)
Returns the first non-NULL value in the list, or NULL if there are no non-NULL values.
The return type of COALESCE() is the aggregated type of the argument types.
```
mysql> SELECT COALESCE(NULL,1);
        -> 1
mysql> SELECT COALESCE(NULL,NULL,NULL);
        -> NULL
```
GREATEST(value1,value2,...)
With two or more arguments, returns the largest (maximum-valued) argument. The arguments are compared using the same rules as for LEAST().
```
mysql> SELECT GREATEST(2,0);
        -> 2
mysql> SELECT GREATEST(34.0,3.0,5.0,767.0);
        -> 767.0
mysql> SELECT GREATEST('B','A','C');
        -> 'C'
```
GREATEST() returns NULL if any argument is NULL.
expr IN (value,...)
Returns 1 if expr is equal to any of the values in the IN list, else returns 0. If all values are constants, they are evaluated according to the type of expr and sorted. The search for the item then is done using a binary search. This means IN is very quick if the IN value list consists entirely of constants. Otherwise, type conversion takes place according to the rules described in Section 12.2, “Type Conversion in Expression Evaluation”, but applied to all the arguments.
```
mysql> SELECT 2 IN (0,3,5,7);
        -> 0
mysql> SELECT 'wefwf' IN ('wee','wefwf','weg');
        -> 1
```
IN can be used to compare row constructors:
```
mysql> SELECT (3,4) IN ((1,2), (3,4));
        -> 1
mysql> SELECT (3,4) IN ((1,2), (3,5));
        -> 0
```
You should never mix quoted and unquoted values in an IN list because the comparison rules for quoted values (such as strings) and unquoted values (such as numbers) differ. Mixing types may therefore lead to inconsistent results. For example, do not write an IN expression like this:
```
SELECT val1 FROM tbl1 WHERE val1 IN (1,2,'a');
```
Instead, write it like this:
```
SELECT val1 FROM tbl1 WHERE val1 IN ('1','2','a');
```
The number of values in the IN list is only limited by the max_allowed_packet value.
To comply with the SQL standard, IN returns NULL not only if the expression on the left hand side is NULL, but also if no match is found in the list and one of the expressions in the list is NULL.
IN() syntax can also be used to write certain types of subqueries. See Section 13.2.11.3, “Subqueries with ANY, IN, or SOME”.
expr NOT IN (value,...)
This is the same as NOT (expr IN (value,...)).
ISNULL(expr)
If expr is NULL, ISNULL() returns 1, otherwise it returns 0.
```
mysql> SELECT ISNULL(1+1);
        -> 0
mysql> SELECT ISNULL(1/0);
        -> 1
```
ISNULL() can be used instead of = to test whether a value is NULL. (Comparing a value to NULL using = always yields NULL.)
The ISNULL() function shares some special behaviors with the IS NULL comparison operator. See the description of IS NULL.
INTERVAL(N,N1,N2,N3,...)
Returns 0 if N < N1, 1 if N < N2 and so on or -1 if N is NULL. All arguments are treated as integers. It is required that N1 < N2 < N3 < ... < Nn for this function to work correctly. This is because a binary search is used (very fast).
```
mysql> SELECT INTERVAL(23, 1, 15, 17, 30, 44, 200);
 -> 3
mysql> SELECT INTERVAL(10, 1, 10, 100, 1000);
 -> 2
mysql> SELECT INTERVAL(22, 23, 30, 44, 200);
 -> 0
```
LEAST(value1,value2,...)
With two or more arguments, returns the smallest (minimum-valued) argument. The arguments are compared using the following rules:
- If any argument is NULL, the result is NULL. No comparison is needed.
- If all arguments are integer-valued, they are compared as integers.
- If at least one argument is double precision, they are compared as double-precision values. Otherwise, if at least one argument is a DECIMAL value, they are compared as DECIMAL values.
- If the arguments comprise a mix of numbers and strings, they are compared as numbers.
- If any argument is a nonbinary (character) string, the arguments are compared as nonbinary strings.
- In all other cases, the arguments are compared as binary strings.
The return type of LEAST() is the aggregated type of the comparison argument types.
```
mysql> SELECT LEAST(2,0);
        -> 0
mysql> SELECT LEAST(34.0,3.0,5.0,767.0);
        -> 3.0
mysql> SELECT LEAST('B','A','C');
        -> 'A'
```

12.3.3 Logical Operators

Table 12.4 Logical Operators

Name	Description
`AND`, `&&`	Logical AND
`NOT`, `!`	Negates value
`\|\|`, `OR`	Logical OR
`XOR`	Logical XOR

In SQL, all logical operators evaluate to TRUE, FALSE, or NULL (UNKNOWN). In MySQL, these are implemented as 1 (TRUE), 0 (FALSE), and NULL. Most of this is common to different SQL database servers, although some servers may return any nonzero value for TRUE.

MySQL evaluates any nonzero, non-NULL value to TRUE. For example, the following statements all assess to TRUE:

mysql> SELECT 10 IS TRUE;
-> 1
mysql> SELECT -10 IS TRUE;
-> 1
mysql> SELECT 'string' IS NOT NULL;
-> 1

NOT, !

Logical NOT. Evaluates to 1 if the operand is 0, to 0 if the operand is nonzero, and NOT NULL returns NULL.

mysql> SELECT NOT 10;
        -> 0
mysql> SELECT NOT 0;
        -> 1
mysql> SELECT NOT NULL;
        -> NULL
mysql> SELECT ! (1+1);
        -> 0
mysql> SELECT ! 1+1;
        -> 1

The last example produces 1 because the expression evaluates the same way as (!1)+1.

AND, &&

Logical AND. Evaluates to 1 if all operands are nonzero and not NULL, to 0 if one or more operands are 0, otherwise NULL is returned.

mysql> SELECT 1 AND 1;
        -> 1
mysql> SELECT 1 AND 0;
        -> 0
mysql> SELECT 1 AND NULL;
        -> NULL
mysql> SELECT 0 AND NULL;
        -> 0
mysql> SELECT NULL AND 0;
        -> 0

OR, ||
Logical OR. When both operands are non-NULL, the result is 1 if any operand is nonzero, and 0 otherwise. With a NULL operand, the result is 1 if the other operand is nonzero, and NULL otherwise. If both operands are NULL, the result is NULL.
```
mysql> SELECT 1 OR 1;
        -> 1
mysql> SELECT 1 OR 0;
        -> 1
mysql> SELECT 0 OR 0;
        -> 0
mysql> SELECT 0 OR NULL;
        -> NULL
mysql> SELECT 1 OR NULL;
        -> 1
```
XOR
Logical XOR. Returns NULL if either operand is NULL. For non-NULL operands, evaluates to 1 if an odd number of operands is nonzero, otherwise 0 is returned.
```
mysql> SELECT 1 XOR 1;
        -> 0
mysql> SELECT 1 XOR 0;
        -> 1
mysql> SELECT 1 XOR NULL;
        -> NULL
mysql> SELECT 1 XOR 1 XOR 1;
        -> 1
```
a XOR b is mathematically equal to (a AND (NOT b)) OR ((NOT a) and b).

12.3.4 Assignment Operators

Table 12.5 Assignment Operators

Name	Description
`=`	Assign a value (as part of a `SET` statement, or as part of the `SET` clause in an `UPDATE` statement)
`:=`	Assign a value

:=
Assignment operator. Causes the user variable on the left hand side of the operator to take on the value to its right. The value on the right hand side may be a literal value, another variable storing a value, or any legal expression that yields a scalar value, including the result of a query (provided that this value is a scalar value). You can perform multiple assignments in the same SET statement. You can perform multiple assignments in the same statement.
Unlike =, the := operator is never interpreted as a comparison operator. This means you can use := in any valid SQL statement (not just in SET statements) to assign a value to a variable.
```
mysql> SELECT @var1, @var2;
        -> NULL, NULL
mysql> SELECT @var1 := 1, @var2;
        -> 1, NULL
mysql> SELECT @var1, @var2;
        -> 1, NULL
mysql> SELECT @var1, @var2 := @var1;
        -> 1, 1
mysql> SELECT @var1, @var2;
        -> 1, 1

mysql> SELECT @var1:=COUNT(*) FROM t1;
        -> 4
mysql> SELECT @var1;
        -> 4
```
You can make value assignments using := in other statements besides SELECT, such as UPDATE, as shown here:
```
mysql> SELECT @var1;
        -> 4
mysql> SELECT * FROM t1;
        -> 1, 3, 5, 7

mysql> UPDATE t1 SET c1 = 2 WHERE c1 = @var1:= 1;
Query OK, 1 row affected (0.00 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT @var1;
        -> 1
mysql> SELECT * FROM t1;
        -> 2, 3, 5, 7
```
While it is also possible both to set and to read the value of the same variable in a single SQL statement using the := operator, this is not recommended. Section 9.4, “User-Defined Variables”, explains why you should avoid doing this.
=
This operator is used to perform value assignments in two cases, described in the next two paragraphs.
Within a SET statement, = is treated as an assignment operator that causes the user variable on the left hand side of the operator to take on the value to its right. (In other words, when used in a SET statement, = is treated identically to :=.) The value on the right hand side may be a literal value, another variable storing a value, or any legal expression that yields a scalar value, including the result of a query (provided that this value is a scalar value). You can perform multiple assignments in the same SET statement.
In the SET clause of an UPDATE statement, = also acts as an assignment operator; in this case, however, it causes the column named on the left hand side of the operator to assume the value given to the right, provided any WHERE conditions that are part of the UPDATE are met. You can make multiple assignments in the same SET clause of an UPDATE statement.
In any other context, = is treated as a comparison operator.
```
mysql> SELECT @var1, @var2;
        -> NULL, NULL
mysql> SELECT @var1 := 1, @var2;
        -> 1, NULL
mysql> SELECT @var1, @var2;
        -> 1, NULL
mysql> SELECT @var1, @var2 := @var1;
        -> 1, 1
mysql> SELECT @var1, @var2;
        -> 1, 1
```
For more information, see Section 13.7.5.1, “SET Syntax for Variable Assignment”, Section 13.2.12, “UPDATE Syntax”, and Section 13.2.11, “Subquery Syntax”.

12.4 Control Flow Functions

Table 12.6 Flow Control Operators

Name	Description
`CASE`	Case operator
`IF()`	If/else construct
`IFNULL()`	Null if/else construct
`NULLIF()`	Return NULL if expr1 = expr2

CASE value WHEN [compare_value] THEN result [WHEN [compare_value] THEN result ...] [ELSE result] END
CASE WHEN [condition] THEN result [WHEN [condition] THEN result ...] [ELSE result] END
The first CASE syntax returns the result for the first value=compare_value comparison that is true. The second syntax returns the result for the first condition that is true. If no comparison or condition is true, the result after ELSE is returned, or NULL if there is no ELSE part.

Note

The syntax of the CASE expression described here differs slightly from that of the SQL CASE statement described in Section 13.6.5.1, “CASE Syntax”, for use inside stored programs. The CASE statement cannot have an ELSE NULL clause, and it is terminated with END CASE instead of END.

The return type of a CASE expression result is the aggregated type of all result values:
- If all types are numeric, the aggregated type is also numeric:
  - If at least one argument is double precision, the result is double precision.
  - Otherwise, if at least one argument is DECIMAL, the result is DECIMAL.
  - Otherwise, the result is an integer type (with one exception):
    
    If all integer types are all signed or all unsigned, the result is the same sign and the precision is the highest of all specified integer types (that is, TINYINT, SMALLINT, MEDIUMINT, INT, or BIGINT).
    If there is a combination of signed and unsigned integer types, the result is signed and the precision may be higher. For example, if the types are signed INT and unsigned INT, the result is signed BIGINT.
    The exception is unsigned BIGINT combined with any signed integer type. The result is DECIMAL with sufficient precision and scale 0.
- If all types are BIT, the result is BIT. Otherwise, BIT arguments are treated similar to BIGINT.
- If all types are YEAR, the result is YEAR. Otherwise, YEAR arguments are treated similar to INT.
- If all types are character string (CHAR or VARCHAR), the result is VARCHAR with maximum length determined by the longest character length of the operands.
- If all types are character or binary string, the result is VARBINARY.
- SET and ENUM are treated similar to VARCHAR; the result is VARCHAR.
- If all types are JSON, the result is JSON.
- If all types are temporal, the result is temporal:
  - If all temporal types are DATE, TIME, or TIMESTAMP, the result is DATE, TIME, or TIMESTAMP, respectively.
  - Otherwise, for a mix of temporal types, the result is DATETIME.
- If all types are GEOMETRY, the result is GEOMETRY.
- If any type is BLOB, the result is BLOB.
- For all other type combinations, the result is VARCHAR.
- Literal NULL operands are ignored for type aggregation.
```
mysql> SELECT CASE 1 WHEN 1 THEN 'one'
    ->     WHEN 2 THEN 'two' ELSE 'more' END;
        -> 'one'
mysql> SELECT CASE WHEN 1>0 THEN 'true' ELSE 'false' END;
        -> 'true'
mysql> SELECT CASE BINARY 'B'
    ->     WHEN 'a' THEN 1 WHEN 'b' THEN 2 END;
        -> NULL
```
IF(expr1,expr2,expr3)
If expr1 is TRUE (expr1 <> 0 and expr1 <> NULL), IF() returns expr2. Otherwise, it returns expr3.

Note

There is also an IF statement, which differs from the IF() function described here. See Section 13.6.5.2, “IF Syntax”.

If only one of expr2 or expr3 is explicitly NULL, the result type of the IF() function is the type of the non-NULL expression.
The default return type of IF() (which may matter when it is stored into a temporary table) is calculated as follows:
- If expr2 or expr3 produce a string, the result is a string.
 If expr2 and expr3 are both strings, the result is case-sensitive if either string is case sensitive.
- If expr2 or expr3 produce a floating-point value, the result is a floating-point value.
- If expr2 or expr3 produce an integer, the result is an integer.
```
mysql> SELECT IF(1>2,2,3);
 -> 3
mysql> SELECT IF(1<2,'yes','no');
 -> 'yes'
mysql> SELECT IF(STRCMP('test','test1'),'no','yes');
 -> 'no'
```

IFNULL(expr1,expr2)

If expr1 is not NULL, IFNULL() returns expr1; otherwise it returns expr2.

mysql> SELECT IFNULL(1,0);
        -> 1
mysql> SELECT IFNULL(NULL,10);
        -> 10
mysql> SELECT IFNULL(1/0,10);
        -> 10
mysql> SELECT IFNULL(1/0,'yes');
        -> 'yes'

The default return type of IFNULL(expr1,expr2) is the more “general” of the two expressions, in the order STRING, REAL, or INTEGER. Consider the case of a table based on expressions or where MySQL must internally store a value returned by IFNULL() in a temporary table:


mysql> CREATE TABLE tmp SELECT IFNULL(1,'test') AS test;
mysql> DESCRIBE tmp;
+-------+--------------+------+-----+---------+-------+
| Field | Type         | Null | Key | Default | Extra |
+-------+--------------+------+-----+---------+-------+
| test  | varbinary(4) | NO   |     |         |       |
+-------+--------------+------+-----+---------+-------+

In this example, the type of the test column is VARBINARY(4) (a string type).

NULLIF(expr1,expr2)
Returns NULL if expr1 = expr2 is true, otherwise returns expr1. This is the same as CASE WHEN expr1 = expr2 THEN NULL ELSE expr1 END.
The return value has the same type as the first argument.
```
mysql> SELECT NULLIF(1,1);
        -> NULL
mysql> SELECT NULLIF(1,2);
        -> 1
```
Note

MySQL evaluates expr1 twice if the arguments are not equal.

12.5 String Functions

12.5.1 String Comparison Functions
12.5.2 Regular Expressions
12.5.3 Character Set and Collation of Function Results

Table 12.7 String Operators

Name	Description
`ASCII()`	Return numeric value of left-most character
`BIN()`	Return a string containing binary representation of a number
`BIT_LENGTH()`	Return length of argument in bits
`CHAR()`	Return the character for each integer passed
`CHAR_LENGTH()`	Return number of characters in argument
`CHARACTER_LENGTH()`	Synonym for CHAR_LENGTH()
`CONCAT()`	Return concatenated string
`CONCAT_WS()`	Return concatenate with separator
`ELT()`	Return string at index number
`EXPORT_SET()`	Return a string such that for every bit set in the value bits, you get an on string and for every unset bit, you get an off string
`FIELD()`	Return the index (position) of the first argument in the subsequent arguments
`FIND_IN_SET()`	Return the index position of the first argument within the second argument
`FORMAT()`	Return a number formatted to specified number of decimal places
`FROM_BASE64()`	Decode to a base-64 string and return result
`HEX()`	Return a hexadecimal representation of a decimal or string value
`INSERT()`	Insert a substring at the specified position up to the specified number of characters
`INSTR()`	Return the index of the first occurrence of substring
`LCASE()`	Synonym for LOWER()
`LEFT()`	Return the leftmost number of characters as specified
`LENGTH()`	Return the length of a string in bytes
`LIKE`	Simple pattern matching
`LOAD_FILE()`	Load the named file
`LOCATE()`	Return the position of the first occurrence of substring
`LOWER()`	Return the argument in lowercase
`LPAD()`	Return the string argument, left-padded with the specified string
`LTRIM()`	Remove leading spaces
`MAKE_SET()`	Return a set of comma-separated strings that have the corresponding bit in bits set
`MATCH`	Perform full-text search
`MID()`	Return a substring starting from the specified position
`NOT LIKE`	Negation of simple pattern matching
`NOT REGEXP`	Negation of REGEXP
`OCT()`	Return a string containing octal representation of a number
`OCTET_LENGTH()`	Synonym for LENGTH()
`ORD()`	Return character code for leftmost character of the argument
`POSITION()`	Synonym for LOCATE()
`QUOTE()`	Escape the argument for use in an SQL statement
`REGEXP`	Whether string matches regular expression
`REGEXP_INSTR()`	Starting index of substring matching regular expression
`REGEXP_LIKE()`	Whether string matches regular expression
`REGEXP_REPLACE()`	Replace substrings matching regular expression
`REGEXP_SUBSTR()`	Return substring matching regular expression
`REPEAT()`	Repeat a string the specified number of times
`REPLACE()`	Replace occurrences of a specified string
`REVERSE()`	Reverse the characters in a string
`RIGHT()`	Return the specified rightmost number of characters
`RLIKE`	Whether string matches regular expression
`RPAD()`	Append string the specified number of times
`RTRIM()`	Remove trailing spaces
`SOUNDEX()`	Return a soundex string
`SOUNDS LIKE`	Compare sounds
`SPACE()`	Return a string of the specified number of spaces
`STRCMP()`	Compare two strings
`SUBSTR()`	Return the substring as specified
`SUBSTRING()`	Return the substring as specified
`SUBSTRING_INDEX()`	Return a substring from a string before the specified number of occurrences of the delimiter
`TO_BASE64()`	Return the argument converted to a base-64 string
`TRIM()`	Remove leading and trailing spaces
`UCASE()`	Synonym for UPPER()
`UNHEX()`	Return a string containing hex representation of a number
`UPPER()`	Convert to uppercase
`WEIGHT_STRING()`	Return the weight string for a string

String-valued functions return NULL if the length of the result would be greater than the value of the max_allowed_packet system variable. See Section 5.1.1, “Configuring the Server”.

For functions that operate on string positions, the first position is numbered 1.

For functions that take length arguments, noninteger arguments are rounded to the nearest integer.

ASCII(str)
Returns the numeric value of the leftmost character of the string str. Returns 0 if str is the empty string. Returns NULL if str is NULL. ASCII() works for 8-bit characters.
```
mysql> SELECT ASCII('2');
        -> 50
mysql> SELECT ASCII(2);
        -> 50
mysql> SELECT ASCII('dx');
        -> 100
```
See also the ORD() function.
BIN(N)
Returns a string representation of the binary value of N, where N is a longlong (BIGINT) number. This is equivalent to CONV(N,10,2). Returns NULL if N is NULL.
```
mysql> SELECT BIN(12);
        -> '1100'
```

BIT_LENGTH(str)

Returns the length of the string str in bits.

mysql> SELECT BIT_LENGTH('text');
        -> 32

CHAR(N,... [USING charset_name])

CHAR() interprets each argument N as an integer and returns a string consisting of the characters given by the code values of those integers. NULL values are skipped.

mysql> SELECT CHAR(77,121,83,81,'76');
        -> 'MySQL'
mysql> SELECT CHAR(77,77.3,'77.3');
        -> 'MMM'

CHAR() arguments larger than 255 are converted into multiple result bytes. For example, CHAR(256) is equivalent to CHAR(1,0), and CHAR(256*256) is equivalent to CHAR(1,0,0):

mysql> SELECT HEX(CHAR(1,0)), HEX(CHAR(256));
+----------------+----------------+
| HEX(CHAR(1,0)) | HEX(CHAR(256)) |
+----------------+----------------+
| 0100           | 0100           |
+----------------+----------------+
mysql> SELECT HEX(CHAR(1,0,0)), HEX(CHAR(256*256));
+------------------+--------------------+
| HEX(CHAR(1,0,0)) | HEX(CHAR(256*256)) |
+------------------+--------------------+
| 010000           | 010000             |
+------------------+--------------------+

By default, CHAR() returns a binary string. To produce a string in a given character set, use the optional USING clause:

mysql> SELECT CHARSET(CHAR(X'65')), CHARSET(CHAR(X'65' USING utf8));
+----------------------+---------------------------------+
| CHARSET(CHAR(X'65')) | CHARSET(CHAR(X'65' USING utf8)) |
+----------------------+---------------------------------+
| binary               | utf8                            |
+----------------------+---------------------------------+

If USING is given and the result string is illegal for the given character set, a warning is issued. Also, if strict SQL mode is enabled, the result from CHAR() becomes NULL.

CHAR_LENGTH(str)
Returns the length of the string str, measured in characters. A multibyte character counts as a single character. This means that for a string containing five 2-byte characters, LENGTH() returns 10, whereas CHAR_LENGTH() returns 5.
CHARACTER_LENGTH(str)
CHARACTER_LENGTH() is a synonym for CHAR_LENGTH().
CONCAT(str1,str2,...)
Returns the string that results from concatenating the arguments. May have one or more arguments. If all arguments are nonbinary strings, the result is a nonbinary string. If the arguments include any binary strings, the result is a binary string. A numeric argument is converted to its equivalent nonbinary string form.
CONCAT() returns NULL if any argument is NULL.
```
mysql> SELECT CONCAT('My', 'S', 'QL');
        -> 'MySQL'
mysql> SELECT CONCAT('My', NULL, 'QL');
        -> NULL
mysql> SELECT CONCAT(14.3);
        -> '14.3'
```
For quoted strings, concatenation can be performed by placing the strings next to each other:
```
mysql> SELECT 'My' 'S' 'QL';
        -> 'MySQL'
```
CONCAT_WS(separator,str1,str2,...)
CONCAT_WS() stands for Concatenate With Separator and is a special form of CONCAT(). The first argument is the separator for the rest of the arguments. The separator is added between the strings to be concatenated. The separator can be a string, as can the rest of the arguments. If the separator is NULL, the result is NULL.
```
mysql> SELECT CONCAT_WS(',','First name','Second name','Last Name');
        -> 'First name,Second name,Last Name'
mysql> SELECT CONCAT_WS(',','First name',NULL,'Last Name');
        -> 'First name,Last Name'
```
CONCAT_WS() does not skip empty strings. However, it does skip any NULL values after the separator argument.
ELT(N,str1,str2,str3,...)
ELT() returns the Nth element of the list of strings: str1 if N = 1, str2 if N = 2, and so on. Returns NULL if N is less than 1 or greater than the number of arguments. ELT() is the complement of FIELD().
```
mysql> SELECT ELT(1, 'Aa', 'Bb', 'Cc', 'Dd');
        -> 'Aa'
mysql> SELECT ELT(4, 'Aa', 'Bb', 'Cc', 'Dd');
        -> 'Dd'
```
EXPORT_SET(bits,on,off[,separator[,number_of_bits]])
Returns a string such that for every bit set in the value bits, you get an on string and for every bit not set in the value, you get an off string. Bits in bits are examined from right to left (from low-order to high-order bits). Strings are added to the result from left to right, separated by the separator string (the default being the comma character ,). The number of bits examined is given by number_of_bits, which has a default of 64 if not specified. number_of_bits is silently clipped to 64 if larger than 64. It is treated as an unsigned integer, so a value of −1 is effectively the same as 64.
```
mysql> SELECT EXPORT_SET(5,'Y','N',',',4);
        -> 'Y,N,Y,N'
mysql> SELECT EXPORT_SET(6,'1','0',',',10);
        -> '0,1,1,0,0,0,0,0,0,0'
```
FIELD(str,str1,str2,str3,...)
Returns the index (position) of str in the str1, str2, str3, ... list. Returns 0 if str is not found.
If all arguments to FIELD() are strings, all arguments are compared as strings. If all arguments are numbers, they are compared as numbers. Otherwise, the arguments are compared as double.
If str is NULL, the return value is 0 because NULL fails equality comparison with any value. FIELD() is the complement of ELT().
```
mysql> SELECT FIELD('Bb', 'Aa', 'Bb', 'Cc', 'Dd', 'Ff');
        -> 2
mysql> SELECT FIELD('Gg', 'Aa', 'Bb', 'Cc', 'Dd', 'Ff');
        -> 0
```
FIND_IN_SET(str,strlist)
Returns a value in the range of 1 to N if the string str is in the string list strlist consisting of N substrings. A string list is a string composed of substrings separated by , characters. If the first argument is a constant string and the second is a column of type SET, the FIND_IN_SET() function is optimized to use bit arithmetic. Returns 0 if str is not in strlist or if strlist is the empty string. Returns NULL if either argument is NULL. This function does not work properly if the first argument contains a comma (,) character.
```
mysql> SELECT FIND_IN_SET('b','a,b,c,d');
        -> 2
```
FORMAT(X,D[,locale])
Formats the number X to a format like '#,###,###.##', rounded to D decimal places, and returns the result as a string. If D is 0, the result has no decimal point or fractional part.
The optional third parameter enables a locale to be specified to be used for the result number's decimal point, thousands separator, and grouping between separators. Permissible locale values are the same as the legal values for the lc_time_names system variable (see Section 10.15, “MySQL Server Locale Support”). If no locale is specified, the default is 'en_US'.
```
mysql> SELECT FORMAT(12332.123456, 4);
        -> '12,332.1235'
mysql> SELECT FORMAT(12332.1,4);
        -> '12,332.1000'
mysql> SELECT FORMAT(12332.2,0);
        -> '12,332'
mysql> SELECT FORMAT(12332.2,2,'de_DE');
        -> '12.332,20'
```
FROM_BASE64(str)
Takes a string encoded with the base-64 encoded rules used by TO_BASE64() and returns the decoded result as a binary string. The result is NULL if the argument is NULL or not a valid base-64 string. See the description of TO_BASE64() for details about the encoding and decoding rules.
```
mysql> SELECT TO_BASE64('abc'), FROM_BASE64(TO_BASE64('abc'));
        -> 'JWJj', 'abc'
```
HEX(str), HEX(N)
For a string argument str, HEX() returns a hexadecimal string representation of str where each byte of each character in str is converted to two hexadecimal digits. (Multibyte characters therefore become more than two digits.) The inverse of this operation is performed by the UNHEX() function.
For a numeric argument N, HEX() returns a hexadecimal string representation of the value of N treated as a longlong (BIGINT) number. This is equivalent to CONV(N,10,16). The inverse of this operation is performed by CONV(HEX(N),16,10).
```
mysql> SELECT X'616263', HEX('abc'), UNHEX(HEX('abc'));
        -> 'abc', 616263, 'abc'
mysql> SELECT HEX(255), CONV(HEX(255),16,10);
        -> 'FF', 255
```
INSERT(str,pos,len,newstr)
Returns the string str, with the substring beginning at position pos and len characters long replaced by the string newstr. Returns the original string if pos is not within the length of the string. Replaces the rest of the string from position pos if len is not within the length of the rest of the string. Returns NULL if any argument is NULL.
```
mysql> SELECT INSERT('Quadratic', 3, 4, 'What');
        -> 'QuWhattic'
mysql> SELECT INSERT('Quadratic', -1, 4, 'What');
        -> 'Quadratic'
mysql> SELECT INSERT('Quadratic', 3, 100, 'What');
        -> 'QuWhat'
```
This function is multibyte safe.
INSTR(str,substr)
Returns the position of the first occurrence of substring substr in string str. This is the same as the two-argument form of LOCATE(), except that the order of the arguments is reversed.
```
mysql> SELECT INSTR('foobarbar', 'bar');
        -> 4
mysql> SELECT INSTR('xbar', 'foobar');
        -> 0
```
This function is multibyte safe, and is case-sensitive only if at least one argument is a binary string.
LCASE(str)
LCASE() is a synonym for LOWER().
LCASE() used in a view is rewritten as LOWER() when storing the view's definition. (Bug #12844279)
LEFT(str,len)
Returns the leftmost len characters from the string str, or NULL if any argument is NULL.
```
mysql> SELECT LEFT('foobarbar', 5);
        -> 'fooba'
```
This function is multibyte safe.
LENGTH(str)
Returns the length of the string str, measured in bytes. A multibyte character counts as multiple bytes. This means that for a string containing five 2-byte characters, LENGTH() returns 10, whereas CHAR_LENGTH() returns 5.
```
mysql> SELECT LENGTH('text');
        -> 4
```
Note

The Length() OpenGIS spatial function is named ST_Length() in MySQL.
LOAD_FILE(file_name)
Reads the file and returns the file contents as a string. To use this function, the file must be located on the server host, you must specify the full path name to the file, and you must have the FILE privilege. The file must be readable by all and its size less than max_allowed_packet bytes. If the secure_file_priv system variable is set to a nonempty directory name, the file to be loaded must be located in that directory.
If the file does not exist or cannot be read because one of the preceding conditions is not satisfied, the function returns NULL.
The character_set_filesystem system variable controls interpretation of file names that are given as literal strings.
```
mysql> UPDATE t
            SET blob_col=LOAD_FILE('/tmp/picture')
            WHERE id=1;
```
LOCATE(substr,str), LOCATE(substr,str,pos)
The first syntax returns the position of the first occurrence of substring substr in string str. The second syntax returns the position of the first occurrence of substring substr in string str, starting at position pos. Returns 0 if substr is not in str. Returns NULL if any argument is NULL.
```
mysql> SELECT LOCATE('bar', 'foobarbar');
        -> 4
mysql> SELECT LOCATE('xbar', 'foobar');
        -> 0
mysql> SELECT LOCATE('bar', 'foobarbar', 5);
        -> 7
```
This function is multibyte safe, and is case-sensitive only if at least one argument is a binary string.
LOWER(str)
Returns the string str with all characters changed to lowercase according to the current character set mapping. The default is utf8mb4.
```
mysql> SELECT LOWER('QUADRATICALLY');
        -> 'quadratically'
```
LOWER() (and UPPER()) are ineffective when applied to binary strings (BINARY, VARBINARY, BLOB). To perform lettercase conversion, convert the string to a nonbinary string:
```
mysql> SET @str = BINARY 'New York';
mysql> SELECT LOWER(@str), LOWER(CONVERT(@str USING utf8mb4));
+-------------+------------------------------------+
| LOWER(@str) | LOWER(CONVERT(@str USING utf8mb4)) |
+-------------+------------------------------------+
| New York    | new york                           |
+-------------+------------------------------------+
```
For collations of Unicode character sets, LOWER() and UPPER() work according to the Unicode Collation Algorithm (UCA) version in the collation name, if there is one, and UCA 4.0.0 if no version is specified. For example, utf8mb4_0900_ai_ci and utf8_unicode_520_ci work according to UCA 9.0.0 and 5.2.0, respectively, whereas utf8_unicode_ci works according to UCA 4.0.0. See Section 10.10.1, “Unicode Character Sets”.
This function is multibyte safe.
LCASE() used within views is rewritten as LOWER().
LPAD(str,len,padstr)
Returns the string str, left-padded with the string padstr to a length of len characters. If str is longer than len, the return value is shortened to len characters.
```
mysql> SELECT LPAD('hi',4,'??');
        -> '??hi'
mysql> SELECT LPAD('hi',1,'??');
        -> 'h'
```
LTRIM(str)
Returns the string str with leading space characters removed.
```
mysql> SELECT LTRIM('  barbar');
        -> 'barbar'
```
This function is multibyte safe.
MAKE_SET(bits,str1,str2,...)
Returns a set value (a string containing substrings separated by , characters) consisting of the strings that have the corresponding bit in bits set. str1 corresponds to bit 0, str2 to bit 1, and so on. NULL values in str1, str2, ... are not appended to the result.
```
mysql> SELECT MAKE_SET(1,'a','b','c');
        -> 'a'
mysql> SELECT MAKE_SET(1 | 4,'hello','nice','world');
        -> 'hello,world'
mysql> SELECT MAKE_SET(1 | 4,'hello','nice',NULL,'world');
        -> 'hello'
mysql> SELECT MAKE_SET(0,'a','b','c');
        -> ''
```
MID(str,pos,len)
MID(str,pos,len) is a synonym for SUBSTRING(str,pos,len).
OCT(N)
Returns a string representation of the octal value of N, where N is a longlong (BIGINT) number. This is equivalent to CONV(N,10,8). Returns NULL if N is NULL.
```
mysql> SELECT OCT(12);
        -> '14'
```
OCTET_LENGTH(str)
OCTET_LENGTH() is a synonym for LENGTH().
ORD(str)
If the leftmost character of the string str is a multibyte character, returns the code for that character, calculated from the numeric values of its constituent bytes using this formula:
```
  (1st byte code)
+ (2nd byte code * 256)
+ (3rd byte code * 256^2) ...
```
If the leftmost character is not a multibyte character, ORD() returns the same value as the ASCII() function.
```
mysql> SELECT ORD('2');
        -> 50
```
POSITION(substr IN str)
POSITION(substr IN str) is a synonym for LOCATE(substr,str).
QUOTE(str)
Quotes a string to produce a result that can be used as a properly escaped data value in an SQL statement. The string is returned enclosed by single quotation marks and with each instance of backslash (\), single quote ('), ASCII NUL, and Control+Z preceded by a backslash. If the argument is NULL, the return value is the word “NULL” without enclosing single quotation marks.
```
mysql> SELECT QUOTE('Don\'t!');
        -> 'Don\'t!'
mysql> SELECT QUOTE(NULL);
        -> NULL
```
For comparison, see the quoting rules for literal strings and within the C API in Section 9.1.1, “String Literals”, and Section 27.7.7.56, “mysql_real_escape_string_quote()”.
REPEAT(str,count)
Returns a string consisting of the string str repeated count times. If count is less than 1, returns an empty string. Returns NULL if str or count are NULL.
```
mysql> SELECT REPEAT('MySQL', 3);
        -> 'MySQLMySQLMySQL'
```
REPLACE(str,from_str,to_str)
Returns the string str with all occurrences of the string from_str replaced by the string to_str. REPLACE() performs a case-sensitive match when searching for from_str.
```
mysql> SELECT REPLACE('www.mysql.com', 'w', 'Ww');
        -> 'WwWwWw.mysql.com'
```
This function is multibyte safe.
REVERSE(str)
Returns the string str with the order of the characters reversed.
```
mysql> SELECT REVERSE('abc');
        -> 'cba'
```
This function is multibyte safe.
RIGHT(str,len)
Returns the rightmost len characters from the string str, or NULL if any argument is NULL.
```
mysql> SELECT RIGHT('foobarbar', 4);
        -> 'rbar'
```
This function is multibyte safe.
RPAD(str,len,padstr)
Returns the string str, right-padded with the string padstr to a length of len characters. If str is longer than len, the return value is shortened to len characters.
```
mysql> SELECT RPAD('hi',5,'?');
        -> 'hi???'
mysql> SELECT RPAD('hi',1,'?');
        -> 'h'
```
This function is multibyte safe.
RTRIM(str)
Returns the string str with trailing space characters removed.
```
mysql> SELECT RTRIM('barbar   ');
        -> 'barbar'
```
This function is multibyte safe.
SOUNDEX(str)
Returns a soundex string from str. Two strings that sound almost the same should have identical soundex strings. A standard soundex string is four characters long, but the SOUNDEX() function returns an arbitrarily long string. You can use SUBSTRING() on the result to get a standard soundex string. All nonalphabetic characters in str are ignored. All international alphabetic characters outside the A-Z range are treated as vowels.

Important

When using SOUNDEX(), you should be aware of the following limitations:
- This function, as currently implemented, is intended to work well with strings that are in the English language only. Strings in other languages may not produce reliable results.
- This function is not guaranteed to provide consistent results with strings that use multibyte character sets, including utf-8. See Bug #22638 for more information.
```
mysql> SELECT SOUNDEX('Hello');
        -> 'H400'
mysql> SELECT SOUNDEX('Quadratically');
        -> 'Q36324'
```
Note

This function implements the original Soundex algorithm, not the more popular enhanced version (also described by D. Knuth). The difference is that original version discards vowels first and duplicates second, whereas the enhanced version discards duplicates first and vowels second.
expr1 SOUNDS LIKE expr2
This is the same as SOUNDEX(expr1) = SOUNDEX(expr2).
SPACE(N)
Returns a string consisting of N space characters.
```
mysql> SELECT SPACE(6);
        -> '      '
```
SUBSTR(str,pos), SUBSTR(str FROM pos), SUBSTR(str,pos,len), SUBSTR(str FROM pos FOR len)
SUBSTR() is a synonym for SUBSTRING().
SUBSTRING(str,pos), SUBSTRING(str FROM pos), SUBSTRING(str,pos,len), SUBSTRING(str FROM pos FOR len)
The forms without a len argument return a substring from string str starting at position pos. The forms with a len argument return a substring len characters long from string str, starting at position pos. The forms that use FROM are standard SQL syntax. It is also possible to use a negative value for pos. In this case, the beginning of the substring is pos characters from the end of the string, rather than the beginning. A negative value may be used for pos in any of the forms of this function.
For all forms of SUBSTRING(), the position of the first character in the string from which the substring is to be extracted is reckoned as 1.
```
mysql> SELECT SUBSTRING('Quadratically',5);
        -> 'ratically'
mysql> SELECT SUBSTRING('foobarbar' FROM 4);
        -> 'barbar'
mysql> SELECT SUBSTRING('Quadratically',5,6);
        -> 'ratica'
mysql> SELECT SUBSTRING('Sakila', -3);
        -> 'ila'
mysql> SELECT SUBSTRING('Sakila', -5, 3);
        -> 'aki'
mysql> SELECT SUBSTRING('Sakila' FROM -4 FOR 2);
        -> 'ki'
```
This function is multibyte safe.
If len is less than 1, the result is the empty string.
SUBSTRING_INDEX(str,delim,count)
Returns the substring from string str before count occurrences of the delimiter delim. If count is positive, everything to the left of the final delimiter (counting from the left) is returned. If count is negative, everything to the right of the final delimiter (counting from the right) is returned. SUBSTRING_INDEX() performs a case-sensitive match when searching for delim.
```
mysql> SELECT SUBSTRING_INDEX('www.mysql.com', '.', 2);
        -> 'www.mysql'
mysql> SELECT SUBSTRING_INDEX('www.mysql.com', '.', -2);
        -> 'mysql.com'
```
This function is multibyte safe.
TO_BASE64(str)
Converts the string argument to base-64 encoded form and returns the result as a character string with the connection character set and collation. If the argument is not a string, it is converted to a string before conversion takes place. The result is NULL if the argument is NULL. Base-64 encoded strings can be decoded using the FROM_BASE64() function.
```
mysql> SELECT TO_BASE64('abc'), FROM_BASE64(TO_BASE64('abc'));
        -> 'JWJj', 'abc'
```
Different base-64 encoding schemes exist. These are the encoding and decoding rules used by TO_BASE64() and FROM_BASE64():
- The encoding for alphabet value 62 is '+'.
- The encoding for alphabet value 63 is '/'.
- Encoded output consists of groups of 4 printable characters. Each 3 bytes of the input data are encoded using 4 characters. If the last group is incomplete, it is padded with '=' characters to a length of 4.
- A newline is added after each 76 characters of encoded output to divide long output into multiple lines.
- Decoding recognizes and ignores newline, carriage return, tab, and space.
TRIM([{BOTH | LEADING | TRAILING} [remstr] FROM] str), TRIM([remstr FROM] str)
Returns the string str with all remstr prefixes or suffixes removed. If none of the specifiers BOTH, LEADING, or TRAILING is given, BOTH is assumed. remstr is optional and, if not specified, spaces are removed.
```
mysql> SELECT TRIM('  bar   ');
        -> 'bar'
mysql> SELECT TRIM(LEADING 'x' FROM 'xxxbarxxx');
        -> 'barxxx'
mysql> SELECT TRIM(BOTH 'x' FROM 'xxxbarxxx');
        -> 'bar'
mysql> SELECT TRIM(TRAILING 'xyz' FROM 'barxxyz');
        -> 'barx'
```
This function is multibyte safe.
UCASE(str)
UCASE() is a synonym for UPPER().
UCASE() used within views is rewritten as UPPER().
UNHEX(str)
For a string argument str, UNHEX(str) interprets each pair of characters in the argument as a hexadecimal number and converts it to the byte represented by the number. The return value is a binary string.
```
mysql> SELECT UNHEX('4D7953514C');
        -> 'MySQL'
mysql> SELECT X'4D7953514C';
        -> 'MySQL'
mysql> SELECT UNHEX(HEX('string'));
        -> 'string'
mysql> SELECT HEX(UNHEX('1267'));
        -> '1267'
```
The characters in the argument string must be legal hexadecimal digits: '0' .. '9', 'A' .. 'F', 'a' .. 'f'. If the argument contains any nonhexadecimal digits, the result is NULL:
```
mysql> SELECT UNHEX('GG');
+-------------+
| UNHEX('GG') |
+-------------+
| NULL        |
+-------------+
```
A NULL result can occur if the argument to UNHEX() is a BINARY column, because values are padded with 0x00 bytes when stored but those bytes are not stripped on retrieval. For example, '41' is stored into a CHAR(3) column as '41 ' and retrieved as '41' (with the trailing pad space stripped), so UNHEX() for the column value returns 'A'. By contrast '41' is stored into a BINARY(3) column as '41\0' and retrieved as '41\0' (with the trailing pad 0x00 byte not stripped). '\0' is not a legal hexadecimal digit, so UNHEX() for the column value returns NULL.
For a numeric argument N, the inverse of HEX(N) is not performed by UNHEX(). Use CONV(HEX(N),16,10) instead. See the description of HEX().
UPPER(str)
Returns the string str with all characters changed to uppercase according to the current character set mapping. The default is utf8mb4.
```
mysql> SELECT UPPER('Hej');
        -> 'HEJ'
```
See the description of LOWER() for information that also applies to UPPER(). This included information about how to perform lettercase conversion of binary strings (BINARY, VARBINARY, BLOB) for which these functions are ineffective, and information about case folding for Unicode character sets.
This function is multibyte safe.
UCASE() used within views is rewritten as UPPER().
WEIGHT_STRING(str [AS {CHAR|BINARY}(N)] [flags])
This function returns the weight string for the input string. The return value is a binary string that represents the comparison and sorting value of the string. It has these properties:
- If WEIGHT_STRING(str1) = WEIGHT_STRING(str2), then str1 = str2 (str1 and str2 are considered equal)
- If WEIGHT_STRING(str1) < WEIGHT_STRING(str2), then str1 < str2 (str1 sorts before str2)
WEIGHT_STRING() is a debugging function intended for internal use. Its behavior can change without notice between MySQL versions. It can be used for testing and debugging of collations, especially if you are adding a new collation. See Section 10.13, “Adding a Collation to a Character Set”.
This list briefly summarizes the arguments. More details are given in the discussion following the list.
- str: The input string expression.
- AS clause: Optional; cast the input string to a given type and length.
- flags: Optional; unused.
The input string, str, is a string expression. If the input is a nonbinary (character) string such as a CHAR, VARCHAR, or TEXT value, the return value contains the collation weights for the string. If the input is a binary (byte) string such as a BINARY, VARBINARY, or BLOB value, the return value is the same as the input (the weight for each byte in a binary string is the byte value). If the input is NULL, WEIGHT_STRING() returns NULL.
Examples:
```
mysql> SET @s = _utf8mb4 'AB' COLLATE utf8mb4_0900_ai_ci;
mysql> SELECT @s, HEX(@s), HEX(WEIGHT_STRING(@s));
+------+---------+------------------------+
| @s | HEX(@s) | HEX(WEIGHT_STRING(@s)) |
+------+---------+------------------------+
| AB | 4142 | 1C471C60 |
+------+---------+------------------------+
```
```
mysql> SET @s = _utf8mb4 'ab' COLLATE utf8mb4_0900_ai_ci;
mysql> SELECT @s, HEX(@s), HEX(WEIGHT_STRING(@s));
+------+---------+------------------------+
| @s | HEX(@s) | HEX(WEIGHT_STRING(@s)) |
+------+---------+------------------------+
| ab | 6162 | 1C471C60 |
+------+---------+------------------------+
```
```
mysql> SET @s = CAST('AB' AS BINARY);
mysql> SELECT @s, HEX(@s), HEX(WEIGHT_STRING(@s));
+------+---------+------------------------+
| @s | HEX(@s) | HEX(WEIGHT_STRING(@s)) |
+------+---------+------------------------+
| AB | 4142 | 4142 |
+------+---------+------------------------+
```
```
mysql> SET @s = CAST('ab' AS BINARY);
mysql> SELECT @s, HEX(@s), HEX(WEIGHT_STRING(@s));
+------+---------+------------------------+
| @s | HEX(@s) | HEX(WEIGHT_STRING(@s)) |
+------+---------+------------------------+
| ab | 6162 | 6162 |
+------+---------+------------------------+
```
The preceding examples use HEX() to display the WEIGHT_STRING() result. Because the result is a binary value, HEX() can be especially useful when the result contains nonprinting values, to display it in printable form:
```
mysql> SET @s = CONVERT(X'C39F' USING utf8) COLLATE utf8_czech_ci;
mysql> SELECT HEX(WEIGHT_STRING(@s));
+------------------------+
| HEX(WEIGHT_STRING(@s)) |
+------------------------+
| 0FEA0FEA |
+------------------------+
```
For non-NULL return values, the data type of the value is VARBINARY if its length is within the maximum length for VARBINARY, otherwise the data type is BLOB.
The AS clause may be given to cast the input string to a nonbinary or binary string and to force it to a given length:
- AS CHAR(N) casts the string to a nonbinary string and pads it on the right with spaces to a length of N characters. N must be at least 1. If N is less than the length of the input string, the string is truncated to N characters. No warning occurs for truncation.
- AS BINARY(N) is similar but casts the string to a binary string, N is measured in bytes (not characters), and padding uses 0x00 bytes (not spaces).
```
mysql> SET NAMES 'latin1';
mysql> SELECT HEX(WEIGHT_STRING('ab' AS CHAR(4)));
+-------------------------------------+
| HEX(WEIGHT_STRING('ab' AS CHAR(4))) |
+-------------------------------------+
| 41422020 |
+-------------------------------------+
mysql> SET NAMES 'utf8';
mysql> SELECT HEX(WEIGHT_STRING('ab' AS CHAR(4)));
+-------------------------------------+
| HEX(WEIGHT_STRING('ab' AS CHAR(4))) |
+-------------------------------------+
| 0041004200200020 |
+-------------------------------------+
```
```
mysql> SELECT HEX(WEIGHT_STRING('ab' AS BINARY(4)));
+---------------------------------------+
| HEX(WEIGHT_STRING('ab' AS BINARY(4))) |
+---------------------------------------+
| 61620000 |
+---------------------------------------+
```
The flags clause currently is unused.

12.5.1 String Comparison Functions

Table 12.8 String Comparison Operators

Name	Description
`LIKE`	Simple pattern matching
`NOT LIKE`	Negation of simple pattern matching
`STRCMP()`	Compare two strings

If a string function is given a binary string as an argument, the resulting string is also a binary string. A number converted to a string is treated as a binary string. This affects only comparisons.

Normally, if any expression in a string comparison is case sensitive, the comparison is performed in case-sensitive fashion.

expr LIKE pat [ESCAPE 'escape_char']
Pattern matching using an SQL pattern. Returns 1 (TRUE) or 0 (FALSE). If either expr or pat is NULL, the result is NULL.
The pattern need not be a literal string. For example, it can be specified as a string expression or table column.
Per the SQL standard, LIKE performs matching on a per-character basis, thus it can produce results different from the = comparison operator:
```
mysql> SELECT 'ä' LIKE 'ae' COLLATE latin1_german2_ci;
+-----------------------------------------+
| 'ä' LIKE 'ae' COLLATE latin1_german2_ci |
+-----------------------------------------+
|                                       0 |
+-----------------------------------------+
mysql> SELECT 'ä' = 'ae' COLLATE latin1_german2_ci;
+--------------------------------------+
| 'ä' = 'ae' COLLATE latin1_german2_ci |
+--------------------------------------+
|                                    1 |
+--------------------------------------+
```
In particular, trailing spaces are significant, which is not true for CHAR or VARCHAR comparisons performed with the = operator:
```
mysql> SELECT 'a' = 'a ', 'a' LIKE 'a ';
+------------+---------------+
| 'a' = 'a ' | 'a' LIKE 'a ' |
+------------+---------------+
|          1 |             0 |
+------------+---------------+
1 row in set (0.00 sec)
```
With LIKE you can use the following two wildcard characters in the pattern:
- % matches any number of characters, even zero characters.
- _ matches exactly one character.
```
mysql> SELECT 'David!' LIKE 'David_';
        -> 1
mysql> SELECT 'David!' LIKE '%D%v%';
        -> 1
```
To test for literal instances of a wildcard character, precede it by the escape character. If you do not specify the ESCAPE character, \ is assumed.
- \% matches one % character.
- \_ matches one _ character.
```
mysql> SELECT 'David!' LIKE 'David\_';
        -> 0
mysql> SELECT 'David_' LIKE 'David\_';
        -> 1
```
To specify a different escape character, use the ESCAPE clause:
```
mysql> SELECT 'David_' LIKE 'David|_' ESCAPE '|';
        -> 1
```
The escape sequence should be empty or one character long. The expression must evaluate as a constant at execution time. If the NO_BACKSLASH_ESCAPES SQL mode is enabled, the sequence cannot be empty.
The following two statements illustrate that string comparisons are not case-sensitive unless one of the operands is case-sensitive (uses a case-sensitive collation or is a binary string):
```
mysql> SELECT 'abc' LIKE 'ABC';
        -> 1
mysql> SELECT 'abc' LIKE _utf8mb4 'ABC' COLLATE utf8mb4_0900_as_cs;
        -> 0
mysql> SELECT 'abc' LIKE _utf8mb4 'ABC' COLLATE utf8mb4_bin;
        -> 0
mysql> SELECT 'abc' LIKE BINARY 'ABC';
        -> 0
```
As an extension to standard SQL, MySQL permits LIKE on numeric expressions.
```
mysql> SELECT 10 LIKE '1%';
        -> 1
```
Note

Because MySQL uses C escape syntax in strings (for example, \n to represent a newline character), you must double any \ that you use in LIKE strings. For example, to search for \n, specify it as \\n. To search for \, specify it as \\\\; this is because the backslashes are stripped once by the parser and again when the pattern match is made, leaving a single backslash to be matched against.
Exception: At the end of the pattern string, backslash can be specified as \\. At the end of the string, backslash stands for itself because there is nothing following to escape. Suppose that a table contains the following values:
```
mysql> SELECT filename FROM t1;
+--------------+
| filename     |
+--------------+
| C:           |
| C:\          |
| C:\Programs  |
| C:\Programs\ |
+--------------+
```
To test for values that end with backslash, you can match the values using either of the following patterns:
```
mysql> SELECT filename, filename LIKE '%\\' FROM t1;
+--------------+---------------------+
| filename     | filename LIKE '%\\' |
+--------------+---------------------+
| C:           |                   0 |
| C:\          |                   1 |
| C:\Programs  |                   0 |
| C:\Programs\ |                   1 |
+--------------+---------------------+

mysql> SELECT filename, filename LIKE '%\\\\' FROM t1;
+--------------+-----------------------+
| filename     | filename LIKE '%\\\\' |
+--------------+-----------------------+
| C:           |                     0 |
| C:\          |                     1 |
| C:\Programs  |                     0 |
| C:\Programs\ |                     1 |
+--------------+-----------------------+
```
expr NOT LIKE pat [ESCAPE 'escape_char']
This is the same as NOT (expr LIKE pat [ESCAPE 'escape_char']).
Note

Aggregate queries involving NOT LIKE comparisons with columns containing NULL may yield unexpected results. For example, consider the following table and data:
```
CREATE TABLE foo (bar VARCHAR(10));

INSERT INTO foo VALUES (NULL), (NULL);
```
The query SELECT COUNT(*) FROM foo WHERE bar LIKE '%baz%'; returns 0. You might assume that SELECT COUNT(*) FROM foo WHERE bar NOT LIKE '%baz%'; would return 2. However, this is not the case: The second query returns 0. This is because NULL NOT LIKE expr always returns NULL, regardless of the value of expr. The same is true for aggregate queries involving NULL and comparisons using NOT RLIKE or NOT REGEXP. In such cases, you must test explicitly for NOT NULL using OR (and not AND), as shown here:
```
SELECT COUNT(*) FROM foo WHERE bar NOT LIKE '%baz%' OR bar IS NULL;
```

STRCMP(expr1,expr2)

STRCMP() returns 0 if the strings are the same, -1 if the first argument is smaller than the second according to the current sort order, and 1 otherwise.

mysql> SELECT STRCMP('text', 'text2');
        -> -1
mysql> SELECT STRCMP('text2', 'text');
        -> 1
mysql> SELECT STRCMP('text', 'text');
        -> 0

STRCMP() performs the comparison using the collation of the arguments.

mysql> SET @s1 = _utf8mb4 'x' COLLATE utf8mb4_0900_ai_ci;
mysql> SET @s2 = _utf8mb4 'X' COLLATE utf8mb4_0900_ai_ci;
mysql> SET @s3 = _utf8mb4 'x' COLLATE utf8mb4_0900_as_cs;
mysql> SET @s4 = _utf8mb4 'X' COLLATE utf8mb4_0900_as_cs;
mysql> SELECT STRCMP(@s1, @s2), STRCMP(@s3, @s4);
+------------------+------------------+
| STRCMP(@s1, @s2) | STRCMP(@s3, @s4) |
+------------------+------------------+
|                0 |               -1 |
+------------------+------------------+

If the collations are incompatible, one of the arguments must be converted to be compatible with the other. See Section 10.8.4, “Collation Coercibility in Expressions”.

mysql> SET @s1 = _utf8mb4 'x' COLLATE utf8mb4_0900_ai_ci;
mysql> SET @s2 = _utf8mb4 'X' COLLATE utf8mb4_0900_ai_ci;
mysql> SET @s3 = _utf8mb4 'x' COLLATE utf8mb4_0900_as_cs;
mysql> SET @s4 = _utf8mb4 'X' COLLATE utf8mb4_0900_as_cs;
-->
mysql> SELECT STRCMP(@s1, @s3);
ERROR 1267 (HY000): Illegal mix of collations (utf8mb4_0900_ai_ci,IMPLICIT)
and (utf8mb4_0900_as_cs,IMPLICIT) for operation 'strcmp'
mysql> SELECT STRCMP(@s1, @s3 COLLATE utf8mb4_0900_ai_ci);
+---------------------------------------------+
| STRCMP(@s1, @s3 COLLATE utf8mb4_0900_ai_ci) |
+---------------------------------------------+
|                                           0 |
+---------------------------------------------+

12.5.2 Regular Expressions

Table 12.9 Regular Expression Functions and Operators

Name	Description
`NOT REGEXP`	Negation of REGEXP
`REGEXP`	Whether string matches regular expression
`REGEXP_INSTR()`	Starting index of substring matching regular expression
`REGEXP_LIKE()`	Whether string matches regular expression
`REGEXP_REPLACE()`	Replace substrings matching regular expression
`REGEXP_SUBSTR()`	Return substring matching regular expression
`RLIKE`	Whether string matches regular expression

A regular expression is a powerful way of specifying a pattern for a complex search. This section discusses the functions and operators available for regular expression matching and illustrates, with examples, some of the special characters and constructs that can be used for regular expression operations. See also Section 3.3.4.7, “Pattern Matching”.

MySQL implements regular expression support using International Components for Unicode (ICU), which provides full Unicode support and is multibyte safe. (Prior to MySQL 8.0.4, MySQL used Henry Spencer's implementation of regular expressions, which operates in byte-wise fashion and is not multibyte safe. For information about ways in which applications that use regular expressions may be affected by the implementation change, see Regular Expression Compatibility Considerations.)

Regular Expression Functions and Operators

expr NOT REGEXP pat, expr NOT RLIKE pat
This is the same as NOT (expr REGEXP pat).

expr REGEXP pat, expr RLIKE pat

Returns 1 if the string expr matches the regular expression specified by the pattern pat, 0 otherwise. If expr or pat is NULL, the return value is NULL.

REGEXP and RLIKE are synonyms for REGEXP_LIKE().

For additional information about how matching occurs, see the description for REGEXP_LIKE().

mysql> SELECT 'Michael!' REGEXP '.*';
+------------------------+
| 'Michael!' REGEXP '.*' |
+------------------------+
|                      1 |
+------------------------+
mysql> SELECT 'new*\n*line' REGEXP 'new\\*.\\*line';
+---------------------------------------+
| 'new*\n*line' REGEXP 'new\\*.\\*line' |
+---------------------------------------+
|                                     0 |
+---------------------------------------+
mysql> SELECT 'a' REGEXP '^[a-d]';
+---------------------+
| 'a' REGEXP '^[a-d]' |
+---------------------+
|                   1 |
+---------------------+
mysql> SELECT 'a' REGEXP 'A', 'a' REGEXP BINARY 'A';
+----------------+-----------------------+
| 'a' REGEXP 'A' | 'a' REGEXP BINARY 'A' |
+----------------+-----------------------+
|              1 |                     0 |
+----------------+-----------------------+

REGEXP_INSTR(expr, pat[, pos[, occurrence[, return_option[, match_type]]]])
Returns the starting index of the substring of the string expr that matches the regular expression specified by the pattern pat, 0 if there is no match. If expr or pat is NULL, the return value is NULL. Character indexes begin at 1.
REGEXP_INSTR() takes these optional arguments:
- pos: The position in expr at which to start the search. If omitted, the default is 1.
- occurrence: Which occurrence of a match to search for. If omitted, the default is 1.
- return_option: Which type of position to return. If this value is 0, REGEXP_INSTR() returns the position of the matched substring's first character. If this value is 1, REGEXP_INSTR() returns the position following the matched substring. If omitted, the default is 0.
- match_type: A string that specifies how to perform matching. The meaning is as described for REGEXP_LIKE().
For additional information about how matching occurs, see the description for REGEXP_LIKE().
```
mysql> SELECT REGEXP_INSTR('dog cat dog', 'dog');
+------------------------------------+
| REGEXP_INSTR('dog cat dog', 'dog') |
+------------------------------------+
|                                  1 |
+------------------------------------+
mysql> SELECT REGEXP_INSTR('dog cat dog', 'dog', 2);
+---------------------------------------+
| REGEXP_INSTR('dog cat dog', 'dog', 2) |
+---------------------------------------+
|                                     9 |
+---------------------------------------+
mysql> SELECT REGEXP_INSTR('aa aaa aaaa', 'a{2}');
+-------------------------------------+
| REGEXP_INSTR('aa aaa aaaa', 'a{2}') |
+-------------------------------------+
|                                   1 |
+-------------------------------------+
mysql> SELECT REGEXP_INSTR('aa aaa aaaa', 'a{4}');
+-------------------------------------+
| REGEXP_INSTR('aa aaa aaaa', 'a{4}') |
+-------------------------------------+
|                                   8 |
+-------------------------------------+
```
REGEXP_LIKE(expr, pat[, match_type])
Returns 1 if the string expr matches the regular expression specified by the pattern pat, 0 otherwise. If expr or pat is NULL, the return value is NULL.
The pattern can be an extended regular expression, the syntax for which is discussed in Regular Expression Syntax. The pattern need not be a literal string. For example, it can be specified as a string expression or table column.
The optional match_type argument is a string that may contain any or all the following characters specifying how to perform matching:
- c: Case sensitive matching.
- i: Case insensitive matching.
- m: Multiple-line mode. Recognize line terminators within the string. The default behavior is to match line terminators only at the start and end of the string expression.
- n: The . character matches line terminators. The default is for . matching to stop at the end of a line.
- u: Unix-only line endings. Only the newline character is recognized as a line ending by the ., ^, and $ match operators.
If characters specifying contradictory options are specified within match_type, the rightmost one takes precedence.
By default, regular expression operations use the character set and collation of the expr and pat arguments when deciding the type of a character and performing the comparison. If the arguments have different character sets or collations, coercibility rules apply as described in Section 10.8.4, “Collation Coercibility in Expressions”. Arguments may be specified with explicit collation indicators to change comparison behavior.
```
mysql> SELECT REGEXP_LIKE('CamelCase', 'CAMELCASE');
+---------------------------------------+
| REGEXP_LIKE('CamelCase', 'CAMELCASE') |
+---------------------------------------+
|                                     1 |
+---------------------------------------+
mysql> SELECT REGEXP_LIKE('CamelCase', 'CAMELCASE' COLLATE utf8mb4_0900_as_cs);
+------------------------------------------------------------------+
| REGEXP_LIKE('CamelCase', 'CAMELCASE' COLLATE utf8mb4_0900_as_cs) |
+------------------------------------------------------------------+
|                                                                0 |
+------------------------------------------------------------------+
```
match_type may be specified with the c or i characters to override the default case sensitivity. Exception: If either argument is a binary string, the arguments are handled in case-sensitive fashion as binary strings, even if match_type contains the i character.

Note

Because MySQL uses the C escape syntax in strings (for example, \n to represent the newline character), you must double any \ that you use in your expr and pat arguments.
```
mysql> SELECT REGEXP_LIKE('Michael!', '.*');
+-------------------------------+
| REGEXP_LIKE('Michael!', '.*') |
+-------------------------------+
|                             1 |
+-------------------------------+
mysql> SELECT REGEXP_LIKE('new*\n*line', 'new\\*.\\*line');
+----------------------------------------------+
| REGEXP_LIKE('new*\n*line', 'new\\*.\\*line') |
+----------------------------------------------+
|                                            0 |
+----------------------------------------------+
mysql> SELECT REGEXP_LIKE('a', '^[a-d]');
+----------------------------+
| REGEXP_LIKE('a', '^[a-d]') |
+----------------------------+
|                          1 |
+----------------------------+
mysql> SELECT REGEXP_LIKE('a', 'A'), REGEXP_LIKE('a', BINARY 'A');
+-----------------------+------------------------------+
| REGEXP_LIKE('a', 'A') | REGEXP_LIKE('a', BINARY 'A') |
+-----------------------+------------------------------+
|                     1 |                            0 |
+-----------------------+------------------------------+
```
```
mysql> SELECT REGEXP_LIKE('abc', 'ABC');
+---------------------------+
| REGEXP_LIKE('abc', 'ABC') |
+---------------------------+
|                         1 |
+---------------------------+
mysql> SELECT REGEXP_LIKE('abc', 'ABC', 'c');
+--------------------------------+
| REGEXP_LIKE('abc', 'ABC', 'c') |
+--------------------------------+
|                              0 |
+--------------------------------+
```
REGEXP_REPLACE(expr, pat, repl[, pos[, occurrence[, match_type]]])
Replaces occurrences in the string expr that match the regular expression specified by the pattern pat with the replacement string repl, and returns the resulting string. If expr, pat, or repl is NULL, the return value is NULL.
REGEXP_REPLACE() takes these optional arguments:
- pos: The position in expr at which to start the search. If omitted, the default is 1.
- occurrence: Which occurrence of a match to replace. If omitted, the default is 0 (which means “replace all occurrences”).
- match_type: A string that specifies how to perform matching. The meaning is as described for REGEXP_LIKE().
For additional information about how matching occurs, see the description for REGEXP_LIKE().
```
mysql> SELECT REGEXP_REPLACE('a b c', 'b', 'X');
+-----------------------------------+
| REGEXP_REPLACE('a b c', 'b', 'X') |
+-----------------------------------+
| a X c                             |
+-----------------------------------+
mysql> SELECT REGEXP_REPLACE('abc def ghi', '[a-z]+', 'X', 1, 3);
+----------------------------------------------------+
| REGEXP_REPLACE('abc def ghi', '[a-z]+', 'X', 1, 3) |
+----------------------------------------------------+
| abc def X                                          |
+----------------------------------------------------+
```
REGEXP_SUBSTR(expr, pat[, pos[, occurrence[, match_type]]])
Returns the substring of the string expr that matches the regular expression specified by the pattern pat, NULL if there is no match. If expr or pat is NULL, the return value is NULL.
REGEXP_SUBSTR() takes these optional arguments:
- pos: The position in expr at which to start the search. If omitted, the default is 1.
- occurrence: Which occurrence of a match to search for. If omitted, the default is 1.
- match_type: A string that specifies how to perform matching. The meaning is as described for REGEXP_LIKE().
For additional information about how matching occurs, see the description for REGEXP_LIKE().
```
mysql> SELECT REGEXP_SUBSTR('abc def ghi', '[a-z]+');
+----------------------------------------+
| REGEXP_SUBSTR('abc def ghi', '[a-z]+') |
+----------------------------------------+
| abc                                    |
+----------------------------------------+
mysql> SELECT REGEXP_SUBSTR('abc def ghi', '[a-z]+', 1, 3);
+----------------------------------------------+
| REGEXP_SUBSTR('abc def ghi', '[a-z]+', 1, 3) |
+----------------------------------------------+
| ghi                                          |
+----------------------------------------------+
```

Regular Expression Syntax

A regular expression describes a set of strings. The simplest regular expression is one that has no special characters in it. For example, the regular expression hello matches hello and nothing else.

Nontrivial regular expressions use certain special constructs so that they can match more than one string. For example, the regular expression hello|world contains the | alternation operator and matches either the hello or world.

As a more complex example, the regular expression B[an]*s matches any of the strings Bananas, Baaaaas, Bs, and any other string starting with a B, ending with an s, and containing any number of a or n characters in between.

The following list covers some of the basic special characters and constructs that can be used in regular expressions. For information about the full regular expression syntax supported by the ICU library used to implement regular expression support, visit the International Components for Unicode website.

^

Match the beginning of a string.

mysql> SELECT REGEXP_LIKE('fo\nfo', '^fo$');                   -> 0
mysql> SELECT REGEXP_LIKE('fofo', '^fo');                      -> 1

$

Match the end of a string.

mysql> SELECT REGEXP_LIKE('fo\no', '^fo\no$');                 -> 1
mysql> SELECT REGEXP_LIKE('fo\no', '^fo$');                    -> 0

.

Match any character (including carriage return and newline, although to match these in the middle of a string, the m (multiple line) match-control character or the (?m) within-pattern modifier must be given).

mysql> SELECT REGEXP_LIKE('fofo', '^f.*$');                    -> 1
mysql> SELECT REGEXP_LIKE('fo\r\nfo', '^f.*$');                -> 0
mysql> SELECT REGEXP_LIKE('fo\r\nfo', '^f.*$', 'm');           -> 1
mysql> SELECT REGEXP_LIKE('fo\r\nfo', '(?m)^f.*$');           -> 1

a*

Match any sequence of zero or more a characters.

mysql> SELECT REGEXP_LIKE('Ban', '^Ba*n');                     -> 1
mysql> SELECT REGEXP_LIKE('Baaan', '^Ba*n');                   -> 1
mysql> SELECT REGEXP_LIKE('Bn', '^Ba*n');                      -> 1

a+

Match any sequence of one or more a characters.

mysql> SELECT REGEXP_LIKE('Ban', '^Ba+n');                     -> 1
mysql> SELECT REGEXP_LIKE('Bn', '^Ba+n');                      -> 0

a?

Match either zero or one a character.

mysql> SELECT REGEXP_LIKE('Bn', '^Ba?n');                      -> 1
mysql> SELECT REGEXP_LIKE('Ban', '^Ba?n');                     -> 1
mysql> SELECT REGEXP_LIKE('Baan', '^Ba?n');                    -> 0

de|abc

Alternation; match either of the sequences de or abc.

mysql> SELECT REGEXP_LIKE('pi', 'pi|apa');                     -> 1
mysql> SELECT REGEXP_LIKE('axe', 'pi|apa');                    -> 0
mysql> SELECT REGEXP_LIKE('apa', 'pi|apa');                    -> 1
mysql> SELECT REGEXP_LIKE('apa', '^(pi|apa)$');                -> 1
mysql> SELECT REGEXP_LIKE('pi', '^(pi|apa)$');                 -> 1
mysql> SELECT REGEXP_LIKE('pix', '^(pi|apa)$');                -> 0

(abc)*

Match zero or more instances of the sequence abc.

mysql> SELECT REGEXP_LIKE('pi', '^(pi)*$');                    -> 1
mysql> SELECT REGEXP_LIKE('pip', '^(pi)*$');                   -> 0
mysql> SELECT REGEXP_LIKE('pipi', '^(pi)*$');                  -> 1

{1}, {2,3}
Repetition; {n} and {m,n} notation provide a more general way of writing regular expressions that match many occurrences of the previous atom (or “piece”) of the pattern. m and n are integers.
- a*
  Can be written as a{0,}.
- a+
  Can be written as a{1,}.
- a?
  Can be written as a{0,1}.
To be more precise, a{n} matches exactly n instances of a. a{n,} matches n or more instances of a. a{m,n} matches m through n instances of a, inclusive. If both m and n are given, m must be less than or equal to n.
```
mysql> SELECT REGEXP_LIKE('abcde', 'a[bcd]{2}e');              -> 0
mysql> SELECT REGEXP_LIKE('abcde', 'a[bcd]{3}e');              -> 1
mysql> SELECT REGEXP_LIKE('abcde', 'a[bcd]{1,10}e');           -> 1
```
[a-dX], [^a-dX]
Matches any character that is (or is not, if ^ is used) either a, b, c, d or X. A - character between two other characters forms a range that matches all characters from the first character to the second. For example, [0-9] matches any decimal digit. To include a literal ] character, it must immediately follow the opening bracket [. To include a literal - character, it must be written first or last. Any character that does not have a defined special meaning inside a [] pair matches only itself.
```
mysql> SELECT REGEXP_LIKE('aXbc', '[a-dXYZ]');                 -> 1
mysql> SELECT REGEXP_LIKE('aXbc', '^[a-dXYZ]$');               -> 0
mysql> SELECT REGEXP_LIKE('aXbc', '^[a-dXYZ]+$');              -> 1
mysql> SELECT REGEXP_LIKE('aXbc', '^[^a-dXYZ]+$');             -> 0
mysql> SELECT REGEXP_LIKE('gheis', '^[^a-dXYZ]+$');            -> 1
mysql> SELECT REGEXP_LIKE('gheisa', '^[^a-dXYZ]+$');           -> 0
```
[=character_class=]
Within a bracket expression (written using [ and ]), [=character_class=] represents an equivalence class. It matches all characters with the same collation value, including itself. For example, if o and (+) are the members of an equivalence class, [[=o=]], [[=(+)=]], and [o(+)] are all synonymous. An equivalence class may not be used as an endpoint of a range.

[:character_class:]

Within a bracket expression (written using [ and ]), [:character_class:] represents a character class that matches all characters belonging to that class. The following table lists the standard class names. These names stand for the character classes defined in the ctype(3) manual page. A particular locale may provide other class names. A character class may not be used as an endpoint of a range.

Character Class Name	Meaning
`alnum`	Alphanumeric characters
`alpha`	Alphabetic characters
`blank`	Whitespace characters
`cntrl`	Control characters
`digit`	Digit characters
`graph`	Graphic characters
`lower`	Lowercase alphabetic characters
`print`	Graphic or space characters
`punct`	Punctuation characters
`space`	Space, tab, newline, and carriage return
`upper`	Uppercase alphabetic characters
`xdigit`	Hexadecimal digit characters

mysql> SELECT REGEXP_LIKE('justalnums', '[[:alnum:]]+');       -> 1
mysql> SELECT REGEXP_LIKE('!!', '[[:alnum:]]+');               -> 0

To use a literal instance of a special character in a regular expression, precede it by two backslash (\) characters. The MySQL parser interprets one of the backslashes, and the regular expression library interprets the other. For example, to match the string 1+2 that contains the special + character, only the last of the following regular expressions is the correct one:

mysql> SELECT REGEXP_LIKE('1+2', '1+2');                       -> 0
mysql> SELECT REGEXP_LIKE('1+2', '1\+2');                      -> 0
mysql> SELECT REGEXP_LIKE('1+2', '1\\+2');                     -> 1

Regular Expression Resource Control

REGEXP_LIKE() and similar functions use resources that can be controlled by setting system variables:

The match engine uses memory for its internal stack. To control the maximum available memory for the stack in bytes, set the regexp_stack_limit system variable.
The match engine operates in steps. To control the maximum number of steps performed by the engine (and thus indirectly the execution time), set the regexp_time_limit system variable. Because this limit is expressed as number of steps, it affects execution time only indirectly. Typically, it is on the order of milliseconds.

Regular Expression Compatibility Considerations

Prior to MySQL 8.0.4, MySQL used the Henry Spencer regular expression library to support regular expression operations, rather than International Components for Unicode (ICU). The following discussion describes differences between the Spencer and ICU libraries that may affect applications:

With the Spencer library, the REGEXP and RLIKE operators work in byte-wise fashion, so they are not multibyte safe and may produce unexpected results with multibyte character sets. In addition, these operators compare characters by their byte values and accented characters may not compare as equal even if a given collation treats them as equal.
ICU has full Unicode support and is multibyte safe. Its regular expression functions treat all strings as as UTF-16. You should keep in mind that positional indexes are based on 16-bit chunks and not on code points. This means that, when passed to such functions, characters using more than one chunk may produce unanticipated results, such as those shown here:
```
mysql> SELECT REGEXP_INSTR('🍣🍣b', 'b');
+--------------------------+
| REGEXP_INSTR('??b', 'b') |
+--------------------------+
|                        5 |
+--------------------------+
1 row in set (0.00 sec)

mysql> SELECT REGEXP_INSTR('🍣🍣bxxx', 'b', 4);
+--------------------------------+
| REGEXP_INSTR('??bxxx', 'b', 4) |
+--------------------------------+
|                              5 |
+--------------------------------+
1 row in set (0.00 sec)
```
Characters within the Unicode Basic Multilingual Plane, which includes characters used by most modern languages, are safe in this regard:
```
mysql> SELECT REGEXP_INSTR('бжb', 'b');
+----------------------------+
| REGEXP_INSTR('бжb', 'b')   |
+----------------------------+
|                          3 |
+----------------------------+
1 row in set (0.00 sec)

mysql> SELECT REGEXP_INSTR('עבb', 'b');
+----------------------------+
| REGEXP_INSTR('עבb', 'b')   |
+----------------------------+
|                          3 |
+----------------------------+
1 row in set (0.00 sec)

mysql> SELECT REGEXP_INSTR('µå周çб', '周');
+------------------------------------+
| REGEXP_INSTR('µå周çб', '周')       |
+------------------------------------+
|                                  3 |
+------------------------------------+
1 row in set (0.00 sec)
```
Emoji, such as the “sushi” character 🍣 (U+1F363) used in the first two examples, are not included in the Basic Multilingual Plane, but rather in Unicode's Supplementary Multilingual Plane. Another issue can arise with emoji and other 4-byte characters when REGEXP_SUBSTR() or a similar function begins searching in the middle of a character. Each of the two statements in the following example starts from the second 2-byte position in the first argument. The first statement works on a string consisting solely of 2-byte (BMP) characters. The second statement contains 4-byte characters which are incorrectly interpreted in the result because the first two bytes are stripped off and so the remainder of the character data is misaligned.
```
mysql> SELECT REGEXP_SUBSTR('周周周周', '.*', 2);
+----------------------------------------+
| REGEXP_SUBSTR('周周周周', '.*', 2)     |
+----------------------------------------+
| 周周周                                 |
+----------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT REGEXP_SUBSTR('🍣🍣🍣🍣', '.*', 2);
+--------------------------------+
| REGEXP_SUBSTR('????', '.*', 2) |
+--------------------------------+
| ?㳟揘㳟揘㳟揘                  |
+--------------------------------+
1 row in set (0.00 sec)
```
For the . operator, the Spencer library matches line-terminator characters (carriage return, newline) anywhere in string expressions, including in the middle. To match line terminator characters in the middle of strings with ICU, specify the m match-control character.
The Spencer library supports word-beginning and word-end boundary markers ([[:<:]] and [[:>:]] notation). ICU does not.
The Spencer library supports collating element bracket expressions ([.characters.] notation). ICU does not.
For repetition counts ({n} and {m,n} notation), the Spencer library has a maximum of 255. ICU has no such limit, although the maximum number of match engine steps can be limited by setting the regexp_time_limit system variable.

ICU interprets parentheses as metacharacters. To specify a literal open parenthesis ( in a regular expression, it must be escaped:

mysql> SELECT REGEXP_LIKE('(', '(');
ERROR 3692 (HY000): Mismatched parenthesis in regular expression.
mysql> SELECT REGEXP_LIKE('(', '\\(');
+-------------------------+
| REGEXP_LIKE('(', '\\(') |
+-------------------------+
|                       1 |
+-------------------------+

12.5.3 Character Set and Collation of Function Results

MySQL has many operators and functions that return a string. This section answers the question: What is the character set and collation of such a string?

For simple functions that take string input and return a string result as output, the output's character set and collation are the same as those of the principal input value. For example, UPPER(X) returns a string with the same character string and collation as X. The same applies for INSTR(), LCASE(), LOWER(), LTRIM(), MID(), REPEAT(), REPLACE(), REVERSE(), RIGHT(), RPAD(), RTRIM(), SOUNDEX(), SUBSTRING(), TRIM(), UCASE(), and UPPER().

Note

The REPLACE() function, unlike all other functions, always ignores the collation of the string input and performs a case-sensitive comparison.

If a string input or function result is a binary string, the string has the binary character set and collation. This can be checked by using the CHARSET() and COLLATION() functions, both of which return binary for a binary string argument:

mysql> SELECT CHARSET(BINARY 'a'), COLLATION(BINARY 'a');
+---------------------+-----------------------+
| CHARSET(BINARY 'a') | COLLATION(BINARY 'a') |
+---------------------+-----------------------+
| binary              | binary                |
+---------------------+-----------------------+

For operations that combine multiple string inputs and return a single string output, the “aggregation rules” of standard SQL apply for determining the collation of the result:

If an explicit COLLATE Y occurs, use Y.
If explicit COLLATE Y and COLLATE Z occur, raise an error.
Otherwise, if all collations are Y, use Y.
Otherwise, the result has no collation.

For example, with CASE ... WHEN a THEN b WHEN b THEN c COLLATE X END, the resulting collation is X. The same applies for UNION, ||, CONCAT(), ELT(), GREATEST(), IF(), and LEAST().

For operations that convert to character data, the character set and collation of the strings that result from the operations are defined by the character_set_connection and collation_connection system variables that determine the default connection character set and collation (see Section 10.4, “Connection Character Sets and Collations”). This applies only to BIN_TO_UUID(), CAST(), CONV(), FORMAT(), HEX(), and SPACE().

An exception to the preceding priniciple occurs for expressions for virtual generated columns. In such expressions, the table character set is used for BIN_TO_UUID(), CONV(), or HEX() results, regardless of connection character set.

If there is any question about the character set or collation of the result returned by a string function, use the CHARSET() or COLLATION() function to find out:

mysql> SELECT USER(), CHARSET(USER()), COLLATION(USER());
+----------------+-----------------+-------------------+
| USER()         | CHARSET(USER()) | COLLATION(USER()) |
+----------------+-----------------+-------------------+
| test@localhost | utf8            | utf8_general_ci   |
+----------------+-----------------+-------------------+
mysql> SELECT CHARSET(COMPRESS('abc')), COLLATION(COMPRESS('abc'));
+--------------------------+----------------------------+
| CHARSET(COMPRESS('abc')) | COLLATION(COMPRESS('abc')) |
+--------------------------+----------------------------+
| binary                   | binary                     |
+--------------------------+----------------------------+

12.6 Numeric Functions and Operators

12.6.1 Arithmetic Operators
12.6.2 Mathematical Functions

Table 12.10 Numeric Functions and Operators

Name	Description
`ABS()`	Return the absolute value
`ACOS()`	Return the arc cosine
`ASIN()`	Return the arc sine
`ATAN()`	Return the arc tangent
`ATAN2()`, `ATAN()`	Return the arc tangent of the two arguments
`CEIL()`	Return the smallest integer value not less than the argument
`CEILING()`	Return the smallest integer value not less than the argument
`CONV()`	Convert numbers between different number bases
`COS()`	Return the cosine
`COT()`	Return the cotangent
`CRC32()`	Compute a cyclic redundancy check value
`DEGREES()`	Convert radians to degrees
`DIV`	Integer division
`/`	Division operator
`EXP()`	Raise to the power of
`FLOOR()`	Return the largest integer value not greater than the argument
`LN()`	Return the natural logarithm of the argument
`LOG()`	Return the natural logarithm of the first argument
`LOG10()`	Return the base-10 logarithm of the argument
`LOG2()`	Return the base-2 logarithm of the argument
`-`	Minus operator
`MOD()`	Return the remainder
`%`, `MOD`	Modulo operator
`PI()`	Return the value of pi
`+`	Addition operator
`POW()`	Return the argument raised to the specified power
`POWER()`	Return the argument raised to the specified power
`RADIANS()`	Return argument converted to radians
`RAND()`	Return a random floating-point value
`ROUND()`	Round the argument
`SIGN()`	Return the sign of the argument
`SIN()`	Return the sine of the argument
`SQRT()`	Return the square root of the argument
`TAN()`	Return the tangent of the argument
`*`	Multiplication operator
`TRUNCATE()`	Truncate to specified number of decimal places
`-`	Change the sign of the argument

12.6.1 Arithmetic Operators

Table 12.11 Arithmetic Operators

Name	Description
`DIV`	Integer division
`/`	Division operator
`-`	Minus operator
`%`, `MOD`	Modulo operator
`+`	Addition operator
`*`	Multiplication operator
`-`	Change the sign of the argument

The usual arithmetic operators are available. The result is determined according to the following rules:

In the case of -, +, and *, the result is calculated with BIGINT (64-bit) precision if both operands are integers.
If both operands are integers and any of them are unsigned, the result is an unsigned integer. For subtraction, if the NO_UNSIGNED_SUBTRACTION SQL mode is enabled, the result is signed even if any operand is unsigned.
If any of the operands of a +, -, /, *, % is a real or string value, the precision of the result is the precision of the operand with the maximum precision.
In division performed with /, the scale of the result when using two exact-value operands is the scale of the first operand plus the value of the div_precision_increment system variable (which is 4 by default). For example, the result of the expression 5.05 / 0.014 has a scale of six decimal places (360.714286).

These rules are applied for each operation, such that nested calculations imply the precision of each component. Hence, (14620 / 9432456) / (24250 / 9432456), resolves first to (0.0014) / (0.0026), with the final result having 8 decimal places (0.60288653).

Because of these rules and the way they are applied, care should be taken to ensure that components and subcomponents of a calculation use the appropriate level of precision. See Section 12.10, “Cast Functions and Operators”.

For information about handling of overflow in numeric expression evaluation, see Section 11.2.6, “Out-of-Range and Overflow Handling”.

Arithmetic operators apply to numbers. For other types of values, alternative operations may be available. For example, to add date values, use DATE_ADD(); see Section 12.7, “Date and Time Functions”.

+
Addition:
```
mysql> SELECT 3+5;
        -> 8
```
-
Subtraction:
```
mysql> SELECT 3-5;
        -> -2
```
-
Unary minus. This operator changes the sign of the operand.
```
mysql> SELECT - 2;
        -> -2
```
Note

If this operator is used with a BIGINT, the return value is also a BIGINT. This means that you should avoid using - on integers that may have the value of −2⁶³.

*

Multiplication:

mysql> SELECT 3*5;
        -> 15
mysql> SELECT 18014398509481984*18014398509481984.0;
        -> 324518553658426726783156020576256.0
mysql> SELECT 18014398509481984*18014398509481984;
        -> out-of-range error

The last expression produces an error because the result of the integer multiplication exceeds the 64-bit range of BIGINT calculations. (See Section 11.2, “Numeric Types”.)

/
Division:
```
mysql> SELECT 3/5;
        -> 0.60
```
Division by zero produces a NULL result:
```
mysql> SELECT 102/(1-1);
        -> NULL
```
A division is calculated with BIGINT arithmetic only if performed in a context where its result is converted to an integer.
DIV
Integer division. Discards from the division result any fractional part to the right of the decimal point.
If either operand has a noninteger type, the operands are converted to DECIMAL and divided using DECIMAL arithmetic before converting the result to BIGINT. If the result exceeds BIGINT range, an error occurs.
```
mysql> SELECT 5 DIV 2, -5 DIV 2, 5 DIV -2, -5 DIV -2;
        -> 2, -2, -2, 2
```
N % M, N MOD M
Modulo operation. Returns the remainder of N divided by M. For more information, see the description for the MOD() function in Section 12.6.2, “Mathematical Functions”.

12.6.2 Mathematical Functions

Table 12.12 Mathematical Functions

Name	Description
`ABS()`	Return the absolute value
`ACOS()`	Return the arc cosine
`ASIN()`	Return the arc sine
`ATAN()`	Return the arc tangent
`ATAN2()`, `ATAN()`	Return the arc tangent of the two arguments
`CEIL()`	Return the smallest integer value not less than the argument
`CEILING()`	Return the smallest integer value not less than the argument
`CONV()`	Convert numbers between different number bases
`COS()`	Return the cosine
`COT()`	Return the cotangent
`CRC32()`	Compute a cyclic redundancy check value
`DEGREES()`	Convert radians to degrees
`EXP()`	Raise to the power of
`FLOOR()`	Return the largest integer value not greater than the argument
`LN()`	Return the natural logarithm of the argument
`LOG()`	Return the natural logarithm of the first argument
`LOG10()`	Return the base-10 logarithm of the argument
`LOG2()`	Return the base-2 logarithm of the argument
`MOD()`	Return the remainder
`PI()`	Return the value of pi
`POW()`	Return the argument raised to the specified power
`POWER()`	Return the argument raised to the specified power
`RADIANS()`	Return argument converted to radians
`RAND()`	Return a random floating-point value
`ROUND()`	Round the argument
`SIGN()`	Return the sign of the argument
`SIN()`	Return the sine of the argument
`SQRT()`	Return the square root of the argument
`TAN()`	Return the tangent of the argument
`TRUNCATE()`	Truncate to specified number of decimal places

All mathematical functions return NULL in the event of an error.

ABS(X)

Returns the absolute value of X.

mysql> SELECT ABS(2);
        -> 2
mysql> SELECT ABS(-32);
        -> 32

This function is safe to use with BIGINT values.

ACOS(X)

Returns the arc cosine of X, that is, the value whose cosine is X. Returns NULL if X is not in the range -1 to 1.

mysql> SELECT ACOS(1);
        -> 0
mysql> SELECT ACOS(1.0001);
        -> NULL
mysql> SELECT ACOS(0);
        -> 1.5707963267949

ASIN(X)

Returns the arc sine of X, that is, the value whose sine is X. Returns NULL if X is not in the range -1 to 1.

mysql> SELECT ASIN(0.2);
        -> 0.20135792079033
mysql> SELECT ASIN('foo');

+-------------+
| ASIN('foo') |
+-------------+
|           0 |
+-------------+
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS;
+---------+------+-----------------------------------------+
| Level   | Code | Message                                 |
+---------+------+-----------------------------------------+
| Warning | 1292 | Truncated incorrect DOUBLE value: 'foo' |
+---------+------+-----------------------------------------+

ATAN(X)

Returns the arc tangent of X, that is, the value whose tangent is X.

mysql> SELECT ATAN(2);
        -> 1.1071487177941
mysql> SELECT ATAN(-2);
        -> -1.1071487177941

ATAN(Y,X), ATAN2(Y,X)
Returns the arc tangent of the two variables X and Y. It is similar to calculating the arc tangent of Y / X, except that the signs of both arguments are used to determine the quadrant of the result.
```
mysql> SELECT ATAN(-2,2);
        -> -0.78539816339745
mysql> SELECT ATAN2(PI(),0);
        -> 1.5707963267949
```
CEIL(X)
CEIL() is a synonym for CEILING().
CEILING(X)
Returns the smallest integer value not less than X.
```
mysql> SELECT CEILING(1.23);
        -> 2
mysql> SELECT CEILING(-1.23);
        -> -1
```
For exact-value numeric arguments, the return value has an exact-value numeric type. For string or floating-point arguments, the return value has a floating-point type.
CONV(N,from_base,to_base)
Converts numbers between different number bases. Returns a string representation of the number N, converted from base from_base to base to_base. Returns NULL if any argument is NULL. The argument N is interpreted as an integer, but may be specified as an integer or a string. The minimum base is 2 and the maximum base is 36. If from_base is a negative number, N is regarded as a signed number. Otherwise, N is treated as unsigned. CONV() works with 64-bit precision.
```
mysql> SELECT CONV('a',16,2);
        -> '1010'
mysql> SELECT CONV('6E',18,8);
        -> '172'
mysql> SELECT CONV(-17,10,-18);
        -> '-H'
mysql> SELECT CONV(10+'10'+'10'+X'0a',10,10);
        -> '40'
```
COS(X)
Returns the cosine of X, where X is given in radians.
```
mysql> SELECT COS(PI());
        -> -1
```

COT(X)

Returns the cotangent of X.

mysql> SELECT COT(12);
        -> -1.5726734063977
mysql> SELECT COT(0);
        -> out-of-range error

CRC32(expr)
Computes a cyclic redundancy check value and returns a 32-bit unsigned value. The result is NULL if the argument is NULL. The argument is expected to be a string and (if possible) is treated as one if it is not.
```
mysql> SELECT CRC32('MySQL');
        -> 3259397556
mysql> SELECT CRC32('mysql');
        -> 2501908538
```

DEGREES(X)

Returns the argument X, converted from radians to degrees.

mysql> SELECT DEGREES(PI());
        -> 180
mysql> SELECT DEGREES(PI() / 2);
        -> 90

EXP(X)
Returns the value of e (the base of natural logarithms) raised to the power of X. The inverse of this function is LOG() (using a single argument only) or LN().
```
mysql> SELECT EXP(2);
        -> 7.3890560989307
mysql> SELECT EXP(-2);
        -> 0.13533528323661
mysql> SELECT EXP(0);
        -> 1
```
FLOOR(X)
Returns the largest integer value not greater than X.
```
mysql> SELECT FLOOR(1.23), FLOOR(-1.23);
        -> 1, -2
```
For exact-value numeric arguments, the return value has an exact-value numeric type. For string or floating-point arguments, the return value has a floating-point type.
FORMAT(X,D)
Formats the number X to a format like '#,###,###.##', rounded to D decimal places, and returns the result as a string. For details, see Section 12.5, “String Functions”.
HEX(N_or_S)
This function can be used to obtain a hexadecimal representation of a decimal number or a string; the manner in which it does so varies according to the argument's type. See this function's description in Section 12.5, “String Functions”, for details.
LN(X)
Returns the natural logarithm of X; that is, the base-e logarithm of X. If X is less than or equal to 0.0E0, the function returns NULL and a warning “Invalid argument for logarithm” is reported.
```
mysql> SELECT LN(2);
        -> 0.69314718055995
mysql> SELECT LN(-2);
        -> NULL
```
This function is synonymous with LOG(X). The inverse of this function is the EXP() function.
LOG(X), LOG(B,X)
If called with one parameter, this function returns the natural logarithm of X. If X is less than or equal to 0.0E0, the function returns NULL and a warning “Invalid argument for logarithm” is reported.
The inverse of this function (when called with a single argument) is the EXP() function.
```
mysql> SELECT LOG(2);
        -> 0.69314718055995
mysql> SELECT LOG(-2);
        -> NULL
```
If called with two parameters, this function returns the logarithm of X to the base B. If X is less than or equal to 0, or if B is less than or equal to 1, then NULL is returned.
```
mysql> SELECT LOG(2,65536);
        -> 16
mysql> SELECT LOG(10,100);
        -> 2
mysql> SELECT LOG(1,100);
        -> NULL
```
LOG(B,X) is equivalent to LOG(X) / LOG(B).
LOG2(X)
Returns the base-2 logarithm of X. If X is less than or equal to 0.0E0, the function returns NULL and a warning “Invalid argument for logarithm” is reported.
```
mysql> SELECT LOG2(65536);
        -> 16
mysql> SELECT LOG2(-100);
        -> NULL
```
LOG2() is useful for finding out how many bits a number requires for storage. This function is equivalent to the expression LOG(X) / LOG(2).
LOG10(X)
Returns the base-10 logarithm of X. If X is less than or equal to 0.0E0, the function returns NULL and a warning “Invalid argument for logarithm” is reported.
```
mysql> SELECT LOG10(2);
        -> 0.30102999566398
mysql> SELECT LOG10(100);
        -> 2
mysql> SELECT LOG10(-100);
        -> NULL
```
LOG10(X) is equivalent to LOG(10,X).
MOD(N,M), N % M, N MOD M
Modulo operation. Returns the remainder of N divided by M.
```
mysql> SELECT MOD(234, 10);
        -> 4
mysql> SELECT 253 % 7;
        -> 1
mysql> SELECT MOD(29,9);
        -> 2
mysql> SELECT 29 MOD 9;
        -> 2
```
This function is safe to use with BIGINT values.
MOD() also works on values that have a fractional part and returns the exact remainder after division:
```
mysql> SELECT MOD(34.5,3);
        -> 1.5
```
MOD(N,0) returns NULL.
PI()
Returns the value of π (pi). The default number of decimal places displayed is seven, but MySQL uses the full double-precision value internally.
```
mysql> SELECT PI();
        -> 3.141593
mysql> SELECT PI()+0.000000000000000000;
        -> 3.141592653589793116
```

POW(X,Y)

Returns the value of X raised to the power of Y.

mysql> SELECT POW(2,2);
        -> 4
mysql> SELECT POW(2,-2);
        -> 0.25

POWER(X,Y)
This is a synonym for POW().
RADIANS(X)
Returns the argument X, converted from degrees to radians. (Note that π radians equals 180 degrees.)
```
mysql> SELECT RADIANS(90);
        -> 1.5707963267949
```
RAND([N])
Returns a random floating-point value v in the range 0 <= v < 1.0. To obtain a random integer R in the range i <= R < j, use the expression FLOOR(i + RAND() * (j − i)). For example, to obtain a random integer in the range the range 7 <= R < 12, use the following statement:
```
SELECT FLOOR(7 + (RAND() * 5));
```
If an integer argument N is specified, it is used as the seed value:
- With a constant initializer argument, the seed is initialized once when the statement is prepared, prior to execution.
- With a nonconstant initializer argument (such as a column name), the seed is initialized with the value for each invocation of RAND().
One implication of this behavior is that for equal argument values, RAND(N) returns the same value each time, and thus produces a repeatable sequence of column values. In the following example, the sequence of values produced by RAND(3) is the same both places it occurs.
```
mysql> CREATE TABLE t (i INT);
Query OK, 0 rows affected (0.42 sec)

mysql> INSERT INTO t VALUES(1),(2),(3);
Query OK, 3 rows affected (0.00 sec)
Records: 3 Duplicates: 0 Warnings: 0

mysql> SELECT i, RAND() FROM t;
+------+------------------+
| i | RAND() |
+------+------------------+
| 1 | 0.61914388706828 |
| 2 | 0.93845168309142 |
| 3 | 0.83482678498591 |
+------+------------------+
3 rows in set (0.00 sec)

mysql> SELECT i, RAND(3) FROM t;
+------+------------------+
| i | RAND(3) |
+------+------------------+
| 1 | 0.90576975597606 |
| 2 | 0.37307905813035 |
| 3 | 0.14808605345719 |
+------+------------------+
3 rows in set (0.00 sec)

mysql> SELECT i, RAND() FROM t;
+------+------------------+
| i | RAND() |
+------+------------------+
| 1 | 0.35877890638893 |
| 2 | 0.28941420772058 |
| 3 | 0.37073435016976 |
+------+------------------+
3 rows in set (0.00 sec)

mysql> SELECT i, RAND(3) FROM t;
+------+------------------+
| i | RAND(3) |
+------+------------------+
| 1 | 0.90576975597606 |
| 2 | 0.37307905813035 |
| 3 | 0.14808605345719 |
+------+------------------+
3 rows in set (0.01 sec)
```
RAND() in a WHERE clause is evaluated for every row (when selecting from one table) or combination of rows (when selecting from a multiple-table join). Thus, for optimizer purposes, RAND() is not a constant value and cannot be used for index optimizations. For more information, see Section 8.2.1.17, “Function Call Optimization”.
Use of a column with RAND() values in an ORDER BY or GROUP BY clause may yield unexpected results because for either clause a RAND() expression can be evaluated multiple times for the same row, each time returning a different result. If the goal is to retrieve rows in random order, you can use a statement like this:
```
SELECT * FROM tbl_name ORDER BY RAND();
```
To select a random sample from a set of rows, combine ORDER BY RAND() with LIMIT:
```
SELECT * FROM table1, table2 WHERE a=b AND c<d ORDER BY RAND() LIMIT 1000;
```
RAND() is not meant to be a perfect random generator. It is a fast way to generate random numbers on demand that is portable between platforms for the same MySQL version.
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT. (Bug #49222)
ROUND(X), ROUND(X,D)
Rounds the argument X to D decimal places. The rounding algorithm depends on the data type of X. D defaults to 0 if not specified. D can be negative to cause D digits left of the decimal point of the value X to become zero.
```
mysql> SELECT ROUND(-1.23);
        -> -1
mysql> SELECT ROUND(-1.58);
        -> -2
mysql> SELECT ROUND(1.58);
        -> 2
mysql> SELECT ROUND(1.298, 1);
        -> 1.3
mysql> SELECT ROUND(1.298, 0);
        -> 1
mysql> SELECT ROUND(23.298, -1);
        -> 20
```
The return value has the same type as the first argument (assuming that it is integer, double, or decimal). This means that for an integer argument, the result is an integer (no decimal places):
```
mysql> SELECT ROUND(150.000,2), ROUND(150,2);
+------------------+--------------+
| ROUND(150.000,2) | ROUND(150,2) |
+------------------+--------------+
|           150.00 |          150 |
+------------------+--------------+
```
ROUND() uses the following rules depending on the type of the first argument:
- For exact-value numbers, ROUND() uses the “round half away from zero” or “round toward nearest” rule: A value with a fractional part of .5 or greater is rounded up to the next integer if positive or down to the next integer if negative. (In other words, it is rounded away from zero.) A value with a fractional part less than .5 is rounded down to the next integer if positive or up to the next integer if negative.
- For approximate-value numbers, the result depends on the C library. On many systems, this means that ROUND() uses the "round to nearest even" rule: A value with any fractional part is rounded to the nearest even integer.
The following example shows how rounding differs for exact and approximate values:
```
mysql> SELECT ROUND(2.5), ROUND(25E-1);
+------------+--------------+
| ROUND(2.5) | ROUND(25E-1) |
+------------+--------------+
| 3          |            2 |
+------------+--------------+
```
For more information, see Section 12.23, “Precision Math”.

SIGN(X)

Returns the sign of the argument as -1, 0, or 1, depending on whether X is negative, zero, or positive.

mysql> SELECT SIGN(-32);
        -> -1
mysql> SELECT SIGN(0);
        -> 0
mysql> SELECT SIGN(234);
        -> 1

SIN(X)

Returns the sine of X, where X is given in radians.

mysql> SELECT SIN(PI());
        -> 1.2246063538224e-16
mysql> SELECT ROUND(SIN(PI()));
        -> 0

SQRT(X)

Returns the square root of a nonnegative number X.

mysql> SELECT SQRT(4);
        -> 2
mysql> SELECT SQRT(20);
        -> 4.4721359549996
mysql> SELECT SQRT(-16);
        -> NULL

TAN(X)

Returns the tangent of X, where X is given in radians.

mysql> SELECT TAN(PI());
        -> -1.2246063538224e-16
mysql> SELECT TAN(PI()+1);
        -> 1.5574077246549

TRUNCATE(X,D)

Returns the number X, truncated to D decimal places. If D is 0, the result has no decimal point or fractional part. D can be negative to cause D digits left of the decimal point of the value X to become zero.

mysql> SELECT TRUNCATE(1.223,1);
        -> 1.2
mysql> SELECT TRUNCATE(1.999,1);
        -> 1.9
mysql> SELECT TRUNCATE(1.999,0);
        -> 1
mysql> SELECT TRUNCATE(-1.999,1);
        -> -1.9
mysql> SELECT TRUNCATE(122,-2);
       -> 100
mysql> SELECT TRUNCATE(10.28*100,0);
       -> 1028

All numbers are rounded toward zero.

12.7 Date and Time Functions

This section describes the functions that can be used to manipulate temporal values. See Section 11.3, “Date and Time Types”, for a description of the range of values each date and time type has and the valid formats in which values may be specified.

Table 12.13 Date and Time Functions

Name	Description
`ADDDATE()`	Add time values (intervals) to a date value
`ADDTIME()`	Add time
`CONVERT_TZ()`	Convert from one time zone to another
`CURDATE()`	Return the current date
`CURRENT_DATE()`, `CURRENT_DATE`	Synonyms for CURDATE()
`CURRENT_TIME()`, `CURRENT_TIME`	Synonyms for CURTIME()
`CURRENT_TIMESTAMP()`, `CURRENT_TIMESTAMP`	Synonyms for NOW()
`CURTIME()`	Return the current time
`DATE()`	Extract the date part of a date or datetime expression
`DATE_ADD()`	Add time values (intervals) to a date value
`DATE_FORMAT()`	Format date as specified
`DATE_SUB()`	Subtract a time value (interval) from a date
`DATEDIFF()`	Subtract two dates
`DAY()`	Synonym for DAYOFMONTH()
`DAYNAME()`	Return the name of the weekday
`DAYOFMONTH()`	Return the day of the month (0-31)
`DAYOFWEEK()`	Return the weekday index of the argument
`DAYOFYEAR()`	Return the day of the year (1-366)
`EXTRACT()`	Extract part of a date
`FROM_DAYS()`	Convert a day number to a date
`FROM_UNIXTIME()`	Format Unix timestamp as a date
`GET_FORMAT()`	Return a date format string
`HOUR()`	Extract the hour
`LAST_DAY`	Return the last day of the month for the argument
`LOCALTIME()`, `LOCALTIME`	Synonym for NOW()
`LOCALTIMESTAMP`, `LOCALTIMESTAMP()`	Synonym for NOW()
`MAKEDATE()`	Create a date from the year and day of year
`MAKETIME()`	Create time from hour, minute, second
`MICROSECOND()`	Return the microseconds from argument
`MINUTE()`	Return the minute from the argument
`MONTH()`	Return the month from the date passed
`MONTHNAME()`	Return the name of the month
`NOW()`	Return the current date and time
`PERIOD_ADD()`	Add a period to a year-month
`PERIOD_DIFF()`	Return the number of months between periods
`QUARTER()`	Return the quarter from a date argument
`SEC_TO_TIME()`	Converts seconds to 'HH:MM:SS' format
`SECOND()`	Return the second (0-59)
`STR_TO_DATE()`	Convert a string to a date
`SUBDATE()`	Synonym for DATE_SUB() when invoked with three arguments
`SUBTIME()`	Subtract times
`SYSDATE()`	Return the time at which the function executes
`TIME()`	Extract the time portion of the expression passed
`TIME_FORMAT()`	Format as time
`TIME_TO_SEC()`	Return the argument converted to seconds
`TIMEDIFF()`	Subtract time
`TIMESTAMP()`	With a single argument, this function returns the date or datetime expression; with two arguments, the sum of the arguments
`TIMESTAMPADD()`	Add an interval to a datetime expression
`TIMESTAMPDIFF()`	Subtract an interval from a datetime expression
`TO_DAYS()`	Return the date argument converted to days
`TO_SECONDS()`	Return the date or datetime argument converted to seconds since Year 0
`UNIX_TIMESTAMP()`	Return a Unix timestamp
`UTC_DATE()`	Return the current UTC date
`UTC_TIME()`	Return the current UTC time
`UTC_TIMESTAMP()`	Return the current UTC date and time
`WEEK()`	Return the week number
`WEEKDAY()`	Return the weekday index
`WEEKOFYEAR()`	Return the calendar week of the date (1-53)
`YEAR()`	Return the year
`YEARWEEK()`	Return the year and week

Here is an example that uses date functions. The following query selects all rows with a date_col value from within the last 30 days:

mysql> SELECT something FROM tbl_name
    -> WHERE DATE_SUB(CURDATE(),INTERVAL 30 DAY) <= date_col;

The query also selects rows with dates that lie in the future.

Functions that expect date values usually accept datetime values and ignore the time part. Functions that expect time values usually accept datetime values and ignore the date part.

Functions that return the current date or time each are evaluated only once per query at the start of query execution. This means that multiple references to a function such as NOW() within a single query always produce the same result. (For our purposes, a single query also includes a call to a stored program (stored routine, trigger, or event) and all subprograms called by that program.) This principle also applies to CURDATE(), CURTIME(), UTC_DATE(), UTC_TIME(), UTC_TIMESTAMP(), and to any of their synonyms.

The CURRENT_TIMESTAMP(), CURRENT_TIME(), CURRENT_DATE(), and FROM_UNIXTIME() functions return values in the connection's current time zone, which is available as the value of the time_zone system variable. In addition, UNIX_TIMESTAMP() assumes that its argument is a datetime value in the current time zone. See Section 5.1.12, “MySQL Server Time Zone Support”.

Some date functions can be used with “zero” dates or incomplete dates such as '2001-11-00', whereas others cannot. Functions that extract parts of dates typically work with incomplete dates and thus can return 0 when you might otherwise expect a nonzero value. For example:

mysql> SELECT DAYOFMONTH('2001-11-00'), MONTH('2005-00-00');
        -> 0, 0

Other functions expect complete dates and return NULL for incomplete dates. These include functions that perform date arithmetic or that map parts of dates to names. For example:

mysql> SELECT DATE_ADD('2006-05-00',INTERVAL 1 DAY);
        -> NULL
mysql> SELECT DAYNAME('2006-05-00');
        -> NULL

Several functions are more strict when passed a DATE() function value as their argument and reject incomplete dates with a day part of zero. These functions are affected: CONVERT_TZ(), DATE_ADD(), DATE_SUB(), DAYOFYEAR(), LAST_DAY() (permits a day part of zero), TIMESTAMPDIFF(), TO_DAYS(), TO_SECONDS(), WEEK(), WEEKDAY(), WEEKOFYEAR(), YEARWEEK().

Fractional seconds for TIME, DATETIME, and TIMESTAMP values are supported, with up to microsecond precision. Functions that take temporal arguments accept values with fractional seconds. Return values from temporal functions include fractional seconds as appropriate.

ADDDATE(date,INTERVAL expr unit), ADDDATE(expr,days)
When invoked with the INTERVAL form of the second argument, ADDDATE() is a synonym for DATE_ADD(). The related function SUBDATE() is a synonym for DATE_SUB(). For information on the INTERVAL unit argument, see the discussion for DATE_ADD().
```
mysql> SELECT DATE_ADD('2008-01-02', INTERVAL 31 DAY);
        -> '2008-02-02'
mysql> SELECT ADDDATE('2008-01-02', INTERVAL 31 DAY);
        -> '2008-02-02'
```
When invoked with the days form of the second argument, MySQL treats it as an integer number of days to be added to expr.
```
mysql> SELECT ADDDATE('2008-01-02', 31);
        -> '2008-02-02'
```

ADDTIME(expr1,expr2)

ADDTIME() adds expr2 to expr1 and returns the result. expr1 is a time or datetime expression, and expr2 is a time expression.

mysql> SELECT ADDTIME('2007-12-31 23:59:59.999999', '1 1:1:1.000002');
        -> '2008-01-02 01:01:01.000001'
mysql> SELECT ADDTIME('01:00:00.999999', '02:00:00.999998');
        -> '03:00:01.999997'

CONVERT_TZ(dt,from_tz,to_tz)
CONVERT_TZ() converts a datetime value dt from the time zone given by from_tz to the time zone given by to_tz and returns the resulting value. Time zones are specified as described in Section 5.1.12, “MySQL Server Time Zone Support”. This function returns NULL if the arguments are invalid.
If the value falls out of the supported range of the TIMESTAMP type when converted from from_tz to UTC, no conversion occurs. The TIMESTAMP range is described in Section 11.1.2, “Date and Time Type Overview”.
```
mysql> SELECT CONVERT_TZ('2004-01-01 12:00:00','GMT','MET');
        -> '2004-01-01 13:00:00'
mysql> SELECT CONVERT_TZ('2004-01-01 12:00:00','+00:00','+10:00');
        -> '2004-01-01 22:00:00'
```
Note

To use named time zones such as 'MET' or 'Europe/Moscow', the time zone tables must be properly set up. See Section 5.1.12, “MySQL Server Time Zone Support”, for instructions.
CURDATE()
Returns the current date as a value in 'YYYY-MM-DD' or YYYYMMDD format, depending on whether the function is used in a string or numeric context.
```
mysql> SELECT CURDATE();
        -> '2008-06-13'
mysql> SELECT CURDATE() + 0;
        -> 20080613
```
CURRENT_DATE, CURRENT_DATE()
CURRENT_DATE and CURRENT_DATE() are synonyms for CURDATE().
CURRENT_TIME, CURRENT_TIME([fsp])
CURRENT_TIME and CURRENT_TIME() are synonyms for CURTIME().
CURRENT_TIMESTAMP, CURRENT_TIMESTAMP([fsp])
CURRENT_TIMESTAMP and CURRENT_TIMESTAMP() are synonyms for NOW().
CURTIME([fsp])
Returns the current time as a value in 'HH:MM:SS' or HHMMSS format, depending on whether the function is used in a string or numeric context. The value is expressed in the current time zone.
If the fsp argument is given to specify a fractional seconds precision from 0 to 6, the return value includes a fractional seconds part of that many digits.
```
mysql> SELECT CURTIME();
        -> '23:50:26'
mysql> SELECT CURTIME() + 0;
        -> 235026.000000
```

DATE(expr)

Extracts the date part of the date or datetime expression expr.

mysql> SELECT DATE('2003-12-31 01:02:03');
        -> '2003-12-31'

DATEDIFF(expr1,expr2)
DATEDIFF() returns expr1 − expr2 expressed as a value in days from one date to the other. expr1 and expr2 are date or date-and-time expressions. Only the date parts of the values are used in the calculation.
```
mysql> SELECT DATEDIFF('2007-12-31 23:59:59','2007-12-30');
        -> 1
mysql> SELECT DATEDIFF('2010-11-30 23:59:59','2010-12-31');
        -> -31
```

DATE_ADD(date,INTERVAL expr unit), DATE_SUB(date,INTERVAL expr unit)

These functions perform date arithmetic. The date argument specifies the starting date or datetime value. expr is an expression specifying the interval value to be added or subtracted from the starting date. expr is a string; it may start with a - for negative intervals. unit is a keyword indicating the units in which the expression should be interpreted.

The INTERVAL keyword and the unit specifier are not case sensitive.

The following table shows the expected form of the expr argument for each unit value.

`unit` Value	Expected `expr` Format
`MICROSECOND`	`MICROSECONDS`
`SECOND`	`SECONDS`
`MINUTE`	`MINUTES`
`HOUR`	`HOURS`
`DAY`	`DAYS`
`WEEK`	`WEEKS`
`MONTH`	`MONTHS`
`QUARTER`	`QUARTERS`
`YEAR`	`YEARS`
`SECOND_MICROSECOND`	`'SECONDS.MICROSECONDS'`
`MINUTE_MICROSECOND`	`'MINUTES:SECONDS.MICROSECONDS'`
`MINUTE_SECOND`	`'MINUTES:SECONDS'`
`HOUR_MICROSECOND`	`'HOURS:MINUTES:SECONDS.MICROSECONDS'`
`HOUR_SECOND`	`'HOURS:MINUTES:SECONDS'`
`HOUR_MINUTE`	`'HOURS:MINUTES'`
`DAY_MICROSECOND`	`'DAYS HOURS:MINUTES:SECONDS.MICROSECONDS'`
`DAY_SECOND`	`'DAYS HOURS:MINUTES:SECONDS'`
`DAY_MINUTE`	`'DAYS HOURS:MINUTES'`
`DAY_HOUR`	`'DAYS HOURS'`
`YEAR_MONTH`	`'YEARS-MONTHS'`

The return value depends on the arguments:

DATETIME if the first argument is a DATETIME (or TIMESTAMP) value, or if the first argument is a DATE and the unit value uses HOURS, MINUTES, or SECONDS.
String otherwise.

To ensure that the result is DATETIME, you can use CAST() to convert the first argument to DATETIME.

MySQL permits any punctuation delimiter in the expr format. Those shown in the table are the suggested delimiters. If the date argument is a DATE value and your calculations involve only YEAR, MONTH, and DAY parts (that is, no time parts), the result is a DATE value. Otherwise, the result is a DATETIME value.

Date arithmetic also can be performed using INTERVAL together with the + or - operator:

date + INTERVAL expr unit
date - INTERVAL expr unit

INTERVAL expr unit is permitted on either side of the + operator if the expression on the other side is a date or datetime value. For the - operator, INTERVAL expr unit is permitted only on the right side, because it makes no sense to subtract a date or datetime value from an interval.

mysql> SELECT '2008-12-31 23:59:59' + INTERVAL 1 SECOND;
        -> '2009-01-01 00:00:00'
mysql> SELECT INTERVAL 1 DAY + '2008-12-31';
        -> '2009-01-01'
mysql> SELECT '2005-01-01' - INTERVAL 1 SECOND;
        -> '2004-12-31 23:59:59'
mysql> SELECT DATE_ADD('2000-12-31 23:59:59',
    ->                 INTERVAL 1 SECOND);
        -> '2001-01-01 00:00:00'
mysql> SELECT DATE_ADD('2010-12-31 23:59:59',
    ->                 INTERVAL 1 DAY);
        -> '2011-01-01 23:59:59'
mysql> SELECT DATE_ADD('2100-12-31 23:59:59',
    ->                 INTERVAL '1:1' MINUTE_SECOND);
        -> '2101-01-01 00:01:00'
mysql> SELECT DATE_SUB('2005-01-01 00:00:00',
    ->                 INTERVAL '1 1:1:1' DAY_SECOND);
        -> '2004-12-30 22:58:59'
mysql> SELECT DATE_ADD('1900-01-01 00:00:00',
    ->                 INTERVAL '-1 10' DAY_HOUR);
        -> '1899-12-30 14:00:00'
mysql> SELECT DATE_SUB('1998-01-02', INTERVAL 31 DAY);
        -> '1997-12-02'
mysql> SELECT DATE_ADD('1992-12-31 23:59:59.000002',
    ->            INTERVAL '1.999999' SECOND_MICROSECOND);
        -> '1993-01-01 00:00:01.000001'

If you specify an interval value that is too short (does not include all the interval parts that would be expected from the unit keyword), MySQL assumes that you have left out the leftmost parts of the interval value. For example, if you specify a unit of DAY_SECOND, the value of expr is expected to have days, hours, minutes, and seconds parts. If you specify a value like '1:10', MySQL assumes that the days and hours parts are missing and the value represents minutes and seconds. In other words, '1:10' DAY_SECOND is interpreted in such a way that it is equivalent to '1:10' MINUTE_SECOND. This is analogous to the way that MySQL interprets TIME values as representing elapsed time rather than as a time of day.

Because expr is treated as a string, be careful if you specify a nonstring value with INTERVAL. For example, with an interval specifier of HOUR_MINUTE, 6/4 evaluates to 1.5000 and is treated as 1 hour, 5000 minutes:

mysql> SELECT 6/4;
        -> 1.5000
mysql> SELECT DATE_ADD('2009-01-01', INTERVAL 6/4 HOUR_MINUTE);
        -> '2009-01-04 12:20:00'

To ensure interpretation of the interval value as you expect, a CAST() operation may be used. To treat 6/4 as 1 hour, 5 minutes, cast it to a DECIMAL value with a single fractional digit:

mysql> SELECT CAST(6/4 AS DECIMAL(3,1));
        -> 1.5
mysql> SELECT DATE_ADD('1970-01-01 12:00:00',
    ->                 INTERVAL CAST(6/4 AS DECIMAL(3,1)) HOUR_MINUTE);
        -> '1970-01-01 13:05:00'

If you add to or subtract from a date value something that contains a time part, the result is automatically converted to a datetime value:

mysql> SELECT DATE_ADD('2013-01-01', INTERVAL 1 DAY);
        -> '2013-01-02'
mysql> SELECT DATE_ADD('2013-01-01', INTERVAL 1 HOUR);
        -> '2013-01-01 01:00:00'

If you add MONTH, YEAR_MONTH, or YEAR and the resulting date has a day that is larger than the maximum day for the new month, the day is adjusted to the maximum days in the new month:

mysql> SELECT DATE_ADD('2009-01-30', INTERVAL 1 MONTH);
        -> '2009-02-28'

Date arithmetic operations require complete dates and do not work with incomplete dates such as '2006-07-00' or badly malformed dates:

mysql> SELECT DATE_ADD('2006-07-00', INTERVAL 1 DAY);
        -> NULL
mysql> SELECT '2005-03-32' + INTERVAL 1 MONTH;
        -> NULL

DATE_FORMAT(date,format)

Formats the date value according to the format string.

The following specifiers may be used in the format string. The % character is required before format specifier characters.

Specifier	Description
`%a`	Abbreviated weekday name (`Sun`..`Sat`)
`%b`	Abbreviated month name (`Jan`..`Dec`)
`%c`	Month, numeric (`0`..`12`)
`%D`	Day of the month with English suffix (`0th`, `1st`, `2nd`, `3rd`, …)
`%d`	Day of the month, numeric (`00`..`31`)
`%e`	Day of the month, numeric (`0`..`31`)
`%f`	Microseconds (`000000`..`999999`)
`%H`	Hour (`00`..`23`)
`%h`	Hour (`01`..`12`)
`%I`	Hour (`01`..`12`)
`%i`	Minutes, numeric (`00`..`59`)
`%j`	Day of year (`001`..`366`)
`%k`	Hour (`0`..`23`)
`%l`	Hour (`1`..`12`)
`%M`	Month name (`January`..`December`)
`%m`	Month, numeric (`00`..`12`)
`%p`	`AM` or `PM`
`%r`	Time, 12-hour (`hh:mm:ss` followed by `AM` or `PM`)
`%S`	Seconds (`00`..`59`)
`%s`	Seconds (`00`..`59`)
`%T`	Time, 24-hour (`hh:mm:ss`)
`%U`	Week (`00`..`53`), where Sunday is the first day of the week; `WEEK()` mode 0
`%u`	Week (`00`..`53`), where Monday is the first day of the week; `WEEK()` mode 1
`%V`	Week (`01`..`53`), where Sunday is the first day of the week; `WEEK()` mode 2; used with `%X`
`%v`	Week (`01`..`53`), where Monday is the first day of the week; `WEEK()` mode 3; used with `%x`
`%W`	Weekday name (`Sunday`..`Saturday`)
`%w`	Day of the week (`0`=Sunday..`6`=Saturday)
`%X`	Year for the week where Sunday is the first day of the week, numeric, four digits; used with `%V`
`%x`	Year for the week, where Monday is the first day of the week, numeric, four digits; used with `%v`
`%Y`	Year, numeric, four digits
`%y`	Year, numeric (two digits)
`%%`	A literal `%` character
`%x`	`x`, for any “`x`” not listed above

Ranges for the month and day specifiers begin with zero due to the fact that MySQL permits the storing of incomplete dates such as '2014-00-00'.

The language used for day and month names and abbreviations is controlled by the value of the lc_time_names system variable (Section 10.15, “MySQL Server Locale Support”).

For the %U, %u, %V, and %v specifiers, see the description of the WEEK() function for information about the mode values. The mode affects how week numbering occurs.

DATE_FORMAT() returns a string with a character set and collation given by character_set_connection and collation_connection so that it can return month and weekday names containing non-ASCII characters.

mysql> SELECT DATE_FORMAT('2009-10-04 22:23:00', '%W %M %Y');
        -> 'Sunday October 2009'
mysql> SELECT DATE_FORMAT('2007-10-04 22:23:00', '%H:%i:%s');
        -> '22:23:00'
mysql> SELECT DATE_FORMAT('1900-10-04 22:23:00',
    ->                 '%D %y %a %d %m %b %j');
        -> '4th 00 Thu 04 10 Oct 277'
mysql> SELECT DATE_FORMAT('1997-10-04 22:23:00',
    ->                 '%H %k %I %r %T %S %w');
        -> '22 22 10 10:23:00 PM 22:23:00 00 6'
mysql> SELECT DATE_FORMAT('1999-01-01', '%X %V');
        -> '1998 52'
mysql> SELECT DATE_FORMAT('2006-06-00', '%d');
        -> '00'

DATE_SUB(date,INTERVAL expr unit)
See the description for DATE_ADD().
DAY(date)
DAY() is a synonym for DAYOFMONTH().
DAYNAME(date)
Returns the name of the weekday for date. The language used for the name is controlled by the value of the lc_time_names system variable (Section 10.15, “MySQL Server Locale Support”).
```
mysql> SELECT DAYNAME('2007-02-03');
        -> 'Saturday'
```
DAYOFMONTH(date)
Returns the day of the month for date, in the range 1 to 31, or 0 for dates such as '0000-00-00' or '2008-00-00' that have a zero day part.
```
mysql> SELECT DAYOFMONTH('2007-02-03');
        -> 3
```
DAYOFWEEK(date)
Returns the weekday index for date (1 = Sunday, 2 = Monday, …, 7 = Saturday). These index values correspond to the ODBC standard.
```
mysql> SELECT DAYOFWEEK('2007-02-03');
        -> 7
```
DAYOFYEAR(date)
Returns the day of the year for date, in the range 1 to 366.
```
mysql> SELECT DAYOFYEAR('2007-02-03');
        -> 34
```

EXTRACT(unit FROM date)

The EXTRACT() function uses the same kinds of unit specifiers as DATE_ADD() or DATE_SUB(), but extracts parts from the date rather than performing date arithmetic.

mysql> SELECT EXTRACT(YEAR FROM '2009-07-02');
       -> 2009
mysql> SELECT EXTRACT(YEAR_MONTH FROM '2009-07-02 01:02:03');
       -> 200907
mysql> SELECT EXTRACT(DAY_MINUTE FROM '2009-07-02 01:02:03');
       -> 20102
mysql> SELECT EXTRACT(MICROSECOND
    ->                FROM '2003-01-02 10:30:00.000123');
        -> 123

FROM_DAYS(N)
Given a day number N, returns a DATE value.
```
mysql> SELECT FROM_DAYS(730669);
        -> '2000-07-03'
```
Use FROM_DAYS() with caution on old dates. It is not intended for use with values that precede the advent of the Gregorian calendar (1582). See Section 12.8, “What Calendar Is Used By MySQL?”.
FROM_UNIXTIME(unix_timestamp), FROM_UNIXTIME(unix_timestamp,format)
Returns a representation of the unix_timestamp argument as a value in 'YYYY-MM-DD HH:MM:SS' or YYYYMMDDHHMMSS format, depending on whether the function is used in a string or numeric context. The value is expressed in the current time zone. unix_timestamp is an internal timestamp value such as is produced by the UNIX_TIMESTAMP() function.
If format is given, the result is formatted according to the format string, which is used the same way as listed in the entry for the DATE_FORMAT() function.
```
mysql> SELECT FROM_UNIXTIME(1447430881);
        -> '2015-11-13 10:08:01'
mysql> SELECT FROM_UNIXTIME(1447430881) + 0;
        -> 20151113100801
mysql> SELECT FROM_UNIXTIME(UNIX_TIMESTAMP(),
    ->                      '%Y %D %M %h:%i:%s %x');
        -> '2015 13th November 10:08:01 2015'
```
Note: If you use UNIX_TIMESTAMP() and FROM_UNIXTIME() to convert between TIMESTAMP values and Unix timestamp values, the conversion is lossy because the mapping is not one-to-one in both directions. For details, see the description of the UNIX_TIMESTAMP() function.

GET_FORMAT({DATE|TIME|DATETIME}, {'EUR'|'USA'|'JIS'|'ISO'|'INTERNAL'})

Returns a format string. This function is useful in combination with the DATE_FORMAT() and the STR_TO_DATE() functions.

The possible values for the first and second arguments result in several possible format strings (for the specifiers used, see the table in the DATE_FORMAT() function description). ISO format refers to ISO 9075, not ISO 8601.

Function Call	Result
`GET_FORMAT(DATE,'USA')`	`'%m.%d.%Y'`
`GET_FORMAT(DATE,'JIS')`	`'%Y-%m-%d'`
`GET_FORMAT(DATE,'ISO')`	`'%Y-%m-%d'`
`GET_FORMAT(DATE,'EUR')`	`'%d.%m.%Y'`
`GET_FORMAT(DATE,'INTERNAL')`	`'%Y%m%d'`
`GET_FORMAT(DATETIME,'USA')`	`'%Y-%m-%d %H.%i.%s'`
`GET_FORMAT(DATETIME,'JIS')`	`'%Y-%m-%d %H:%i:%s'`
`GET_FORMAT(DATETIME,'ISO')`	`'%Y-%m-%d %H:%i:%s'`
`GET_FORMAT(DATETIME,'EUR')`	`'%Y-%m-%d %H.%i.%s'`
`GET_FORMAT(DATETIME,'INTERNAL')`	`'%Y%m%d%H%i%s'`
`GET_FORMAT(TIME,'USA')`	`'%h:%i:%s %p'`
`GET_FORMAT(TIME,'JIS')`	`'%H:%i:%s'`
`GET_FORMAT(TIME,'ISO')`	`'%H:%i:%s'`
`GET_FORMAT(TIME,'EUR')`	`'%H.%i.%s'`
`GET_FORMAT(TIME,'INTERNAL')`	`'%H%i%s'`

TIMESTAMP can also be used as the first argument to GET_FORMAT(), in which case the function returns the same values as for DATETIME.

mysql> SELECT DATE_FORMAT('2003-10-03',GET_FORMAT(DATE,'EUR'));
        -> '03.10.2003'
mysql> SELECT STR_TO_DATE('10.31.2003',GET_FORMAT(DATE,'USA'));
        -> '2003-10-31'

HOUR(time)
Returns the hour for time. The range of the return value is 0 to 23 for time-of-day values. However, the range of TIME values actually is much larger, so HOUR can return values greater than 23.
```
mysql> SELECT HOUR('10:05:03');
        -> 10
mysql> SELECT HOUR('272:59:59');
        -> 272
```

LAST_DAY(date)

Takes a date or datetime value and returns the corresponding value for the last day of the month. Returns NULL if the argument is invalid.

mysql> SELECT LAST_DAY('2003-02-05');
        -> '2003-02-28'
mysql> SELECT LAST_DAY('2004-02-05');
        -> '2004-02-29'
mysql> SELECT LAST_DAY('2004-01-01 01:01:01');
        -> '2004-01-31'
mysql> SELECT LAST_DAY('2003-03-32');
        -> NULL

LOCALTIME, LOCALTIME([fsp])
LOCALTIME and LOCALTIME() are synonyms for NOW().
LOCALTIMESTAMP, LOCALTIMESTAMP([fsp])
LOCALTIMESTAMP and LOCALTIMESTAMP() are synonyms for NOW().

MAKEDATE(year,dayofyear)

Returns a date, given year and day-of-year values. dayofyear must be greater than 0 or the result is NULL.

mysql> SELECT MAKEDATE(2011,31), MAKEDATE(2011,32);
        -> '2011-01-31', '2011-02-01'
mysql> SELECT MAKEDATE(2011,365), MAKEDATE(2014,365);
        -> '2011-12-31', '2014-12-31'
mysql> SELECT MAKEDATE(2011,0);
        -> NULL

MAKETIME(hour,minute,second)
Returns a time value calculated from the hour, minute, and second arguments.
The second argument can have a fractional part.
```
mysql> SELECT MAKETIME(12,15,30);
        -> '12:15:30'
```

MICROSECOND(expr)

Returns the microseconds from the time or datetime expression expr as a number in the range from 0 to 999999.

mysql> SELECT MICROSECOND('12:00:00.123456');
        -> 123456
mysql> SELECT MICROSECOND('2009-12-31 23:59:59.000010');
        -> 10

MINUTE(time)

Returns the minute for time, in the range 0 to 59.

mysql> SELECT MINUTE('2008-02-03 10:05:03');
        -> 5

MONTH(date)
Returns the month for date, in the range 1 to 12 for January to December, or 0 for dates such as '0000-00-00' or '2008-00-00' that have a zero month part.
```
mysql> SELECT MONTH('2008-02-03');
        -> 2
```
MONTHNAME(date)
Returns the full name of the month for date. The language used for the name is controlled by the value of the lc_time_names system variable (Section 10.15, “MySQL Server Locale Support”).
```
mysql> SELECT MONTHNAME('2008-02-03');
        -> 'February'
```
NOW([fsp])
Returns the current date and time as a value in 'YYYY-MM-DD HH:MM:SS' or YYYYMMDDHHMMSS format, depending on whether the function is used in a string or numeric context. The value is expressed in the current time zone.
If the fsp argument is given to specify a fractional seconds precision from 0 to 6, the return value includes a fractional seconds part of that many digits.
```
mysql> SELECT NOW();
        -> '2007-12-15 23:50:26'
mysql> SELECT NOW() + 0;
        -> 20071215235026.000000
```
NOW() returns a constant time that indicates the time at which the statement began to execute. (Within a stored function or trigger, NOW() returns the time at which the function or triggering statement began to execute.) This differs from the behavior for SYSDATE(), which returns the exact time at which it executes.
```
mysql> SELECT NOW(), SLEEP(2), NOW();
+---------------------+----------+---------------------+
| NOW()               | SLEEP(2) | NOW()               |
+---------------------+----------+---------------------+
| 2006-04-12 13:47:36 |        0 | 2006-04-12 13:47:36 |
+---------------------+----------+---------------------+

mysql> SELECT SYSDATE(), SLEEP(2), SYSDATE();
+---------------------+----------+---------------------+
| SYSDATE()           | SLEEP(2) | SYSDATE()           |
+---------------------+----------+---------------------+
| 2006-04-12 13:47:44 |        0 | 2006-04-12 13:47:46 |
+---------------------+----------+---------------------+
```
In addition, the SET TIMESTAMP statement affects the value returned by NOW() but not by SYSDATE(). This means that timestamp settings in the binary log have no effect on invocations of SYSDATE(). Setting the timestamp to a nonzero value causes each subsequent invocation of NOW() to return that value. Setting the timestamp to zero cancels this effect so that NOW() once again returns the current date and time.
See the description for SYSDATE() for additional information about the differences between the two functions.
PERIOD_ADD(P,N)
Adds N months to period P (in the format YYMM or YYYYMM). Returns a value in the format YYYYMM. Note that the period argument P is not a date value.
```
mysql> SELECT PERIOD_ADD(200801,2);
        -> 200803
```
PERIOD_DIFF(P1,P2)
Returns the number of months between periods P1 and P2. P1 and P2 should be in the format YYMM or YYYYMM. Note that the period arguments P1 and P2 are not date values.
```
mysql> SELECT PERIOD_DIFF(200802,200703);
        -> 11
```
QUARTER(date)
Returns the quarter of the year for date, in the range 1 to 4.
```
mysql> SELECT QUARTER('2008-04-01');
        -> 2
```
SECOND(time)
Returns the second for time, in the range 0 to 59.
```
mysql> SELECT SECOND('10:05:03');
        -> 3
```
SEC_TO_TIME(seconds)
Returns the seconds argument, converted to hours, minutes, and seconds, as a TIME value. The range of the result is constrained to that of the TIME data type. A warning occurs if the argument corresponds to a value outside that range.
```
mysql> SELECT SEC_TO_TIME(2378);
        -> '00:39:38'
mysql> SELECT SEC_TO_TIME(2378) + 0;
        -> 3938
```
STR_TO_DATE(str,format)
This is the inverse of the DATE_FORMAT() function. It takes a string str and a format string format. STR_TO_DATE() returns a DATETIME value if the format string contains both date and time parts, or a DATE or TIME value if the string contains only date or time parts. If the date, time, or datetime value extracted from str is illegal, STR_TO_DATE() returns NULL and produces a warning.
The server scans str attempting to match format to it. The format string can contain literal characters and format specifiers beginning with %. Literal characters in format must match literally in str. Format specifiers in format must match a date or time part in str. For the specifiers that can be used in format, see the DATE_FORMAT() function description.
```
mysql> SELECT STR_TO_DATE('01,5,2013','%d,%m,%Y');
        -> '2013-05-01'
mysql> SELECT STR_TO_DATE('May 1, 2013','%M %d,%Y');
        -> '2013-05-01'
```
Scanning starts at the beginning of str and fails if format is found not to match. Extra characters at the end of str are ignored.
```
mysql> SELECT STR_TO_DATE('a09:30:17','a%h:%i:%s');
        -> '09:30:17'
mysql> SELECT STR_TO_DATE('a09:30:17','%h:%i:%s');
        -> NULL
mysql> SELECT STR_TO_DATE('09:30:17a','%h:%i:%s');
        -> '09:30:17'
```
Unspecified date or time parts have a value of 0, so incompletely specified values in str produce a result with some or all parts set to 0:
```
mysql> SELECT STR_TO_DATE('abc','abc');
        -> '0000-00-00'
mysql> SELECT STR_TO_DATE('9','%m');
        -> '0000-09-00'
mysql> SELECT STR_TO_DATE('9','%s');
        -> '00:00:09'
```
Range checking on the parts of date values is as described in Section 11.3.1, “The DATE, DATETIME, and TIMESTAMP Types”. This means, for example, that “zero” dates or dates with part values of 0 are permitted unless the SQL mode is set to disallow such values.
```
mysql> SELECT STR_TO_DATE('00/00/0000', '%m/%d/%Y');
        -> '0000-00-00'
mysql> SELECT STR_TO_DATE('04/31/2004', '%m/%d/%Y');
        -> '2004-04-31'
```
If the NO_ZERO_DATE or NO_ZERO_IN_DATE SQL mode is enabled, zero dates or part of dates are disallowed. In that case, STR_TO_DATE() returns NULL and generates a warning:
```
mysql> SET sql_mode = '';
mysql> SELECT STR_TO_DATE('15:35:00', '%H:%i:%s');
+-------------------------------------+
| STR_TO_DATE('15:35:00', '%H:%i:%s') |
+-------------------------------------+
| 15:35:00                            |
+-------------------------------------+
mysql> SET sql_mode = 'NO_ZERO_IN_DATE';
mysql> SELECT STR_TO_DATE('15:35:00', '%h:%i:%s');
+-------------------------------------+
| STR_TO_DATE('15:35:00', '%h:%i:%s') |
+-------------------------------------+
| NULL                                |
+-------------------------------------+
mysql> SHOW WARNINGS\G
*************************** 1. row ***************************
  Level: Warning
   Code: 1411
Message: Incorrect datetime value: '15:35:00' for function str_to_date
```
Note

You cannot use format "%X%V" to convert a year-week string to a date because the combination of a year and week does not uniquely identify a year and month if the week crosses a month boundary. To convert a year-week to a date, you should also specify the weekday:
```
mysql> SELECT STR_TO_DATE('200442 Monday', '%X%V %W');
        -> '2004-10-18'
```
SUBDATE(date,INTERVAL expr unit), SUBDATE(expr,days)
When invoked with the INTERVAL form of the second argument, SUBDATE() is a synonym for DATE_SUB(). For information on the INTERVAL unit argument, see the discussion for DATE_ADD().
```
mysql> SELECT DATE_SUB('2008-01-02', INTERVAL 31 DAY);
        -> '2007-12-02'
mysql> SELECT SUBDATE('2008-01-02', INTERVAL 31 DAY);
        -> '2007-12-02'
```
The second form enables the use of an integer value for days. In such cases, it is interpreted as the number of days to be subtracted from the date or datetime expression expr.
```
mysql> SELECT SUBDATE('2008-01-02 12:00:00', 31);
        -> '2007-12-02 12:00:00'
```

SUBTIME(expr1,expr2)

SUBTIME() returns expr1 − expr2 expressed as a value in the same format as expr1. expr1 is a time or datetime expression, and expr2 is a time expression.

mysql> SELECT SUBTIME('2007-12-31 23:59:59.999999','1 1:1:1.000002');
        -> '2007-12-30 22:58:58.999997'
mysql> SELECT SUBTIME('01:00:00.999999', '02:00:00.999998');
        -> '-00:59:59.999999'

SYSDATE([fsp])
Returns the current date and time as a value in 'YYYY-MM-DD HH:MM:SS' or YYYYMMDDHHMMSS format, depending on whether the function is used in a string or numeric context.
If the fsp argument is given to specify a fractional seconds precision from 0 to 6, the return value includes a fractional seconds part of that many digits.
SYSDATE() returns the time at which it executes. This differs from the behavior for NOW(), which returns a constant time that indicates the time at which the statement began to execute. (Within a stored function or trigger, NOW() returns the time at which the function or triggering statement began to execute.)
```
mysql> SELECT NOW(), SLEEP(2), NOW();
+---------------------+----------+---------------------+
| NOW()               | SLEEP(2) | NOW()               |
+---------------------+----------+---------------------+
| 2006-04-12 13:47:36 |        0 | 2006-04-12 13:47:36 |
+---------------------+----------+---------------------+

mysql> SELECT SYSDATE(), SLEEP(2), SYSDATE();
+---------------------+----------+---------------------+
| SYSDATE()           | SLEEP(2) | SYSDATE()           |
+---------------------+----------+---------------------+
| 2006-04-12 13:47:44 |        0 | 2006-04-12 13:47:46 |
+---------------------+----------+---------------------+
```
In addition, the SET TIMESTAMP statement affects the value returned by NOW() but not by SYSDATE(). This means that timestamp settings in the binary log have no effect on invocations of SYSDATE().
Because SYSDATE() can return different values even within the same statement, and is not affected by SET TIMESTAMP, it is nondeterministic and therefore unsafe for replication if statement-based binary logging is used. If that is a problem, you can use row-based logging.
Alternatively, you can use the --sysdate-is-now option to cause SYSDATE() to be an alias for NOW(). This works if the option is used on both the master and the slave.
The nondeterministic nature of SYSDATE() also means that indexes cannot be used for evaluating expressions that refer to it.
TIME(expr)
Extracts the time part of the time or datetime expression expr and returns it as a string.
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
```
mysql> SELECT TIME('2003-12-31 01:02:03');
        -> '01:02:03'
mysql> SELECT TIME('2003-12-31 01:02:03.000123');
        -> '01:02:03.000123'
```
TIMEDIFF(expr1,expr2)
TIMEDIFF() returns expr1 − expr2 expressed as a time value. expr1 and expr2 are time or date-and-time expressions, but both must be of the same type.
The result returned by TIMEDIFF() is limited to the range allowed for TIME values. Alternatively, you can use either of the functions TIMESTAMPDIFF() and UNIX_TIMESTAMP(), both of which return integers.
```
mysql> SELECT TIMEDIFF('2000:01:01 00:00:00',
    ->                 '2000:01:01 00:00:00.000001');
        -> '-00:00:00.000001'
mysql> SELECT TIMEDIFF('2008-12-31 23:59:59.000001',
    ->                 '2008-12-30 01:01:01.000002');
        -> '46:58:57.999999'
```
TIMESTAMP(expr), TIMESTAMP(expr1,expr2)
With a single argument, this function returns the date or datetime expression expr as a datetime value. With two arguments, it adds the time expression expr2 to the date or datetime expression expr1 and returns the result as a datetime value.
```
mysql> SELECT TIMESTAMP('2003-12-31');
        -> '2003-12-31 00:00:00'
mysql> SELECT TIMESTAMP('2003-12-31 12:00:00','12:00:00');
        -> '2004-01-01 00:00:00'
```
TIMESTAMPADD(unit,interval,datetime_expr)
Adds the integer expression interval to the date or datetime expression datetime_expr. The unit for interval is given by the unit argument, which should be one of the following values: MICROSECOND (microseconds), SECOND, MINUTE, HOUR, DAY, WEEK, MONTH, QUARTER, or YEAR.
The unit value may be specified using one of keywords as shown, or with a prefix of SQL_TSI_. For example, DAY and SQL_TSI_DAY both are legal.
```
mysql> SELECT TIMESTAMPADD(MINUTE,1,'2003-01-02');
        -> '2003-01-02 00:01:00'
mysql> SELECT TIMESTAMPADD(WEEK,1,'2003-01-02');
        -> '2003-01-09'
```
TIMESTAMPDIFF(unit,datetime_expr1,datetime_expr2)
Returns datetime_expr2 − datetime_expr1, where datetime_expr1 and datetime_expr2 are date or datetime expressions. One expression may be a date and the other a datetime; a date value is treated as a datetime having the time part '00:00:00' where necessary. The unit for the result (an integer) is given by the unit argument. The legal values for unit are the same as those listed in the description of the TIMESTAMPADD() function.
```
mysql> SELECT TIMESTAMPDIFF(MONTH,'2003-02-01','2003-05-01');
        -> 3
mysql> SELECT TIMESTAMPDIFF(YEAR,'2002-05-01','2001-01-01');
        -> -1
mysql> SELECT TIMESTAMPDIFF(MINUTE,'2003-02-01','2003-05-01 12:05:55');
        -> 128885
```
Note

The order of the date or datetime arguments for this function is the opposite of that used with the TIMESTAMP() function when invoked with 2 arguments.
TIME_FORMAT(time,format)
This is used like the DATE_FORMAT() function, but the format string may contain format specifiers only for hours, minutes, seconds, and microseconds. Other specifiers produce a NULL value or 0.
If the time value contains an hour part that is greater than 23, the %H and %k hour format specifiers produce a value larger than the usual range of 0..23. The other hour format specifiers produce the hour value modulo 12.
```
mysql> SELECT TIME_FORMAT('100:00:00', '%H %k %h %I %l');
        -> '100 100 04 04 4'
```

TIME_TO_SEC(time)

Returns the time argument, converted to seconds.

mysql> SELECT TIME_TO_SEC('22:23:00');
        -> 80580
mysql> SELECT TIME_TO_SEC('00:39:38');
        -> 2378

TO_DAYS(date)
Given a date date, returns a day number (the number of days since year 0).
```
mysql> SELECT TO_DAYS(950501);
        -> 728779
mysql> SELECT TO_DAYS('2007-10-07');
        -> 733321
```
TO_DAYS() is not intended for use with values that precede the advent of the Gregorian calendar (1582), because it does not take into account the days that were lost when the calendar was changed. For dates before 1582 (and possibly a later year in other locales), results from this function are not reliable. See Section 12.8, “What Calendar Is Used By MySQL?”, for details.
Remember that MySQL converts two-digit year values in dates to four-digit form using the rules in Section 11.3, “Date and Time Types”. For example, '2008-10-07' and '08-10-07' are seen as identical dates:
```
mysql> SELECT TO_DAYS('2008-10-07'), TO_DAYS('08-10-07');
        -> 733687, 733687
```
In MySQL, the zero date is defined as '0000-00-00', even though this date is itself considered invalid. This means that, for '0000-00-00' and '0000-01-01', TO_DAYS() returns the values shown here:
```
mysql> SELECT TO_DAYS('0000-00-00');
+-----------------------+
| to_days('0000-00-00') |
+-----------------------+
|                  NULL |
+-----------------------+
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS;
+---------+------+----------------------------------------+
| Level   | Code | Message                                |
+---------+------+----------------------------------------+
| Warning | 1292 | Incorrect datetime value: '0000-00-00' |
+---------+------+----------------------------------------+
1 row in set (0.00 sec)


mysql> SELECT TO_DAYS('0000-01-01');
+-----------------------+
| to_days('0000-01-01') |
+-----------------------+
|                     1 |
+-----------------------+
1 row in set (0.00 sec)
```
This is true whether or not the ALLOW_INVALID_DATES SQL server mode is enabled.

TO_SECONDS(expr)

Given a date or datetime expr, returns the number of seconds since the year 0. If expr is not a valid date or datetime value, returns NULL.

mysql> SELECT TO_SECONDS(950501);
        -> 62966505600
mysql> SELECT TO_SECONDS('2009-11-29');
        -> 63426672000
mysql> SELECT TO_SECONDS('2009-11-29 13:43:32');
        -> 63426721412
mysql> SELECT TO_SECONDS( NOW() );
        -> 63426721458

Like TO_DAYS(), TO_SECONDS() is not intended for use with values that precede the advent of the Gregorian calendar (1582), because it does not take into account the days that were lost when the calendar was changed. For dates before 1582 (and possibly a later year in other locales), results from this function are not reliable. See Section 12.8, “What Calendar Is Used By MySQL?”, for details.

Like TO_DAYS(), TO_SECONDS(), converts two-digit year values in dates to four-digit form using the rules in Section 11.3, “Date and Time Types”.

In MySQL, the zero date is defined as '0000-00-00', even though this date is itself considered invalid. This means that, for '0000-00-00' and '0000-01-01', TO_SECONDS() returns the values shown here:

mysql> SELECT TO_SECONDS('0000-00-00');
+--------------------------+
| TO_SECONDS('0000-00-00') |
+--------------------------+
|                     NULL |
+--------------------------+
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS;
+---------+------+----------------------------------------+
| Level   | Code | Message                                |
+---------+------+----------------------------------------+
| Warning | 1292 | Incorrect datetime value: '0000-00-00' |
+---------+------+----------------------------------------+
1 row in set (0.00 sec)


mysql> SELECT TO_SECONDS('0000-01-01');
+--------------------------+
| TO_SECONDS('0000-01-01') |
+--------------------------+
|                    86400 |
+--------------------------+
1 row in set (0.00 sec)

This is true whether or not the ALLOW_INVALID_DATES SQL server mode is enabled.

UNIX_TIMESTAMP(), UNIX_TIMESTAMP(date)
If called with no argument, returns a Unix timestamp (seconds since '1970-01-01 00:00:00' UTC). The return value is an integer if no argument is given or the argument does not include a fractional seconds part, or DECIMAL if an argument is given that includes a fractional seconds part.
If UNIX_TIMESTAMP() is called with a date argument, it returns the value of the argument as seconds since '1970-01-01 00:00:00' UTC. The date argument may be a DATE, DATETIME, or TIMESTAMP string, or a number in YYMMDD, YYMMDDHHMMSS, YYYYMMDD, or YYYYMMDDHHMMSS format. If the argument includes a time part, it may optionally include a fractional seconds part. The server interprets date as a value in the current time zone and converts it to an internal value in UTC. Clients can set their time zone as described in Section 5.1.12, “MySQL Server Time Zone Support”.
```
mysql> SELECT UNIX_TIMESTAMP();
        -> 1447431666
mysql> SELECT UNIX_TIMESTAMP('2015-11-13 10:20:19');
        -> 1447431619
mysql> SELECT UNIX_TIMESTAMP('2015-11-13 10:20:19.012');
        -> 1447431619.012
```
When UNIX_TIMESTAMP() is used on a TIMESTAMP column, the function returns the internal timestamp value directly, with no implicit “string-to-Unix-timestamp” conversion. If you pass an out-of-range date to UNIX_TIMESTAMP(), it returns 0. The valid range of values is the same as for the TIMESTAMP data type: '1970-01-01 00:00:01.000000' UTC to '2038-01-19 03:14:07.999999' UTC.
Note: If you use UNIX_TIMESTAMP() and FROM_UNIXTIME() to convert between TIMESTAMP values and Unix timestamp values, the conversion is lossy because the mapping is not one-to-one in both directions. For example, due to conventions for local time zone changes, it is possible for two UNIX_TIMESTAMP() to map two TIMESTAMP values to the same Unix timestamp value. FROM_UNIXTIME() will map that value back to only one of the original TIMESTAMP values. Here is an example, using TIMESTAMP values in the CET time zone:
```
mysql> SELECT UNIX_TIMESTAMP('2005-03-27 03:00:00');
+---------------------------------------+
| UNIX_TIMESTAMP('2005-03-27 03:00:00') |
+---------------------------------------+
|                            1111885200 |
+---------------------------------------+
mysql> SELECT UNIX_TIMESTAMP('2005-03-27 02:00:00');
+---------------------------------------+
| UNIX_TIMESTAMP('2005-03-27 02:00:00') |
+---------------------------------------+
|                            1111885200 |
+---------------------------------------+
mysql> SELECT FROM_UNIXTIME(1111885200);
+---------------------------+
| FROM_UNIXTIME(1111885200) |
+---------------------------+
| 2005-03-27 03:00:00       |
+---------------------------+
```
If you want to subtract UNIX_TIMESTAMP() columns, you might want to cast the result to signed integers. See Section 12.10, “Cast Functions and Operators”.
UTC_DATE, UTC_DATE()
Returns the current UTC date as a value in 'YYYY-MM-DD' or YYYYMMDD format, depending on whether the function is used in a string or numeric context.
```
mysql> SELECT UTC_DATE(), UTC_DATE() + 0;
        -> '2003-08-14', 20030814
```
UTC_TIME, UTC_TIME([fsp])
Returns the current UTC time as a value in 'HH:MM:SS' or HHMMSS format, depending on whether the function is used in a string or numeric context.
If the fsp argument is given to specify a fractional seconds precision from 0 to 6, the return value includes a fractional seconds part of that many digits.
```
mysql> SELECT UTC_TIME(), UTC_TIME() + 0;
        -> '18:07:53', 180753.000000
```
UTC_TIMESTAMP, UTC_TIMESTAMP([fsp])
Returns the current UTC date and time as a value in 'YYYY-MM-DD HH:MM:SS' or YYYYMMDDHHMMSS format, depending on whether the function is used in a string or numeric context.
If the fsp argument is given to specify a fractional seconds precision from 0 to 6, the return value includes a fractional seconds part of that many digits.
```
mysql> SELECT UTC_TIMESTAMP(), UTC_TIMESTAMP() + 0;
        -> '2003-08-14 18:08:04', 20030814180804.000000
```

WEEK(date[,mode])

This function returns the week number for date. The two-argument form of WEEK() enables you to specify whether the week starts on Sunday or Monday and whether the return value should be in the range from 0 to 53 or from 1 to 53. If the mode argument is omitted, the value of the default_week_format system variable is used. See Section 5.1.7, “Server System Variables”.

The following table describes how the mode argument works.

Mode	First day of week	Range	Week 1 is the first week …
0	Sunday	0-53	with a Sunday in this year
1	Monday	0-53	with 4 or more days this year
2	Sunday	1-53	with a Sunday in this year
3	Monday	1-53	with 4 or more days this year
4	Sunday	0-53	with 4 or more days this year
5	Monday	0-53	with a Monday in this year
6	Sunday	1-53	with 4 or more days this year
7	Monday	1-53	with a Monday in this year

For mode values with a meaning of “with 4 or more days this year,” weeks are numbered according to ISO 8601:1988:

If the week containing January 1 has 4 or more days in the new year, it is week 1.
Otherwise, it is the last week of the previous year, and the next week is week 1.

mysql> SELECT WEEK('2008-02-20');
        -> 7
mysql> SELECT WEEK('2008-02-20',0);
        -> 7
mysql> SELECT WEEK('2008-02-20',1);
        -> 8
mysql> SELECT WEEK('2008-12-31',1);
        -> 53

Note that if a date falls in the last week of the previous year, MySQL returns 0 if you do not use 2, 3, 6, or 7 as the optional mode argument:

mysql> SELECT YEAR('2000-01-01'), WEEK('2000-01-01',0);
        -> 2000, 0

One might argue that WEEK() should return 52 because the given date actually occurs in the 52nd week of 1999. WEEK() returns 0 instead so that the return value is “the week number in the given year.” This makes use of the WEEK() function reliable when combined with other functions that extract a date part from a date.

If you prefer a result evaluated with respect to the year that contains the first day of the week for the given date, use 0, 2, 5, or 7 as the optional mode argument.

mysql> SELECT WEEK('2000-01-01',2);
        -> 52

Alternatively, use the YEARWEEK() function:

mysql> SELECT YEARWEEK('2000-01-01');
        -> 199952
mysql> SELECT MID(YEARWEEK('2000-01-01'),5,2);
        -> '52'

WEEKDAY(date)

Returns the weekday index for date (0 = Monday, 1 = Tuesday, … 6 = Sunday).

mysql> SELECT WEEKDAY('2008-02-03 22:23:00');
        -> 6
mysql> SELECT WEEKDAY('2007-11-06');
        -> 1

WEEKOFYEAR(date)
Returns the calendar week of the date as a number in the range from 1 to 53. WEEKOFYEAR() is a compatibility function that is equivalent to WEEK(date,3).
```
mysql> SELECT WEEKOFYEAR('2008-02-20');
        -> 8
```
YEAR(date)
Returns the year for date, in the range 1000 to 9999, or 0 for the “zero” date.
```
mysql> SELECT YEAR('1987-01-01');
        -> 1987
```
YEARWEEK(date), YEARWEEK(date,mode)
Returns year and week for a date. The year in the result may be different from the year in the date argument for the first and the last week of the year.
The mode argument works exactly like the mode argument to WEEK(). For the single-argument syntax, a mode value of 0 is used. Unlike WEEK(), the value of default_week_format does not influence YEARWEEK().
```
mysql> SELECT YEARWEEK('1987-01-01');
        -> 198652
```
Note that the week number is different from what the WEEK() function would return (0) for optional arguments 0 or 1, as WEEK() then returns the week in the context of the given year.

12.8 What Calendar Is Used By MySQL?

MySQL uses what is known as a proleptic Gregorian calendar.

Every country that has switched from the Julian to the Gregorian calendar has had to discard at least ten days during the switch. To see how this works, consider the month of October 1582, when the first Julian-to-Gregorian switch occurred.

Monday	Tuesday	Wednesday	Thursday	Friday	Saturday	Sunday
1	2	3	4	15	16	17
18	19	20	21	22	23	24
25	26	27	28	29	30	31

There are no dates between October 4 and October 15. This discontinuity is called the cutover. Any dates before the cutover are Julian, and any dates following the cutover are Gregorian. Dates during a cutover are nonexistent.

A calendar applied to dates when it was not actually in use is called proleptic. Thus, if we assume there was never a cutover and Gregorian rules always rule, we have a proleptic Gregorian calendar. This is what is used by MySQL, as is required by standard SQL. For this reason, dates prior to the cutover stored as MySQL DATE or DATETIME values must be adjusted to compensate for the difference. It is important to realize that the cutover did not occur at the same time in all countries, and that the later it happened, the more days were lost. For example, in Great Britain, it took place in 1752, when Wednesday September 2 was followed by Thursday September 14. Russia remained on the Julian calendar until 1918, losing 13 days in the process, and what is popularly referred to as its “October Revolution” occurred in November according to the Gregorian calendar.

12.9 Full-Text Search Functions

12.9.1 Natural Language Full-Text Searches
12.9.2 Boolean Full-Text Searches
12.9.3 Full-Text Searches with Query Expansion
12.9.4 Full-Text Stopwords
12.9.5 Full-Text Restrictions
12.9.6 Fine-Tuning MySQL Full-Text Search
12.9.7 Adding a Collation for Full-Text Indexing
12.9.8 ngram Full-Text Parser
12.9.9 MeCab Full-Text Parser Plugin

MATCH (col1,col2,...) AGAINST (expr [search_modifier])

search_modifier:
  {
       IN NATURAL LANGUAGE MODE
     | IN NATURAL LANGUAGE MODE WITH QUERY EXPANSION
     | IN BOOLEAN MODE
     | WITH QUERY EXPANSION
  }

MySQL has support for full-text indexing and searching:

A full-text index in MySQL is an index of type FULLTEXT.
Full-text indexes can be used only with InnoDB or MyISAM tables, and can be created only for CHAR, VARCHAR, or TEXT columns.
MySQL provides a built-in full-text ngram parser that supports Chinese, Japanese, and Korean (CJK), and an installable MeCab full-text parser plugin for Japanese. Parsing differences are outlined in Section 12.9.8, “ngram Full-Text Parser”, and Section 12.9.9, “MeCab Full-Text Parser Plugin”.
A FULLTEXT index definition can be given in the CREATE TABLE statement when a table is created, or added later using ALTER TABLE or CREATE INDEX.
For large data sets, it is much faster to load your data into a table that has no FULLTEXT index and then create the index after that, than to load data into a table that has an existing FULLTEXT index.

Full-text searching is performed using MATCH() ... AGAINST syntax. MATCH() takes a comma-separated list that names the columns to be searched. AGAINST takes a string to search for, and an optional modifier that indicates what type of search to perform. The search string must be a string value that is constant during query evaluation. This rules out, for example, a table column because that can differ for each row.

There are three types of full-text searches:

A natural language search interprets the search string as a phrase in natural human language (a phrase in free text). There are no special operators, with the exception of double quote (") characters. The stopword list applies. For more information about stopword lists, see Section 12.9.4, “Full-Text Stopwords”.
Full-text searches are natural language searches if the IN NATURAL LANGUAGE MODE modifier is given or if no modifier is given. For more information, see Section 12.9.1, “Natural Language Full-Text Searches”.
A boolean search interprets the search string using the rules of a special query language. The string contains the words to search for. It can also contain operators that specify requirements such that a word must be present or absent in matching rows, or that it should be weighted higher or lower than usual. Certain common words (stopwords) are omitted from the search index and do not match if present in the search string. The IN BOOLEAN MODE modifier specifies a boolean search. For more information, see Section 12.9.2, “Boolean Full-Text Searches”.
A query expansion search is a modification of a natural language search. The search string is used to perform a natural language search. Then words from the most relevant rows returned by the search are added to the search string and the search is done again. The query returns the rows from the second search. The IN NATURAL LANGUAGE MODE WITH QUERY EXPANSION or WITH QUERY EXPANSION modifier specifies a query expansion search. For more information, see Section 12.9.3, “Full-Text Searches with Query Expansion”.

For information about FULLTEXT query performance, see Section 8.3.5, “Column Indexes”.

For more information about InnoDB FULLTEXT indexes, see Section 15.8.2.4, “InnoDB FULLTEXT Indexes”.

Constraints on full-text searching are listed in Section 12.9.5, “Full-Text Restrictions”.

The myisam_ftdump utility dumps the contents of a MyISAM full-text index. This may be helpful for debugging full-text queries. See Section 4.6.3, “myisam_ftdump — Display Full-Text Index information”.

12.9.1 Natural Language Full-Text Searches

By default or with the IN NATURAL LANGUAGE MODE modifier, the MATCH() function performs a natural language search for a string against a text collection. A collection is a set of one or more columns included in a FULLTEXT index. The search string is given as the argument to AGAINST(). For each row in the table, MATCH() returns a relevance value; that is, a similarity measure between the search string and the text in that row in the columns named in the MATCH() list.

mysql> CREATE TABLE articles (
          id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
          title VARCHAR(200),
          body TEXT,
          FULLTEXT (title,body)
        ) ENGINE=InnoDB;
Query OK, 0 rows affected (0.08 sec)

mysql> INSERT INTO articles (title,body) VALUES
        ('MySQL Tutorial','DBMS stands for DataBase ...'),
        ('How To Use MySQL Well','After you went through a ...'),
        ('Optimizing MySQL','In this tutorial we will show ...'),
        ('1001 MySQL Tricks','1. Never run mysqld as root. 2. ...'),
        ('MySQL vs. YourSQL','In the following database comparison ...'),
        ('MySQL Security','When configured properly, MySQL ...');
Query OK, 6 rows affected (0.01 sec)
Records: 6  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM articles
        WHERE MATCH (title,body)
        AGAINST ('database' IN NATURAL LANGUAGE MODE);
+----+-------------------+------------------------------------------+
| id | title             | body                                     |
+----+-------------------+------------------------------------------+
|  1 | MySQL Tutorial    | DBMS stands for DataBase ...             |
|  5 | MySQL vs. YourSQL | In the following database comparison ... |
+----+-------------------+------------------------------------------+
2 rows in set (0.00 sec)

By default, the search is performed in case-insensitive fashion. To perform a case-sensitive full-text search, use a case-sensitive or binary collation for the indexed columns. For example, a column that uses the utf8mb4 character set of can be assigned a collation of utf8mb4_0900_as_cs or utf8mb4_bin to make it case-sensitive for full-text searches.

When MATCH() is used in a WHERE clause, as in the example shown earlier, the rows returned are automatically sorted with the highest relevance first. Relevance values are nonnegative floating-point numbers. Zero relevance means no similarity. Relevance is computed based on the number of words in the row (document), the number of unique words in the row, the total number of words in the collection, and the number of rows that contain a particular word.

Note

The term “document” may be used interchangeably with the term “row”, and both terms refer to the indexed part of the row. The term “collection” refers to the indexed columns and encompasses all rows.

To simply count matches, you could use a query like this:

mysql> SELECT COUNT(*) FROM articles
    WHERE MATCH (title,body)
    AGAINST ('database' IN NATURAL LANGUAGE MODE);
+----------+
| COUNT(*) |
+----------+
|        2 |
+----------+
1 row in set (0.00 sec)

You might find it quicker to rewrite the query as follows:

mysql> SELECT
    COUNT(IF(MATCH (title,body) AGAINST ('database' IN NATURAL LANGUAGE MODE), 1, NULL))
    AS count
    FROM articles;
+-------+
| count |
+-------+
|     2 |
+-------+
1 row in set (0.03 sec)

The first query does some extra work (sorting the results by relevance) but also can use an index lookup based on the WHERE clause. The index lookup might make the first query faster if the search matches few rows. The second query performs a full table scan, which might be faster than the index lookup if the search term was present in most rows.

For natural-language full-text searches, the columns named in the MATCH() function must be the same columns included in some FULLTEXT index in your table. For the preceding query, note that the columns named in the MATCH() function (title and body) are the same as those named in the definition of the article table's FULLTEXT index. To search the title or body separately, you would create separate FULLTEXT indexes for each column.

You can also perform a boolean search or a search with query expansion. These search types are described in Section 12.9.2, “Boolean Full-Text Searches”, and Section 12.9.3, “Full-Text Searches with Query Expansion”.

A full-text search that uses an index can name columns only from a single table in the MATCH() clause because an index cannot span multiple tables. For MyISAM tables, a boolean search can be done in the absence of an index (albeit more slowly), in which case it is possible to name columns from multiple tables.

The preceding example is a basic illustration that shows how to use the MATCH() function where rows are returned in order of decreasing relevance. The next example shows how to retrieve the relevance values explicitly. Returned rows are not ordered because the SELECT statement includes neither WHERE nor ORDER BY clauses:

mysql> SELECT id, MATCH (title,body)
    AGAINST ('Tutorial' IN NATURAL LANGUAGE MODE) AS score
    FROM articles;
+----+---------------------+
| id | score               |
+----+---------------------+
|  1 | 0.22764469683170319 |
|  2 |                   0 |
|  3 | 0.22764469683170319 |
|  4 |                   0 |
|  5 |                   0 |
|  6 |                   0 |
+----+---------------------+
6 rows in set (0.00 sec)

The following example is more complex. The query returns the relevance values and it also sorts the rows in order of decreasing relevance. To achieve this result, specify MATCH() twice: once in the SELECT list and once in the WHERE clause. This causes no additional overhead, because the MySQL optimizer notices that the two MATCH() calls are identical and invokes the full-text search code only once.

mysql> SELECT id, body, MATCH (title,body) AGAINST
    ('Security implications of running MySQL as root'
    IN NATURAL LANGUAGE MODE) AS score
    FROM articles WHERE MATCH (title,body) AGAINST
    ('Security implications of running MySQL as root'
    IN NATURAL LANGUAGE MODE);
+----+-------------------------------------+-----------------+
| id | body                                | score           |
+----+-------------------------------------+-----------------+
|  4 | 1. Never run mysqld as root. 2. ... | 1.5219271183014 |
|  6 | When configured properly, MySQL ... | 1.3114095926285 |
+----+-------------------------------------+-----------------+
2 rows in set (0.00 sec)

A phrase that is enclosed within double quote (") characters matches only rows that contain the phrase literally, as it was typed. The full-text engine splits the phrase into words and performs a search in the FULLTEXT index for the words. Nonword characters need not be matched exactly: Phrase searching requires only that matches contain exactly the same words as the phrase and in the same order. For example, "test phrase" matches "test, phrase". If the phrase contains no words that are in the index, the result is empty. For example, if all words are either stopwords or shorter than the minimum length of indexed words, the result is empty.

The MySQL FULLTEXT implementation regards any sequence of true word characters (letters, digits, and underscores) as a word. That sequence may also contain apostrophes ('), but not more than one in a row. This means that aaa'bbb is regarded as one word, but aaa''bbb is regarded as two words. Apostrophes at the beginning or the end of a word are stripped by the FULLTEXT parser; 'aaa'bbb' would be parsed as aaa'bbb.

The built-in FULLTEXT parser determines where words start and end by looking for certain delimiter characters; for example, (space), , (comma), and . (period). If words are not separated by delimiters (as in, for example, Chinese), the built-in FULLTEXT parser cannot determine where a word begins or ends. To be able to add words or other indexed terms in such languages to a FULLTEXT index that uses the built-in FULLTEXT parser, you must preprocess them so that they are separated by some arbitrary delimiter. Alternatively, you can create FULLTEXT indexes using the ngram parser plugin (for Chinese, Japanese, or Korean) or the MeCab parser plugin (for Japanese).

It is possible to write a plugin that replaces the built-in full-text parser. For details, see Section 28.2, “The MySQL Plugin API”. For example parser plugin source code, see the plugin/fulltext directory of a MySQL source distribution.

Some words are ignored in full-text searches:

Any word that is too short is ignored. The default minimum length of words that are found by full-text searches is three characters for InnoDB search indexes, or four characters for MyISAM. You can control the cutoff by setting a configuration option before creating the index: innodb_ft_min_token_size configuration option for InnoDB search indexes, or ft_min_word_len for MyISAM.

Note

This behavior does not apply to FULLTEXT indexes that use the ngram parser. For the ngram parser, token length is defined by the ngram_token_size option.
Words in the stopword list are ignored. A stopword is a word such as “the” or “some” that is so common that it is considered to have zero semantic value. There is a built-in stopword list, but it can be overridden by a user-defined list. The stopword lists and related configuration options are different for InnoDB search indexes and MyISAM ones. Stopword processing is controlled by the configuration options innodb_ft_enable_stopword, innodb_ft_server_stopword_table, and innodb_ft_user_stopword_table for InnoDB search indexes, and ft_stopword_file for MyISAM ones.

See Section 12.9.4, “Full-Text Stopwords” to view default stopword lists and how to change them. The default minimum word length can be changed as described in Section 12.9.6, “Fine-Tuning MySQL Full-Text Search”.

Every correct word in the collection and in the query is weighted according to its significance in the collection or query. Thus, a word that is present in many documents has a lower weight, because it has lower semantic value in this particular collection. Conversely, if the word is rare, it receives a higher weight. The weights of the words are combined to compute the relevance of the row. This technique works best with large collections.

MyISAM Limitation

For very small tables, word distribution does not adequately reflect their semantic value, and this model may sometimes produce bizarre results for search indexes on MyISAM tables. For example, although the word “MySQL” is present in every row of the articles table shown earlier, a search for the word in a MyISAM search index produces no results:

mysql> SELECT * FROM articles
    WHERE MATCH (title,body)
    AGAINST ('MySQL' IN NATURAL LANGUAGE MODE);
Empty set (0.00 sec)

The search result is empty because the word “MySQL” is present in at least 50% of the rows, and so is effectively treated as a stopword. This filtering technique is more suitable for large data sets, where you might not want the result set to return every second row from a 1GB table, than for small data sets where it might cause poor results for popular terms.

The 50% threshold can surprise you when you first try full-text searching to see how it works, and makes InnoDB tables more suited to experimentation with full-text searches. If you create a MyISAM table and insert only one or two rows of text into it, every word in the text occurs in at least 50% of the rows. As a result, no search returns any results until the table contains more rows. Users who need to bypass the 50% limitation can build search indexes on InnoDB tables, or use the boolean search mode explained in Section 12.9.2, “Boolean Full-Text Searches”.

12.9.2 Boolean Full-Text Searches

MySQL can perform boolean full-text searches using the IN BOOLEAN MODE modifier. With this modifier, certain characters have special meaning at the beginning or end of words in the search string. In the following query, the + and - operators indicate that a word must be present or absent, respectively, for a match to occur. Thus, the query retrieves all the rows that contain the word “MySQL” but that do not contain the word “YourSQL”:

mysql> SELECT * FROM articles WHERE MATCH (title,body)
    AGAINST ('+MySQL -YourSQL' IN BOOLEAN MODE);
+----+-----------------------+-------------------------------------+
| id | title                 | body                                |
+----+-----------------------+-------------------------------------+
|  1 | MySQL Tutorial        | DBMS stands for DataBase ...        |
|  2 | How To Use MySQL Well | After you went through a ...        |
|  3 | Optimizing MySQL      | In this tutorial we will show ...   |
|  4 | 1001 MySQL Tricks     | 1. Never run mysqld as root. 2. ... |
|  6 | MySQL Security        | When configured properly, MySQL ... |
+----+-----------------------+-------------------------------------+

Note

In implementing this feature, MySQL uses what is sometimes referred to as implied Boolean logic, in which

+ stands for AND
- stands for NOT
[no operator] implies OR

Boolean full-text searches have these characteristics:

They do not automatically sort rows in order of decreasing relevance.
InnoDB tables require a FULLTEXT index on all columns of the MATCH() expression to perform boolean queries. Boolean queries against a MyISAM search index can work even without a FULLTEXT index, although a search executed in this fashion would be quite slow.
The minimum and maximum word length full-text parameters apply to FULLTEXT indexes created using the built-in FULLTEXT parser and MeCab parser plugin. innodb_ft_min_token_size and innodb_ft_max_token_size are used for InnoDB search indexes. ft_min_word_len and ft_max_word_len are used for MyISAM search indexes.
Minimum and maximum word length full-text parameters do not apply to FULLTEXT indexes created using the ngram parser. ngram token size is defined by the ngram_token_size option.
The stopword list applies, controlled by innodb_ft_enable_stopword, innodb_ft_server_stopword_table, and innodb_ft_user_stopword_table for InnoDB search indexes, and ft_stopword_file for MyISAM ones.
InnoDB full-text search does not support the use of multiple operators on a single search word, as in this example: '++apple'. Use of multiple operators on a single search word returns a syntax error to standard out. MyISAM full-text search will successfully process the same search ignoring all operators except for the operator immediately adjacent to the search word.
InnoDB full-text search only supports leading plus or minus signs. For example, InnoDB supports '+apple' but does not support 'apple+'. Specifying a trailing plus or minus sign causes InnoDB to report a syntax error.
InnoDB full-text search does not support the use of a leading plus sign with wildcard ('+*'), a plus and minus sign combination ('+-'), or leading a plus and minus sign combination ('+-apple'). These invalid queries return a syntax error.
InnoDB full-text search does not support the use of the @ symbol in boolean full-text searches. The @ symbol is reserved for use by the @distance proximity search operator.
They do not use the 50% threshold that applies to MyISAM search indexes.

The boolean full-text search capability supports the following operators:

+
A leading or trailing plus sign indicates that this word must be present in each row that is returned. InnoDB only supports leading plus signs.
-
A leading or trailing minus sign indicates that this word must not be present in any of the rows that are returned. InnoDB only supports leading minus signs.
Note: The - operator acts only to exclude rows that are otherwise matched by other search terms. Thus, a boolean-mode search that contains only terms preceded by - returns an empty result. It does not return “all rows except those containing any of the excluded terms.”
(no operator)
By default (when neither + nor - is specified), the word is optional, but the rows that contain it are rated higher. This mimics the behavior of MATCH() ... AGAINST() without the IN BOOLEAN MODE modifier.
@distance
This operator works on InnoDB tables only. It tests whether two or more words all start within a specified distance from each other, measured in words. Specify the search words within a double-quoted string immediately before the @distance operator, for example, MATCH(col1) AGAINST('"word1 word2 word3" @8' IN BOOLEAN MODE)
> <
These two operators are used to change a word's contribution to the relevance value that is assigned to a row. The > operator increases the contribution and the < operator decreases it. See the example following this list.
( )
Parentheses group words into subexpressions. Parenthesized groups can be nested.
~
A leading tilde acts as a negation operator, causing the word's contribution to the row's relevance to be negative. This is useful for marking “noise” words. A row containing such a word is rated lower than others, but is not excluded altogether, as it would be with the - operator.
*
The asterisk serves as the truncation (or wildcard) operator. Unlike the other operators, it is appended to the word to be affected. Words match if they begin with the word preceding the * operator.
If a word is specified with the truncation operator, it is not stripped from a boolean query, even if it is too short or a stopword. Whether a word is too short is determined from the innodb_ft_min_token_size setting for InnoDB tables, or ft_min_word_len for MyISAM tables. These options are not applicable to FULLTEXT indexes that use the ngram parser.
The wildcarded word is considered as a prefix that must be present at the start of one or more words. If the minimum word length is 4, a search for '+word +the*' could return fewer rows than a search for '+word +the', because the second query ignores the too-short search term the.
"
A phrase that is enclosed within double quote (") characters matches only rows that contain the phrase literally, as it was typed. The full-text engine splits the phrase into words and performs a search in the FULLTEXT index for the words. Nonword characters need not be matched exactly: Phrase searching requires only that matches contain exactly the same words as the phrase and in the same order. For example, "test phrase" matches "test, phrase".
If the phrase contains no words that are in the index, the result is empty. The words might not be in the index because of a combination of factors: if they do not exist in the text, are stopwords, or are shorter than the minimum length of indexed words.

The following examples demonstrate some search strings that use boolean full-text operators:

'apple banana'
Find rows that contain at least one of the two words.
'+apple +juice'
Find rows that contain both words.
'+apple macintosh'
Find rows that contain the word “apple”, but rank rows higher if they also contain “macintosh”.
'+apple -macintosh'
Find rows that contain the word “apple” but not “macintosh”.
'+apple ~macintosh'
Find rows that contain the word “apple”, but if the row also contains the word “macintosh”, rate it lower than if row does not. This is “softer” than a search for '+apple -macintosh', for which the presence of “macintosh” causes the row not to be returned at all.
'+apple +(>turnover <strudel)'
Find rows that contain the words “apple” and “turnover”, or “apple” and “strudel” (in any order), but rank “apple turnover” higher than “apple strudel”.
'apple*'
Find rows that contain words such as “apple”, “apples”, “applesauce”, or “applet”.
'"some words"'
Find rows that contain the exact phrase “some words” (for example, rows that contain “some words of wisdom” but not “some noise words”). Note that the " characters that enclose the phrase are operator characters that delimit the phrase. They are not the quotation marks that enclose the search string itself.

Relevancy Rankings for InnoDB Boolean Mode Search

InnoDB full-text search is modeled on the Sphinx full-text search engine, and the algorithms used are based on BM25 and TF-IDF ranking algorithms. For these reasons, relevancy rankings for InnoDB boolean full-text search may differ from MyISAM relevancy rankings.

InnoDB uses a variation of the “term frequency-inverse document frequency” (TF-IDF) weighting system to rank a document's relevance for a given full-text search query. The TF-IDF weighting is based on how frequently a word appears in a document, offset by how frequently the word appears in all documents in the collection. In other words, the more frequently a word appears in a document, and the less frequently the word appears in the document collection, the higher the document is ranked.

How Relevancy Ranking is Calculated

The term frequency (TF) value is the number of times that a word appears in a document. The inverse document frequency (IDF) value of a word is calculated using the following formula, where total_records is the number of records in the collection, and matching_records is the number of records that the search term appears in.

${IDF} = log10( ${total_records} / ${matching_records} )

When a document contains a word multiple times, the IDF value is multiplied by the TF value:

${TF} * ${IDF}

Using the TF and IDF values, the relevancy ranking for a document is calculated using this formula:

${rank} = ${TF} * ${IDF} * ${IDF}

The formula is demonstrated in the following examples.

Relevancy Ranking for a Single Word Search

This example demonstrates the relevancy ranking calculation for a single-word search.

mysql> CREATE TABLE articles (
id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
title VARCHAR(200),
body TEXT,
FULLTEXT (title,body)
) ENGINE=InnoDB;
Query OK, 0 rows affected (1.04 sec)

mysql> INSERT INTO articles (title,body) VALUES
('MySQL Tutorial','This database tutorial ...'),
("How To Use MySQL",'After you went through a ...'),
('Optimizing Your Database','In this database tutorial ...'),
('MySQL vs. YourSQL','When comparing databases ...'),
('MySQL Security','When configured properly, MySQL ...'),
('Database, Database, Database','database database database'),
('1001 MySQL Tricks','1. Never run mysqld as root. 2. ...'),
('MySQL Full-Text Indexes', 'MySQL fulltext indexes use a ..');                  
Query OK, 8 rows affected (0.06 sec)
Records: 8  Duplicates: 0  Warnings: 0

mysql> SELECT id, title, body, MATCH (title,body)  AGAINST ('database' IN BOOLEAN MODE)
AS score FROM articles ORDER BY score DESC;
+----+------------------------------+-------------------------------------+---------------------+
| id | title                        | body                                | score               |
+----+------------------------------+-------------------------------------+---------------------+
|  6 | Database, Database, Database | database database database          |  1.0886961221694946 |
|  3 | Optimizing Your Database     | In this database tutorial ...       | 0.36289870738983154 |
|  1 | MySQL Tutorial               | This database tutorial ...          | 0.18144935369491577 |
|  2 | How To Use MySQL             | After you went through a ...        |                   0 |
|  4 | MySQL vs. YourSQL            | When comparing databases ...        |                   0 |
|  5 | MySQL Security               | When configured properly, MySQL ... |                   0 |
|  7 | 1001 MySQL Tricks            | 1. Never run mysqld as root. 2. ... |                   0 |
|  8 | MySQL Full-Text Indexes      | MySQL fulltext indexes use a ..     |                   0 |
+----+------------------------------+-------------------------------------+---------------------+
8 rows in set (0.00 sec)

There are 8 records in total, with 3 that match the “database” search term. The first record (id 6) contains the search term 6 times and has a relevancy ranking of 1.0886961221694946. This ranking value is calculated using a TF value of 6 (the “database” search term appears 6 times in record id 6) and an IDF value of 0.42596873216370745, which is calculated as follows (where 8 is the total number of records and 3 is the number of records that the search term appears in):

${IDF} = log10( 8 / 3 ) = 0.42596873216370745

The TF and IDF values are then entered into the ranking formula:

${rank} = ${TF} * ${IDF} * ${IDF}

Performing the calculation in the MySQL command-line client returns a ranking value of 1.088696164686938.

mysql> SELECT 6*log10(8/3)*log10(8/3);
+-------------------------+
| 6*log10(8/3)*log10(8/3) |
+-------------------------+
|       1.088696164686938 |
+-------------------------+
1 row in set (0.00 sec)

Note

You may notice a slight difference in the ranking values returned by the SELECT ... MATCH ... AGAINST statement and the MySQL command-line client (1.0886961221694946 versus 1.088696164686938). The difference is due to how the casts between integers and floats/doubles are performed internally by InnoDB (along with related precision and rounding decisions), and how they are performed elsewhere, such as in the MySQL command-line client or other types of calculators.

Relevancy Ranking for a Multiple Word Search

This example demonstrates the relevancy ranking calculation for a multiple-word full-text search based on the articles table and data used in the previous example.

If you search on more than one word, the relevancy ranking value is a sum of the relevancy ranking value for each word, as shown in this formula:

${rank} = ${TF} * ${IDF} * ${IDF} + ${TF} * ${IDF} * ${IDF}

Performing a search on two terms ('mysql tutorial') returns the following results:

mysql> SELECT id, title, body, MATCH (title,body)  AGAINST ('mysql tutorial' IN BOOLEAN MODE)
    AS score FROM articles ORDER BY score DESC;
+----+------------------------------+-------------------------------------+----------------------+
| id | title                        | body                                | score                |
+----+------------------------------+-------------------------------------+----------------------+
|  1 | MySQL Tutorial               | This database tutorial ...          |   0.7405621409416199 |
|  3 | Optimizing Your Database     | In this database tutorial ...       |   0.3624762296676636 |
|  5 | MySQL Security               | When configured properly, MySQL ... | 0.031219376251101494 |
|  8 | MySQL Full-Text Indexes      | MySQL fulltext indexes use a ..     | 0.031219376251101494 |
|  2 | How To Use MySQL             | After you went through a ...        | 0.015609688125550747 |
|  4 | MySQL vs. YourSQL            | When comparing databases ...        | 0.015609688125550747 |
|  7 | 1001 MySQL Tricks            | 1. Never run mysqld as root. 2. ... | 0.015609688125550747 |
|  6 | Database, Database, Database | database database database          |                    0 |
+----+------------------------------+-------------------------------------+----------------------+
8 rows in set (0.00 sec)

In the first record (id 8), 'mysql' appears once and 'tutorial' appears twice. There are six matching records for 'mysql' and two matching records for 'tutorial'. The MySQL command-line client returns the expected ranking value when inserting these values into the ranking formula for a multiple word search:

mysql> SELECT (1*log10(8/6)*log10(8/6)) + (2*log10(8/2)*log10(8/2));
+-------------------------------------------------------+
| (1*log10(8/6)*log10(8/6)) + (2*log10(8/2)*log10(8/2)) |
+-------------------------------------------------------+
|                                    0.7405621541938003 |
+-------------------------------------------------------+
1 row in set (0.00 sec)

Note

The slight difference in the ranking values returned by the SELECT ... MATCH ... AGAINST statement and the MySQL command-line client is explained in the preceding example.

12.9.3 Full-Text Searches with Query Expansion

Full-text search supports query expansion (and in particular, its variant “blind query expansion”). This is generally useful when a search phrase is too short, which often means that the user is relying on implied knowledge that the full-text search engine lacks. For example, a user searching for “database” may really mean that “MySQL”, “Oracle”, “DB2”, and “RDBMS” all are phrases that should match “databases” and should be returned, too. This is implied knowledge.

Blind query expansion (also known as automatic relevance feedback) is enabled by adding WITH QUERY EXPANSION or IN NATURAL LANGUAGE MODE WITH QUERY EXPANSION following the search phrase. It works by performing the search twice, where the search phrase for the second search is the original search phrase concatenated with the few most highly relevant documents from the first search. Thus, if one of these documents contains the word “databases” and the word “MySQL”, the second search finds the documents that contain the word “MySQL” even if they do not contain the word “database”. The following example shows this difference:

mysql> SELECT * FROM articles
    WHERE MATCH (title,body)
    AGAINST ('database' IN NATURAL LANGUAGE MODE);
+----+-------------------+------------------------------------------+
| id | title             | body                                     |
+----+-------------------+------------------------------------------+
|  1 | MySQL Tutorial    | DBMS stands for DataBase ...             |
|  5 | MySQL vs. YourSQL | In the following database comparison ... |
+----+-------------------+------------------------------------------+
2 rows in set (0.00 sec)

mysql> SELECT * FROM articles
    WHERE MATCH (title,body)
    AGAINST ('database' WITH QUERY EXPANSION);
+----+-----------------------+------------------------------------------+
| id | title                 | body                                     |
+----+-----------------------+------------------------------------------+
|  5 | MySQL vs. YourSQL     | In the following database comparison ... |
|  1 | MySQL Tutorial        | DBMS stands for DataBase ...             |
|  3 | Optimizing MySQL      | In this tutorial we will show ...        |
|  6 | MySQL Security        | When configured properly, MySQL ...      |
|  2 | How To Use MySQL Well | After you went through a ...             |
|  4 | 1001 MySQL Tricks     | 1. Never run mysqld as root. 2. ...      |
+----+-----------------------+------------------------------------------+
6 rows in set (0.00 sec)

Another example could be searching for books by Georges Simenon about Maigret, when a user is not sure how to spell “Maigret”. A search for “Megre and the reluctant witnesses” finds only “Maigret and the Reluctant Witnesses” without query expansion. A search with query expansion finds all books with the word “Maigret” on the second pass.

Note

Because blind query expansion tends to increase noise significantly by returning nonrelevant documents, use it only when a search phrase is short.

12.9.4 Full-Text Stopwords

The stopword list is loaded and searched for full-text queries using the server character set and collation (the values of the character_set_server and collation_server system variables). False hits or misses might occur for stopword lookups if the stopword file or columns used for full-text indexing or searches have a character set or collation different from character_set_server or collation_server.

Case sensitivity of stopword lookups depends on the server collation. For example, lookups are case insensitive if the collation is utf8mb4_0900_ai_ci, whereas lookups are case-sensitive if the collation is utf8mb4_0900_as_cs or utf8mb4_bin.

Stopwords for InnoDB Search Indexes

InnoDB has a relatively short list of default stopwords, because documents from technical, literary, and other sources often use short words as keywords or in significant phrases. For example, you might search for “to be or not to be” and expect to get a sensible result, rather than having all those words ignored.

To see the default InnoDB stopword list, query the INFORMATION_SCHEMA.INNODB_FT_DEFAULT_STOPWORD table.

mysql> SELECT * FROM INFORMATION_SCHEMA.INNODB_FT_DEFAULT_STOPWORD;
+-------+
| value |
+-------+
| a     |
| about |
| an    |
| are   |
| as    |
| at    |
| be    |
| by    |
| com   |
| de    |
| en    |
| for   |
| from  |
| how   |
| i     |
| in    |
| is    |
| it    |
| la    |
| of    |
| on    |
| or    |
| that  |
| the   |
| this  |
| to    |
| was   |
| what  |
| when  |
| where |
| who   |
| will  |
| with  |
| und   |
| the   |
| www   |
+-------+
36 rows in set (0.00 sec)

To define your own stopword list for all InnoDB tables, define a table with the same structure as the INNODB_FT_DEFAULT_STOPWORD table, populate it with stopwords, and set the value of the innodb_ft_server_stopword_table option to a value in the form db_name/table_name before creating the full-text index. The stopword table must have a single VARCHAR column named value. The following example demonstrates creating and configuring a new global stopword table for InnoDB.

-- Create a new stopword table

mysql> CREATE TABLE my_stopwords(value VARCHAR(30)) ENGINE = INNODB;
Query OK, 0 rows affected (0.01 sec)

-- Insert stopwords (for simplicity, a single stopword is used in this example)

mysql> INSERT INTO my_stopwords(value) VALUES ('Ishmael');
Query OK, 1 row affected (0.00 sec)

-- Create the table

mysql> CREATE TABLE opening_lines (
id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
opening_line TEXT(500),
author VARCHAR(200),
title VARCHAR(200)
) ENGINE=InnoDB;
Query OK, 0 rows affected (0.01 sec)

-- Insert data into the table

mysql> INSERT INTO opening_lines(opening_line,author,title) VALUES
('Call me Ishmael.','Herman Melville','Moby-Dick'),
('A screaming comes across the sky.','Thomas Pynchon','Gravity\'s Rainbow'),
('I am an invisible man.','Ralph Ellison','Invisible Man'),
('Where now? Who now? When now?','Samuel Beckett','The Unnamable'),
('It was love at first sight.','Joseph Heller','Catch-22'),
('All this happened, more or less.','Kurt Vonnegut','Slaughterhouse-Five'),
('Mrs. Dalloway said she would buy the flowers herself.','Virginia Woolf','Mrs. Dalloway'),
('It was a pleasure to burn.','Ray Bradbury','Fahrenheit 451');
Query OK, 8 rows affected (0.00 sec)
Records: 8  Duplicates: 0  Warnings: 0

-- Set the innodb_ft_server_stopword_table option to the new stopword table

mysql> SET GLOBAL innodb_ft_server_stopword_table = 'test/my_stopwords';
Query OK, 0 rows affected (0.00 sec)

-- Create the full-text index (which rebuilds the table if no FTS_DOC_ID column is defined)

mysql> CREATE FULLTEXT INDEX idx ON opening_lines(opening_line);
Query OK, 0 rows affected, 1 warning (1.17 sec)
Records: 0  Duplicates: 0  Warnings: 1

Verify that the specified stopword ('Ishmael') does not appear by querying the words in INFORMATION_SCHEMA.INNODB_FT_INDEX_TABLE.

Note

By default, words less than 3 characters in length or greater than 84 characters in length do not appear in an InnoDB full-text search index. Maximum and minimum word length values are configurable using the innodb_ft_max_token_size and innodb_ft_min_token_size variables. This default behavior does not apply to the ngram parser plugin. ngram token size is defined by the ngram_token_size option.

mysql> SET GLOBAL innodb_ft_aux_table='test/opening_lines';
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT word FROM INFORMATION_SCHEMA.INNODB_FT_INDEX_TABLE LIMIT 15;
+-----------+
| word      |
+-----------+
| across    |
| all       |
| burn      |
| buy       |
| call      |
| comes     |
| dalloway  |
| first     |
| flowers   |
| happened  |
| herself   |
| invisible |
| less      |
| love      |
| man       |
+-----------+
15 rows in set (0.00 sec)

To create stopword lists on a table-by-table basis, create other stopword tables and use the innodb_ft_user_stopword_table option to specify the stopword table that you want to use before you create the full-text index.

Stopwords for MyISAM Search Indexes

The stopword file is loaded and searched using latin1 if character_set_server is ucs2, utf16, utf16le, or utf32.

To override the default stopword list for MyISAM tables, set the ft_stopword_file system variable. (See Section 5.1.7, “Server System Variables”.) The variable value should be the path name of the file containing the stopword list, or the empty string to disable stopword filtering. The server looks for the file in the data directory unless an absolute path name is given to specify a different directory. After changing the value of this variable or the contents of the stopword file, restart the server and rebuild your FULLTEXT indexes.

The stopword list is free-form, separating stopwords with any nonalphanumeric character such as newline, space, or comma. Exceptions are the underscore character (_) and a single apostrophe (') which are treated as part of a word. The character set of the stopword list is the server's default character set; see Section 10.3.2, “Server Character Set and Collation”.

The following list shows the default stopwords for MyISAM search indexes. In a MySQL source distribution, you can find this list in the storage/myisam/ft_static.c file.

a's           able          about         above         according
accordingly   across        actually      after         afterwards
again         against       ain't         all           allow
allows        almost        alone         along         already
also          although      always        am            among
amongst       an            and           another       any
anybody       anyhow        anyone        anything      anyway
anyways       anywhere      apart         appear        appreciate
appropriate   are           aren't        around        as
aside         ask           asking        associated    at
available     away          awfully       be            became
because       become        becomes       becoming      been
before        beforehand    behind        being         believe
below         beside        besides       best          better
between       beyond        both          brief         but
by            c'mon         c's           came          can
can't         cannot        cant          cause         causes
certain       certainly     changes       clearly       co
com           come          comes         concerning    consequently
consider      considering   contain       containing    contains
corresponding could         couldn't      course        currently
definitely    described     despite       did           didn't
different     do            does          doesn't       doing
don't         done          down          downwards     during
each          edu           eg            eight         either
else          elsewhere     enough        entirely      especially
et            etc           even          ever          every
everybody     everyone      everything    everywhere    ex
exactly       example       except        far           few
fifth         first         five          followed      following
follows       for           former        formerly      forth
four          from          further       furthermore   get
gets          getting       given         gives         go
goes          going         gone          got           gotten
greetings     had           hadn't        happens       hardly
has           hasn't        have          haven't       having
he            he's          hello         help          hence
her           here          here's        hereafter     hereby
herein        hereupon      hers          herself       hi
him           himself       his           hither        hopefully
how           howbeit       however       i'd           i'll
i'm           i've          ie            if            ignored
immediate     in            inasmuch      inc           indeed
indicate      indicated     indicates     inner         insofar
instead       into          inward        is            isn't
it            it'd          it'll         it's          its
itself        just          keep          keeps         kept
know          known         knows         last          lately
later         latter        latterly      least         less
lest          let           let's         like          liked
likely        little        look          looking       looks
ltd           mainly        many          may           maybe
me            mean          meanwhile     merely        might
more          moreover      most          mostly        much
must          my            myself        name          namely
nd            near          nearly        necessary     need
needs         neither       never         nevertheless  new
next          nine          no            nobody        non
none          noone         nor           normally      not
nothing       novel         now           nowhere       obviously
of            off           often         oh            ok
okay          old           on            once          one
ones          only          onto          or            other
others        otherwise     ought         our           ours
ourselves     out           outside       over          overall
own           particular    particularly  per           perhaps
placed        please        plus          possible      presumably
probably      provides      que           quite         qv
rather        rd            re            really        reasonably
regarding     regardless    regards       relatively    respectively
right         said          same          saw           say
saying        says          second        secondly      see
seeing        seem          seemed        seeming       seems
seen          self          selves        sensible      sent
serious       seriously     seven         several       shall
she           should        shouldn't     since         six
so            some          somebody      somehow       someone
something     sometime      sometimes     somewhat      somewhere
soon          sorry         specified     specify       specifying
still         sub           such          sup           sure
t's           take          taken         tell          tends      
th            than          thank         thanks        thanx
that          that's        thats         the           their
theirs        them          themselves    then          thence
there         there's       thereafter    thereby       therefore
therein       theres        thereupon     these         they
they'd        they'll       they're       they've       think
third         this          thorough      thoroughly    those
though        three         through       throughout    thru
thus          to            together      too           took
toward        towards       tried         tries         truly
try           trying        twice         two           un
under         unfortunately unless        unlikely      until
unto          up            upon          us            use
used          useful        uses          using         usually
value         various       very          via           viz
vs            want          wants         was           wasn't
way           we            we'd          we'll         we're
we've         welcome       well          went          were
weren't       what          what's        whatever      when
whence        whenever      where         where's       whereafter
whereas       whereby       wherein       whereupon     wherever
whether       which         while         whither       who
who's         whoever       whole         whom          whose
why           will          willing       wish          with
within        without       won't         wonder        would
wouldn't      yes           yet           you           you'd
you'll        you're        you've        your          yours
yourself      yourselves    zero

12.9.5 Full-Text Restrictions

Full-text searches are supported for InnoDB and MyISAM tables only.
Full-text searches are not supported for partitioned tables. See Section 22.6, “Restrictions and Limitations on Partitioning”.
Full-text searches can be used with most multibyte character sets. The exception is that for Unicode, the utf8 character set can be used, but not the ucs2 character set. Although FULLTEXT indexes on ucs2 columns cannot be used, you can perform IN BOOLEAN MODE searches on a ucs2 column that has no such index.
The remarks for utf8 also apply to utf8mb4, and the remarks for ucs2 also apply to utf16, utf16le, and utf32.
Ideographic languages such as Chinese and Japanese do not have word delimiters. Therefore, the built-in full-text parser cannot determine where words begin and end in these and other such languages.
A character-based ngram full-text parser that supports Chinese, Japanese, and Korean (CJK), and a word-based MeCab parser plugin that supports Japanese are provided for use with InnoDB and MyISAM tables.
Although the use of multiple character sets within a single table is supported, all columns in a FULLTEXT index must use the same character set and collation.
The MATCH() column list must match exactly the column list in some FULLTEXT index definition for the table, unless this MATCH() is IN BOOLEAN MODE on a MyISAM table. For MyISAM tables, boolean-mode searches can be done on nonindexed columns, although they are likely to be slow.
The argument to AGAINST() must be a string value that is constant during query evaluation. This rules out, for example, a table column because that can differ for each row.
Index hints are more limited for FULLTEXT searches than for non-FULLTEXT searches. See Section 8.9.4, “Index Hints”.
For InnoDB, all DML operations (INSERT, UPDATE, DELETE) involving columns with full-text indexes are processed at transaction commit time. For example, for an INSERT operation, an inserted string is tokenized and decomposed into individual words. The individual words are then added to full-text index tables when the transaction is committed. As a result, full-text searches only return committed data.
The '%' character is not a supported wildcard character for full-text searches.

12.9.6 Fine-Tuning MySQL Full-Text Search

MySQL's full-text search capability has few user-tunable parameters. You can exert more control over full-text searching behavior if you have a MySQL source distribution because some changes require source code modifications. See Section 2.8, “Installing MySQL from Source”.

Full-text search is carefully tuned for effectiveness. Modifying the default behavior in most cases can actually decrease effectiveness. Do not alter the MySQL sources unless you know what you are doing.

Most full-text variables described in this section must be set at server startup time. A server restart is required to change them; they cannot be modified while the server is running.

Some variable changes require that you rebuild the FULLTEXT indexes in your tables. Instructions for doing so are given later in this section.

Configuring Minimum and Maximum Word Length

The minimum and maximum lengths of words to be indexed are defined by the innodb_ft_min_token_size and innodb_ft_max_token_size for InnoDB search indexes, and ft_min_word_len and ft_max_word_len for MyISAM ones.

Note

Minimum and maximum word length full-text parameters do not apply to FULLTEXT indexes created using the ngram parser. ngram token size is defined by the ngram_token_size option.

After changing any of these options, rebuild your FULLTEXT indexes for the change to take effect. For example, to make two-character words searchable, you could put the following lines in an option file:

[mysqld]
innodb_ft_min_token_size=2
ft_min_word_len=2

Then restart the server and rebuild your FULLTEXT indexes. For MyISAM tables, note the remarks regarding myisamchk in the instructions that follow for rebuilding MyISAM full-text indexes.

Configuring the Natural Language Search Threshold

For MyISAM search indexes, the 50% threshold for natural language searches is determined by the particular weighting scheme chosen. To disable it, look for the following line in storage/myisam/ftdefs.h:

#define GWS_IN_USE GWS_PROB

Change that line to this:

#define GWS_IN_USE GWS_FREQ

Then recompile MySQL. There is no need to rebuild the indexes in this case.

Note

By making this change, you severely decrease MySQL's ability to provide adequate relevance values for the MATCH() function. If you really need to search for such common words, it would be better to search using IN BOOLEAN MODE instead, which does not observe the 50% threshold.

Modifying Boolean Full-Text Search Operators

To change the operators used for boolean full-text searches on MyISAM tables, set the ft_boolean_syntax system variable. (InnoDB does not have an equivalent setting.) This variable can be changed while the server is running, but you must have the SYSTEM_VARIABLES_ADMIN or SUPER privilege to do so. No rebuilding of indexes is necessary in this case. See Section 5.1.7, “Server System Variables”, which describes the rules governing how to set this variable.

Character Set Modifications

For the built-in full-text parser, you can change the set of characters that are considered word characters in several ways, as described in the following list. After making the modification, rebuild the indexes for each table that contains any FULLTEXT indexes. Suppose that you want to treat the hyphen character ('-') as a word character. Use one of these methods:

Modify the MySQL source: In storage/innobase/handler/ha_innodb.cc (for InnoDB), or in storage/myisam/ftdefs.h (for MyISAM), see the true_word_char() and misc_word_char() macros. Add '-' to one of those macros and recompile MySQL.
Modify a character set file: This requires no recompilation. The true_word_char() macro uses a “character type” table to distinguish letters and numbers from other characters. . You can edit the contents of the <ctype><map> array in one of the character set XML files to specify that '-' is a “letter.” Then use the given character set for your FULLTEXT indexes. For information about the <ctype><map> array format, see Section 10.12.1, “Character Definition Arrays”.
Add a new collation for the character set used by the indexed columns, and alter the columns to use that collation. For general information about adding collations, see Section 10.13, “Adding a Collation to a Character Set”. For an example specific to full-text indexing, see Section 12.9.7, “Adding a Collation for Full-Text Indexing”.

Rebuilding InnoDB Full-Text Indexes

If you modify full-text variables that affect indexing (innodb_ft_min_token_size, innodb_ft_max_token_size, innodb_ft_server_stopword_table, innodb_ft_user_stopword_table, innodb_ft_enable_stopword, ngram_token_size you must rebuild your FULLTEXT indexes after making the changes. Modifying the innodb_ft_min_token_size, innodb_ft_max_token_size, or ngram_token_size variables, which cannot be set dynamically, require restarting the server and rebuilding the indexes.

To rebuild the FULLTEXT indexes for an InnoDB table, use ALTER TABLE with the DROP INDEX and ADD INDEX options to drop and re-create each index.

Optimizing InnoDB Full-Text Indexes

Running OPTIMIZE TABLE on a table with a full-text index rebuilds the full-text index, removing deleted Document IDs and consolidating multiple entries for the same word, where possible.

To optimize a full-text index, enable innodb_optimize_fulltext_only and run OPTIMIZE TABLE.

mysql> set GLOBAL innodb_optimize_fulltext_only=ON;
Query OK, 0 rows affected (0.01 sec)

mysql> OPTIMIZE TABLE opening_lines;
+--------------------+----------+----------+----------+
| Table              | Op       | Msg_type | Msg_text |
+--------------------+----------+----------+----------+
| test.opening_lines | optimize | status   | OK       |
+--------------------+----------+----------+----------+
1 row in set (0.01 sec)

To avoid lengthy rebuild times for full-text indexes on large tables, you can use the innodb_ft_num_word_optimize option to perform the optimization in stages. The innodb_ft_num_word_optimize option defines the number of words that are optimized each time OPTIMIZE TABLE is run. The default setting is 2000, which means that 2000 words are optimized each time OPTIMIZE TABLE is run. Subsequent OPTIMIZE TABLE operations continue from where the preceding OPTIMIZE TABLE operation ended.

Rebuilding MyISAM Full-Text Indexes

If you modify full-text variables that affect indexing (ft_min_word_len, ft_max_word_len, or ft_stopword_file), or if you change the stopword file itself, you must rebuild your FULLTEXT indexes after making the changes and restarting the server.

To rebuild the FULLTEXT indexes for a MyISAM table, it is sufficient to do a QUICK repair operation:

mysql> REPAIR TABLE tbl_name QUICK;

Alternatively, use ALTER TABLE as just described. In some cases, this may be faster than a repair operation.

Each table that contains any FULLTEXT index must be repaired as just shown. Otherwise, queries for the table may yield incorrect results, and modifications to the table will cause the server to see the table as corrupt and in need of repair.

If you use myisamchk to perform an operation that modifies MyISAM table indexes (such as repair or analyze), the FULLTEXT indexes are rebuilt using the default full-text parameter values for minimum word length, maximum word length, and stopword file unless you specify otherwise. This can result in queries failing.

The problem occurs because these parameters are known only by the server. They are not stored in MyISAM index files. To avoid the problem if you have modified the minimum or maximum word length or stopword file values used by the server, specify the same ft_min_word_len, ft_max_word_len, and ft_stopword_file values for myisamchk that you use for mysqld. For example, if you have set the minimum word length to 3, you can repair a table with myisamchk like this:

myisamchk --recover --ft_min_word_len=3 tbl_name.MYI

To ensure that myisamchk and the server use the same values for full-text parameters, place each one in both the [mysqld] and [myisamchk] sections of an option file:

[mysqld]
ft_min_word_len=3

[myisamchk]
ft_min_word_len=3

An alternative to using myisamchk for MyISAM table index modification is to use the REPAIR TABLE, ANALYZE TABLE, OPTIMIZE TABLE, or ALTER TABLE statements. These statements are performed by the server, which knows the proper full-text parameter values to use.

12.9.7 Adding a Collation for Full-Text Indexing

This section describes how to add a new collation for full-text searches using the built-in full-text parser. The sample collation is like latin1_swedish_ci but treats the '-' character as a letter rather than as a punctuation character so that it can be indexed as a word character. General information about adding collations is given in Section 10.13, “Adding a Collation to a Character Set”; it is assumed that you have read it and are familiar with the files involved.

To add a collation for full-text indexing, use the following procedure. The instructions here add a collation for a simple character set, which as discussed in Section 10.13, “Adding a Collation to a Character Set”, can be created using a configuration file that describes the character set properties. For a complex character set such as Unicode, create collations using C source files that describe the character set properties.

Add a collation to the Index.xml file. The collation ID must be unused, so choose a value different from 1000 if that ID is already taken on your system.
```
<charset name="latin1">
...
<collation name="latin1_fulltext_ci" id="1000"/>
</charset>
```

Declare the sort order for the collation in the latin1.xml file. In this case, the order can be copied from latin1_swedish_ci:

<collation name="latin1_fulltext_ci">
<map>
00 01 02 03 04 05 06 07 08 09 0A 0B 0C 0D 0E 0F
10 11 12 13 14 15 16 17 18 19 1A 1B 1C 1D 1E 1F
20 21 22 23 24 25 26 27 28 29 2A 2B 2C 2D 2E 2F
30 31 32 33 34 35 36 37 38 39 3A 3B 3C 3D 3E 3F
40 41 42 43 44 45 46 47 48 49 4A 4B 4C 4D 4E 4F
50 51 52 53 54 55 56 57 58 59 5A 5B 5C 5D 5E 5F
60 41 42 43 44 45 46 47 48 49 4A 4B 4C 4D 4E 4F
50 51 52 53 54 55 56 57 58 59 5A 7B 7C 7D 7E 7F
80 81 82 83 84 85 86 87 88 89 8A 8B 8C 8D 8E 8F
90 91 92 93 94 95 96 97 98 99 9A 9B 9C 9D 9E 9F
A0 A1 A2 A3 A4 A5 A6 A7 A8 A9 AA AB AC AD AE AF
B0 B1 B2 B3 B4 B5 B6 B7 B8 B9 BA BB BC BD BE BF
41 41 41 41 5C 5B 5C 43 45 45 45 45 49 49 49 49
44 4E 4F 4F 4F 4F 5D D7 D8 55 55 55 59 59 DE DF
41 41 41 41 5C 5B 5C 43 45 45 45 45 49 49 49 49
44 4E 4F 4F 4F 4F 5D F7 D8 55 55 55 59 59 DE FF
</map>
</collation>

Modify the ctype array in latin1.xml. Change the value corresponding to 0x2D (which is the code for the '-' character) from 10 (punctuation) to 01 (small letter). In the following array, this is the element in the fourth row down, third value from the end.

<ctype>
<map>
00
20 20 20 20 20 20 20 20 20 28 28 28 28 28 20 20
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
48 10 10 10 10 10 10 10 10 10 10 10 10 01 10 10
84 84 84 84 84 84 84 84 84 84 10 10 10 10 10 10
10 81 81 81 81 81 81 01 01 01 01 01 01 01 01 01
01 01 01 01 01 01 01 01 01 01 01 10 10 10 10 10
10 82 82 82 82 82 82 02 02 02 02 02 02 02 02 02
02 02 02 02 02 02 02 02 02 02 02 10 10 10 10 20
10 00 10 02 10 10 10 10 10 10 01 10 01 00 01 00
00 10 10 10 10 10 10 10 10 10 02 10 02 00 02 01
48 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
01 01 01 01 01 01 01 01 01 01 01 01 01 01 01 01
01 01 01 01 01 01 01 10 01 01 01 01 01 01 01 02
02 02 02 02 02 02 02 02 02 02 02 02 02 02 02 02
02 02 02 02 02 02 02 10 02 02 02 02 02 02 02 02
</map>
</ctype>

Restart the server.

To employ the new collation, include it in the definition of columns that are to use it:

mysql> DROP TABLE IF EXISTS t1;
Query OK, 0 rows affected (0.13 sec)

mysql> CREATE TABLE t1 (
    a TEXT CHARACTER SET latin1 COLLATE latin1_fulltext_ci,
    FULLTEXT INDEX(a)
    ) ENGINE=InnoDB;
Query OK, 0 rows affected (0.47 sec)

Test the collation to verify that hyphen is considered as a word character:

mysql> INSERT INTO t1 VALUEs ('----'),('....'),('abcd');
Query OK, 3 rows affected (0.22 sec)
Records: 3  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM t1 WHERE MATCH a AGAINST ('----' IN BOOLEAN MODE);
+------+
| a    |
+------+
| ---- |
+------+
1 row in set (0.00 sec)

12.9.8 ngram Full-Text Parser

The built-in MySQL full-text parser uses the white space between words as a delimiter to determine where words begin and end, which is a limitation when working with ideographic languages that do not use word delimiters. To address this limitation, MySQL provides an ngram full-text parser that supports Chinese, Japanese, and Korean (CJK). The ngram full-text parser is supported for use with InnoDB and MyISAM.

Note

MySQL also provides a MeCab full-text parser plugin for Japanese, which tokenizes documents into meaningful words. For more information, see Section 12.9.9, “MeCab Full-Text Parser Plugin”.

An ngram is a contiguous sequence of n characters from a given sequence of text. The ngram parser tokenizes a sequence of text into a contiguous sequence of n characters. For example, you can tokenize “abcd” for different values of n using the ngram full-text parser.

n=1: 'a', 'b', 'c', 'd'
n=2: 'ab', 'bc', 'cd'
n=3: 'abc', 'bcd'
n=4: 'abcd'

The ngram full-text parser is a built-in server plugin. As with other built-in server plugins, it is automatically loaded when the server is started.

The full-text search syntax described in Section 12.9, “Full-Text Search Functions” applies to the ngram parser plugin. Differences in parsing behavior are described in this section. Full-text-related configuration options, except for minimum and maximum word length options (innodb_ft_min_token_size, innodb_ft_max_token_size, ft_min_word_len, ft_max_word_len) are also applicable.

Configuring ngram Token Size

The ngram parser has a default ngram token size of 2 (bigram). For example, with a token size of 2, the ngram parser parses the string “abc def” into four tokens: “ab”, “bc”, “de” and “ef”.

ngram token size is configurable using the ngram_token_size configuration option, which has a minimum value of 1 and maximum value of 10.

Typically, ngram_token_size is set to the size of the largest token that you want to search for. If you only intend to search for single characters, set ngram_token_size to 1. A smaller token size produces a smaller full-text search index, and faster searches. If you need to search for words comprised of more than one character, set ngram_token_size accordingly. For example, “Happy Birthday” is “生日快乐” in simplified Chinese, where “生日” is “birthday”, and “快乐” translates as “happy”. To search on two-character words such as these, set ngram_token_size to a value of 2 or higher.

As a read-only variable, ngram_token_size may only be set as part of a startup string or in a configuration file:

Startup string:
```
mysqld --ngram_token_size=2
```
Configuration file:
```
[mysqld]
ngram_token_size=2
```

Note

The following minimum and maximum word length configuration options are ignored for FULLTEXT indexes that use the ngram parser: innodb_ft_min_token_size, innodb_ft_max_token_size, ft_min_word_len, and ft_max_word_len.

Creating a FULLTEXT Index that Uses the ngram Parser

To create a FULLTEXT index that uses the ngram parser, specify WITH PARSER ngram with CREATE TABLE, ALTER TABLE, or CREATE INDEX.

The following example demonstrates creating a table with an ngram FULLTEXT index, inserting sample data (Simplified Chinese text), and viewing tokenized data in the INFORMATION_SCHEMA.INNODB_FT_INDEX_CACHE table.

mysql> USE test;

mysql> CREATE TABLE articles (
      id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
      title VARCHAR(200),
      body TEXT,
      FULLTEXT (title,body) WITH PARSER ngram
    ) ENGINE=InnoDB CHARACTER SET utf8mb4;

mysql> SET NAMES utf8mb4;

INSERT INTO articles (title,body) VALUES
    ('数据库管理','在本教程中我将向你展示如何管理数据库'),
    ('数据库应用开发','学习开发数据库应用程序');
    
mysql> SET GLOBAL innodb_ft_aux_table="test/articles";

mysql> SELECT * FROM INFORMATION_SCHEMA.INNODB_FT_INDEX_CACHE ORDER BY doc_id, position;

To add a FULLTEXT index to an existing table, you can use ALTER TABLE or CREATE INDEX. For example:

CREATE TABLE articles (
      id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
      title VARCHAR(200),
      body TEXT
     ) ENGINE=InnoDB CHARACTER SET utf8;

ALTER TABLE articles ADD FULLTEXT INDEX ft_index (title,body) WITH PARSER ngram;

# Or:

CREATE FULLTEXT INDEX ft_index ON articles (title,body) WITH PARSER ngram;

ngram Parser Space Handling

The ngram parser eliminates spaces when parsing. For example:

“ab cd” is parsed to “ab”, “cd”
“a bc” is parsed to “bc”

ngram Parser Stopword Handling

The built-in MySQL full-text parser compares words to entries in the stopword list. If a word is equal to an entry in the stopword list, the word is excluded from the index. For the ngram parser, stopword handling is performed differently. Instead of excluding tokens that are equal to entries in the stopword list, the ngram parser excludes tokens that contain stopwords. For example, assuming ngram_token_size=2, a document that contains “a,b” is parsed to “a,” and “,b”. If a comma (“,”) is defined as a stopword, both “a,” and “,b” are excluded from the index because they contain a comma.

By default, the ngram parser uses the default stopword list, which contains a list of English stopwords. For a stopword list applicable to Chinese, Japanese, or Korean, you must create your own. For information about creating a stopword list, see Section 12.9.4, “Full-Text Stopwords”.

Stopwords greater in length than ngram_token_size are ignored.

ngram Parser Term Search

For natural language mode search, the search term is converted to a union of ngram terms. For example, the string “abc” (assuming ngram_token_size=2) is converted to “ab bc”. Given two documents, one containing “ab” and the other containing “abc”, the search term “ab bc” matches both documents.

For boolean mode search, the search term is converted to an ngram phrase search. For example, the string 'abc' (assuming ngram_token_size=2) is converted to '“ab bc”'. Given two documents, one containing 'ab' and the other containing 'abc', the search phrase '“ab bc”' only matches the document containing 'abc'.

ngram Parser Wildcard Search

Because an ngram FULLTEXT index contains only ngrams, and does not contain information about the beginning of terms, wildcard searches may return unexpected results. The following behaviors apply to wildcard searches using ngram FULLTEXT search indexes:

If the prefix term of a wildcard search is shorter than ngram token size, the query returns all indexed rows that contain ngram tokens starting with the prefix term. For example, assuming ngram_token_size=2, a search on “a*” returns all rows starting with “a”.
If the prefix term of a wildcard search is longer than ngram token size, the prefix term is converted to an ngram phrase and the wildcard operator is ignored. For example, assuming ngram_token_size=2, an “abc*” wildcard search is converted to “ab bc”.

ngram Parser Phrase Search

Phrase searches are converted to ngram phrase searches. For example, The search phrase “abc” is converted to “ab bc”, which returns documents containing “abc” and “ab bc”.

The search phrase “abc def” is converted to “ab bc de ef”, which returns documents containing “abc def” and “ab bc de ef”. A document that contains “abcdef” is not returned.

12.9.9 MeCab Full-Text Parser Plugin

The built-in MySQL full-text parser uses the white space between words as a delimiter to determine where words begin and end, which is a limitation when working with ideographic languages that do not use word delimiters. To address this limitation for Japanese, MySQL provides a MeCab full-text parser plugin. The MeCab full-text parser plugin is supported for use with InnoDB and MyISAM.

Note

MySQL also provides an ngram full-text parser plugin that supports Japanese. For more information, see Section 12.9.8, “ngram Full-Text Parser”.

The MeCab full-text parser plugin is a full-text parser plugin for Japanese that tokenizes a sequence of text into meaningful words. For example, MeCab tokenizes “データベース管理” (“Database Management”) into “データベース” (“Database”) and “管理” (“Management”). By comparison, the ngram full-text parser tokenizes text into a contiguous sequence of n characters, where n represents a number between 1 and 10.

In addition to tokenizing text into meaningful words, MeCab indexes are typically smaller than ngram indexes, and MeCab full-text searches are generally faster. One drawback is that it may take longer for the MeCab full-text parser to tokenize documents, compared to the ngram full-text parser.

The full-text search syntax described in Section 12.9, “Full-Text Search Functions” applies to the MeCab parser plugin. Differences in parsing behavior are described in this section. Full-text related configuration options are also applicable.

For additional information about the MeCab parser, refer to the MeCab: Yet Another Part-of-Speech and Morphological Analyzer project on Github.

Installing the MeCab Parser Plugin

The MeCab parser plugin requires mecab and mecab-ipadic.

On supported Fedora, Debian and Ubuntu platforms (except Ubuntu 12.04 where the system mecab version is too old), MySQL dynamically links to the system mecab installation if it is installed to the default location. On other supported Unix-like platforms, libmecab.so is statically linked in libpluginmecab.so, which is located in the MySQL plugin directory. mecab-ipadic is included in MySQL binaries and is located in MYSQL_HOME\lib\mecab.

You can install mecab and mecab-ipadic using a native package management utility (on Fedora, Debian, and Ubuntu), or you can build mecab and mecab-ipadic from source. For information about installing mecab and mecab-ipadic using a native package management utility, see Installing MeCab From a Binary Distribution (Optional). If you want to build mecab and mecab-ipadic from source, see Building MeCab From Source (Optional).

On Windows, libmecab.dll is found in the MySQL bin directory. mecab-ipadic is located in MYSQL_HOME/lib/mecab.

To install and configure the MeCab parser plugin, perform the following steps:

In the MySQL configuration file, set the mecab_rc_file configuration option to the location of the mecabrc configuration file, which is the configuration file for MeCab. If you are using the MeCab package distributed with MySQL, the mecabrc file is located in MYSQL_HOME/lib/mecab/etc/.
```
[mysqld]
loose-mecab-rc-file=MYSQL_HOME/lib/mecab/etc/mecabrc
```
The loose prefix is an option modifier. The mecab_rc_file option is not recognized by MySQL until the MeCaB parser plugin is installed but it must be set before attempting to install the MeCaB parser plugin. The loose prefix allows you restart MySQL without encountering an error due to an unrecognized variable.
If you use your own MeCab installation, or build MeCab from source, the location of the mecabrc configuration file may differ.
For information about the MySQL configuration file and its location, see Section 4.2.6, “Using Option Files”.
Also in the MySQL configuration file, set the minimum token size to 1 or 2, which are the values recommended for use with the MeCab parser. For InnoDB tables, minimum token size is defined by the innodb_ft_min_token_size configuration option, which has a default value of 3. For MyISAM tables, minimum token size is defined by ft_min_word_len, which has a default value of 4.
```
[mysqld]
innodb_ft_min_token_size=1
```
Modify the mecabrc configuration file to specify the dictionary you want to use. The mecab-ipadic package distributed with MySQL binaries includes three dictionaries (ipadic_euc-jp, ipadic_sjis, and ipadic_utf-8). The mecabrc configuration file packaged with MySQL contains and entry similar to the following:
```
dicdir =  /path/to/mysql/lib/mecab/lib/mecab/dic/ipadic_euc-jp
```
To use the ipadic_utf-8 dictionary, for example, modify the entry as follows:
```
dicdir=MYSQL_HOME/lib/mecab/dic/ipadic_utf-8
```
If you are using your own MeCab installation or have built MeCab from source, the default dicdir entry in the mecabrc file will differ, as will the dictionaries and their location.
Note

After the MeCab parser plugin is installed, you can use the mecab_charset status variable to view the character set used with MeCab. The three MeCab dictionaries provided with the MySQL binary support the following character sets.
- The ipadic_euc-jp dictionary supports the ujis and eucjpms character sets.
- The ipadic_sjis dictionary supports the sjis and cp932 character sets.
- The ipadic_utf-8 dictionary supports the utf8 and utf8mb4 character sets.
mecab_charset only reports the first supported character set. For example, the ipadic_utf-8 dictionary supports both utf8 and utf8mb4. mecab_charset always reports utf8 when this dictionary is in use.
Restart MySQL.
Install the MeCab parser plugin:
The MeCab parser plugin is installed using INSTALL PLUGIN syntax. The plugin name is mecab, and the shared library name is libpluginmecab.so. For additional information about installing plugins, see Section 5.6.1, “Installing and Uninstalling Plugins”.
```
INSTALL PLUGIN mecab SONAME 'libpluginmecab.so';
```
Once installed, the MeCab parser plugin loads at every normal MySQL restart.
Verify that the MeCab parser plugin is loaded using the SHOW PLUGINS statement.
```
mysql> SHOW PLUGINS;
```
A mecab plugin should appear in the list of plugins.

Creating a FULLTEXT Index that uses the MeCab Parser

To create a FULLTEXT index that uses the mecab parser, specify WITH PARSER ngram with CREATE TABLE, ALTER TABLE, or CREATE INDEX.

This example demonstrates creating a table with a mecab FULLTEXT index, inserting sample data, and viewing tokenized data in the INFORMATION_SCHEMA.INNODB_FT_INDEX_CACHE table:

mysql> USE test;

mysql> CREATE TABLE articles (
      id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
      title VARCHAR(200),
      body TEXT,
      FULLTEXT (title,body) WITH PARSER mecab
    ) ENGINE=InnoDB CHARACTER SET utf8;

mysql> SET NAMES utf8;
    
mysql> INSERT INTO articles (title,body) VALUES
    ('データベース管理','このチュートリアルでは、私はどのようにデータベースを管理する方法を紹介します'),
    ('データベースアプリケーション開発','データベースアプリケーションを開発することを学ぶ');

mysql> SET GLOBAL innodb_ft_aux_table="test/articles";

mysql> SELECT * FROM INFORMATION_SCHEMA.INNODB_FT_INDEX_CACHE ORDER BY doc_id, position;

To add a FULLTEXT index to an existing table, you can use ALTER TABLE or CREATE INDEX. For example:

CREATE TABLE articles (
      id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
      title VARCHAR(200),
      body TEXT
     ) ENGINE=InnoDB CHARACTER SET utf8;

ALTER TABLE articles ADD FULLTEXT INDEX ft_index (title,body) WITH PARSER mecab;

# Or:

CREATE FULLTEXT INDEX ft_index ON articles (title,body) WITH PARSER mecab;

MeCab Parser Space Handling

The MeCab parser uses spaces as separators in query strings. For example, the MeCab parser tokenizes データベース管理 as データベース and 管理.

MeCab Parser Stopword Handling

By default, the MeCab parser uses the default stopword list, which contains a short list of English stopwords. For a stopword list applicable to Japanese, you must create your own. For information about creating stopword lists, see Section 12.9.4, “Full-Text Stopwords”.

MeCab Parser Term Search

For natural language mode search, the search term is converted to a union of tokens. For example, データベース管理 is converted to データベース管理.

SELECT COUNT(*) FROM articles WHERE MATCH(title,body) AGAINST('データベース管理' IN NATURAL LANGUAGE MODE);

For boolean mode search, the search term is converted to a search phrase. For example, データベース管理 is converted to データベース管理.

SELECT COUNT(*) FROM articles WHERE MATCH(title,body) AGAINST('データベース管理' IN BOOLEAN MODE);

MeCab Parser Wildcard Search

Wildcard search terms are not tokenized. A search on データベース管理* is performed on the prefix, データベース管理.

SELECT COUNT(*) FROM articles WHERE MATCH(title,body) AGAINST('データベース*' IN BOOLEAN MODE);

MeCab Parser Phrase Search

Phrases are tokenized. For example, データベース管理 is tokenized as データベース管理.

SELECT COUNT(*) FROM articles WHERE MATCH(title,body) AGAINST('"データベース管理"' IN BOOLEAN MODE);

Installing MeCab From a Binary Distribution (Optional)

This section describes how to install mecab and mecab-ipadic from a binary distribution using a native package management utility. For example, on Fedora, you can use Yum to perform the installation:

yum mecab-devel

On Debian or Ubuntu, you can perform an APT installation:

apt-get install mecab
apt-get install mecab-ipadic

Installing MeCab From Source (Optional)

If you want to build mecab and mecab-ipadic from source, basic installation steps are provided below. For additional information, refer to the MeCab documentation.

Download the tar.gz packages for mecab and mecab-ipadic from http://taku910.github.io/mecab/#download. As of February, 2016, the latest available packages are mecab-0.996.tar.gz and mecab-ipadic-2.7.0-20070801.tar.gz.

Install mecab:

tar zxfv mecab-0.996.tar
cd mecab-0.996
./configure
make
make check
su
make install

Install mecab-ipadic:

tar zxfv mecab-ipadic-2.7.0-20070801.tar
cd mecab-ipadic-2.7.0-20070801
./configure
make
su
make install

Compile MySQL using the WITH_MECAB CMake option. Set the WITH_MECAB option to system if you have installed mecab and mecab-ipadic to the default location.
```
-DWITH_MECAB=system
```
If you defined a custom installation directory, set WITH_MECAB to the custom directory. For example:
```
-DWITH_MECAB=/path/to/mecab
```

12.10 Cast Functions and Operators

Table 12.14 Cast Functions and Operators

Name	Description
`BINARY`	Cast a string to a binary string
`CAST()`	Cast a value as a certain type
`CONVERT()`	Cast a value as a certain type

Cast functions and operators enable conversion of values from one data type to another.

CONVERT() with a USING clause provides a way to convert data between different character sets:

CONVERT(expr USING transcoding_name)

In MySQL, transcoding names are the same as the corresponding character set names.

Examples:

SELECT CONVERT(_latin1'Müller' USING utf8);
INSERT INTO utf8_table (utf8_column)
    SELECT CONVERT(latin1_column USING utf8) FROM latin1_table;

You can also use CONVERT() without USING or CAST() to convert strings between different character sets:

CONVERT(string, CHAR[(N)] CHARACTER SET charset_name)
CAST(string AS CHAR[(N)] CHARACTER SET charset_name)

Examples:

SELECT CONVERT('test', CHAR CHARACTER SET utf8);
SELECT CAST('test' AS CHAR CHARACTER SET utf8);

If you specify CHARACTER SET charset_name as just shown, the resulting character set and collation are charset_name and the default collation of charset_name. If you omit CHARACTER SET charset_name, the resulting character set and collation are defined by the character_set_connection and collation_connection system variables that determine the default connection character set and collation (see Section 10.4, “Connection Character Sets and Collations”).

A COLLATE clause is not permitted within a CONVERT() or CAST() call, but you can apply it to the function result. For example, this is legal:

SELECT CAST('test' AS CHAR CHARACTER SET utf8) COLLATE utf8_bin;

But this is illegal:

SELECT CAST('test' AS CHAR CHARACTER SET utf8 COLLATE utf8_bin);

Normally, you cannot compare a BLOB value or other binary string in case-insensitive fashion because binary strings use the binary character set, which has no collation with the concept of lettercase. To perform a case-insensitive comparison, use the CONVERT() or CAST() function to convert the value to a nonbinary string. Comparisons of the resulting string use its collation. For example, if the conversion result character set has a case-insensitive collation, a LIKE operation is not case-sensitive:

SELECT 'A' LIKE CONVERT(blob_col USING latin1)
  FROM tbl_name;

To use a different character set, substitute its name for latin1 in the preceding statement. To specify a particular collation for the converted string, use a COLLATE clause following the CONVERT() call:

SELECT 'A' LIKE CONVERT(blob_col USING latin1) COLLATE latin1_german1_ci
  FROM tbl_name;

CONVERT() and CAST() can be used more generally for comparing strings that are represented in different character sets. For example, a comparison of these strings results in an error because they have different character sets:

mysql> SET @s1 = _latin1 'abc', @s2 = _latin2 'abc';
mysql> SELECT @s1 = @s2;
ERROR 1267 (HY000): Illegal mix of collations (latin1_swedish_ci,IMPLICIT)
and (latin2_general_ci,IMPLICIT) for operation '='

Converting one of the strings to a character set compatible with the other enables the comparison to occur without error:

mysql> SELECT @s1 = CONVERT(@s2 USING latin1);
+---------------------------------+
| @s1 = CONVERT(@s2 USING latin1) |
+---------------------------------+
|                               1 |
+---------------------------------+

For string literals, another way to specify the character set is to use a character set introducer (_latin1 and _latin2 in the preceding example are instances of introducers). Unlike conversion functions such as CAST(), or CONVERT(), which convert a string from one character set to another, an introducer designates a string literal as having a particular character set, with no conversion involved. For more information, see Section 10.3.8, “Character Set Introducers”.

Character set conversion is also useful preceding lettercase conversion of binary strings. LOWER() and UPPER() are ineffective when applied directly to binary strings because the concept of lettercase does not apply. To perform lettercase conversion of a binary string, first convert it to a nonbinary string:

mysql> SET @str = BINARY 'New York';
mysql> SELECT LOWER(@str), LOWER(CONVERT(@str USING utf8mb4));
+-------------+------------------------------------+
| LOWER(@str) | LOWER(CONVERT(@str USING utf8mb4)) |
+-------------+------------------------------------+
| New York    | new york                           |
+-------------+------------------------------------+

If you convert an indexed column using BINARY, CAST(), or CONVERT(), MySQL may not be able to use the index efficiently.

The cast functions are useful for creating a column with a specific type in a CREATE TABLE ... SELECT statement:


mysql> CREATE TABLE new_table SELECT CAST('2000-01-01' AS DATE) AS c1;
mysql> SHOW CREATE TABLE new_table\G
*************************** 1. row ***************************
       Table: new_table
Create Table: CREATE TABLE `new_table` (
  `c1` date DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4

The cast functions are useful for sorting ENUM columns in lexical order. Normally, sorting of ENUM columns occurs using the internal numeric values. Casting the values to CHAR results in a lexical sort:

SELECT enum_col FROM tbl_name ORDER BY CAST(enum_col AS CHAR);

CAST() also changes the result if you use it as part of a more complex expression such as CONCAT('Date: ',CAST(NOW() AS DATE)).

For temporal values, there is little need to use CAST() to extract data in different formats. Instead, use a function such as EXTRACT(), DATE_FORMAT(), or TIME_FORMAT(). See Section 12.7, “Date and Time Functions”.

To cast a string to a number, you normally need do nothing other than use the string value in numeric context:

mysql> SELECT 1+'1';
       -> 2

That is also true for hexadecimal and bit literals, which are binary strings by default:

mysql> SELECT X'41', X'41'+0;
        -> 'A', 65
mysql> SELECT b'1100001', b'1100001'+0;
        -> 'a', 97

A string used in an arithmetic operation is converted to a floating-point number during expression evaluation.

A number used in string context is converted to a string:

mysql> SELECT CONCAT('hello you ',2);
        -> 'hello you 2'

For information about implicit conversion of numbers to strings, see Section 12.2, “Type Conversion in Expression Evaluation”.

MySQL supports arithmetic with both signed and unsigned 64-bit values. For numeric operators (such as + or -) where one of the operands is an unsigned integer, the result is unsigned by default (see Section 12.6.1, “Arithmetic Operators”). To override this, use the SIGNED or UNSIGNED cast operator to cast a value to a signed or unsigned 64-bit integer, respectively.

mysql> SELECT 1 - 2;
        -> -1
mysql> SELECT CAST(1 - 2 AS UNSIGNED);
        -> 18446744073709551615
mysql> SELECT CAST(CAST(1 - 2 AS UNSIGNED) AS SIGNED);
        -> -1

If either operand is a floating-point value, the result is a floating-point value and is not affected by the preceding rule. (In this context, DECIMAL column values are regarded as floating-point values.)

mysql> SELECT CAST(1 AS UNSIGNED) - 2.0;
        -> -1.0

The SQL mode affects the result of conversion operations (see Section 5.1.10, “Server SQL Modes”). Examples:

For conversion of a “zero” date string to a date, CONVERT() and CAST() return NULL and produce a warning when the NO_ZERO_DATE SQL mode is enabled.
For integer subtraction, if the NO_UNSIGNED_SUBTRACTION SQL mode is enabled, the subtraction result is signed even if any operand is unsigned.

The following list describes the available cast functions and operators:

BINARY expr
The BINARY operator converts the expression to a binary string. A common use for BINARY is to force a character string comparison to be done byte by byte rather than character by character, in effect becoming case-sensitive. The BINARY operator also causes trailing spaces in comparisons to be significant.
```
mysql> SELECT 'a' = 'A';
        -> 1
mysql> SELECT BINARY 'a' = 'A';
        -> 0
mysql> SELECT 'a' = 'a ';
        -> 1
mysql> SELECT BINARY 'a' = 'a ';
        -> 0
```
In a comparison, BINARY affects the entire operation; it can be given before either operand with the same result.
For purposes of converting a string expression to a binary string, these constructs are equivalent:
```
BINARY expr
CAST(expr AS BINARY)
CONVERT(expr USING BINARY)
```
If a value is a string literal, it can be designated as a binary string without performing any conversion by using the _binary character set introducer:
```
mysql> SELECT 'a' = 'A';
        -> 1
mysql> SELECT _binary 'a' = 'A';
        -> 0
```
For information about introducers, see Section 10.3.8, “Character Set Introducers”.
The BINARY operator in expressions differs in effect from the BINARY attribute in character column definitions. A character column defined with the BINARY attribute is assigned table default character set and the binary (_bin) collation of that character set. Every nonbinary character set has a _bin collation. For example, the binary collation for the utf8 character set is utf8_bin, so if the table default character set is utf8, these two column definitions are equivalent:
```
CHAR(10) BINARY
CHAR(10) CHARACTER SET utf8 COLLATE utf8_bin
```
The use of CHARACTER SET binary in the definition of a CHAR, VARCHAR, or TEXT column causes the column to be treated as the corresponding binary string data type. For example, the following pairs of definitions are equivalent:
```
CHAR(10) CHARACTER SET binary
BINARY(10)

VARCHAR(10) CHARACTER SET binary
VARBINARY(10)

TEXT CHARACTER SET binary
BLOB
```
CAST(expr AS type)
The CAST() function takes an expression of any type and produces a result value of the specified type, similar to CONVERT(). For more information, see the description of CONVERT().
CAST() is standard SQL syntax.
CONVERT(expr,type), CONVERT(expr USING transcoding_name)
The CONVERT() function takes an expression of any type and produces a result value of the specified type.
Discussion of CONVERT(expr, type) syntax here also applies to CAST(expr AS type), which is equivalent.
CONVERT(... USING ...) is standard SQL syntax. The non-USING form of CONVERT() is ODBC syntax.
CONVERT() with USING converts data between different character sets. In MySQL, transcoding names are the same as the corresponding character set names. For example, this statement converts the string 'abc' in the default character set to the corresponding string in the utf8 character set:
```
SELECT CONVERT('abc' USING utf8);
```
CONVERT() without USING and CAST() take an expression and a type value specifying the result type. These type values are permitted:
- BINARY[(N)]
  Produces a string with the BINARY data type. See Section 11.4.2, “The BINARY and VARBINARY Types” for a description of how this affects comparisons. If the optional length N is given, BINARY(N) causes the cast to use no more than N bytes of the argument. Values shorter than N bytes are padded with 0x00 bytes to a length of N.
- CHAR[(N)] [charset_info]
  Produces a string with the CHAR data type. If the optional length N is given, CHAR(N) causes the cast to use no more than N characters of the argument. No padding occurs for values shorter than N characters.
  With no charset_info clause, CHAR produces a string with the default character set. To specify the character set explicitly, these charset_info values are permitted:
  - CHARACTER SET charset_name: Produces a string with the given character set.
  - ASCII: Shorthand for CHARACTER SET latin1.
  - UNICODE: Shorthand for CHARACTER SET ucs2.
  In all cases, the string has the default collation for the character set.
- DATE
  Produces a DATE value.
- DATETIME
  Produces a DATETIME value.
- DECIMAL[(M[,D])]
  Produces a DECIMAL value. If the optional M and D values are given, they specify the maximum number of digits (the precision) and the number of digits following the decimal point (the scale).
- JSON
  Produces a JSON value. For details on the rules for conversion of values between JSON and other types, see Comparison and Ordering of JSON Values.
- NCHAR[(N)]
  Like CHAR, but produces a string with the national character set. See Section 10.3.7, “The National Character Set”.
  Unlike CHAR, NCHAR does not permit trailing character set information to be specified.
- SIGNED [INTEGER]
  Produces a signed integer value.
- TIME
  Produces a TIME value.
- UNSIGNED [INTEGER]
  Produces an unsigned integer value.

12.11 XML Functions

Table 12.15 XML Functions

Name	Description
`ExtractValue()`	Extracts a value from an XML string using XPath notation
`UpdateXML()`	Return replaced XML fragment

This section discusses XML and related functionality in MySQL.

Note

It is possible to obtain XML-formatted output from MySQL in the mysql and mysqldump clients by invoking them with the --xml option. See Section 4.5.1, “mysql — The MySQL Command-Line Tool”, and Section 4.5.4, “mysqldump — A Database Backup Program”.

Two functions providing basic XPath 1.0 (XML Path Language, version 1.0) capabilities are available. Some basic information about XPath syntax and usage is provided later in this section; however, an in-depth discussion of these topics is beyond the scope of this manual, and you should refer to the XML Path Language (XPath) 1.0 standard for definitive information. A useful resource for those new to XPath or who desire a refresher in the basics is the Zvon.org XPath Tutorial, which is available in several languages.

Note

These functions remain under development. We continue to improve these and other aspects of XML and XPath functionality in MySQL 8.0 and onwards. You may discuss these, ask questions about them, and obtain help from other users with them in the MySQL XML User Forum.

XPath expressions used with these functions support user variables and local stored program variables. User variables are weakly checked; variables local to stored programs are strongly checked (see also Bug #26518):

User variables (weak checking). Variables using the syntax $@variable_name (that is, user variables) are not checked. No warnings or errors are issued by the server if a variable has the wrong type or has previously not been assigned a value. This also means the user is fully responsible for any typographical errors, since no warnings will be given if (for example) $@myvariable is used where $@myvariable was intended.

Example:

mysql> SET @xml = '<a><b>X</b><b>Y</b></a>';
Query OK, 0 rows affected (0.00 sec)

mysql> SET @i =1, @j = 2;
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT @i, ExtractValue(@xml, '//b[$@i]');
+------+--------------------------------+
| @i   | ExtractValue(@xml, '//b[$@i]') |
+------+--------------------------------+
|    1 | X                              |
+------+--------------------------------+
1 row in set (0.00 sec)

mysql> SELECT @j, ExtractValue(@xml, '//b[$@j]');
+------+--------------------------------+
| @j   | ExtractValue(@xml, '//b[$@j]') |
+------+--------------------------------+
|    2 | Y                              |
+------+--------------------------------+
1 row in set (0.00 sec)

mysql> SELECT @k, ExtractValue(@xml, '//b[$@k]');
+------+--------------------------------+
| @k   | ExtractValue(@xml, '//b[$@k]') |
+------+--------------------------------+
| NULL |                                |
+------+--------------------------------+
1 row in set (0.00 sec)

Variables in stored programs (strong checking). Variables using the syntax $variable_name can be declared and used with these functions when they are called inside stored programs. Such variables are local to the stored program in which they are defined, and are strongly checked for type and value.

Example:

mysql> DELIMITER |

mysql> CREATE PROCEDURE myproc ()
    -> BEGIN
    ->   DECLARE i INT DEFAULT 1;
    ->   DECLARE xml VARCHAR(25) DEFAULT '<a>X</a><a>Y</a><a>Z</a>';
    ->
    ->   WHILE i < 4 DO
    ->     SELECT xml, i, ExtractValue(xml, '//a[$i]');
    ->     SET i = i+1;
    ->   END WHILE;
    -> END |
Query OK, 0 rows affected (0.01 sec)

mysql> DELIMITER ;

mysql> CALL myproc();
+--------------------------+---+------------------------------+
| xml                      | i | ExtractValue(xml, '//a[$i]') |
+--------------------------+---+------------------------------+
| <a>X</a><a>Y</a><a>Z</a> | 1 | X                            |
+--------------------------+---+------------------------------+
1 row in set (0.00 sec)

+--------------------------+---+------------------------------+
| xml                      | i | ExtractValue(xml, '//a[$i]') |
+--------------------------+---+------------------------------+
| <a>X</a><a>Y</a><a>Z</a> | 2 | Y                            |
+--------------------------+---+------------------------------+
1 row in set (0.01 sec)

+--------------------------+---+------------------------------+
| xml                      | i | ExtractValue(xml, '//a[$i]') |
+--------------------------+---+------------------------------+
| <a>X</a><a>Y</a><a>Z</a> | 3 | Z                            |
+--------------------------+---+------------------------------+
1 row in set (0.01 sec)

Parameters. Variables used in XPath expressions inside stored routines that are passed in as parameters are also subject to strong checking.

Expressions containing user variables or variables local to stored programs must otherwise (except for notation) conform to the rules for XPath expressions containing variables as given in the XPath 1.0 specification.

Note

A user variable used to store an XPath expression is treated as an empty string. Because of this, it is not possible to store an XPath expression as a user variable. (Bug #32911)

ExtractValue(xml_frag, xpath_expr)

ExtractValue() takes two string arguments, a fragment of XML markup xml_frag and an XPath expression xpath_expr (also known as a locator); it returns the text (CDATA) of the first text node which is a child of the element or elements matched by the XPath expression.

Using this function is the equivalent of performing a match using the xpath_expr after appending /text(). In other words, ExtractValue('<a>Sakila</a>', '/a/b') and ExtractValue('<a>Sakila</a>', '/a/b/text()') produce the same result.

If multiple matches are found, the content of the first child text node of each matching element is returned (in the order matched) as a single, space-delimited string.

If no matching text node is found for the expression (including the implicit /text())—for whatever reason, as long as xpath_expr is valid, and xml_frag consists of elements which are properly nested and closed—an empty string is returned. No distinction is made between a match on an empty element and no match at all. This is by design.

If you need to determine whether no matching element was found in xml_frag or such an element was found but contained no child text nodes, you should test the result of an expression that uses the XPath count() function. For example, both of these statements return an empty string, as shown here:

mysql> SELECT ExtractValue('<a><b/></a>', '/a/b');
+-------------------------------------+
| ExtractValue('<a><b/></a>', '/a/b') |
+-------------------------------------+
|                                     |
+-------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ExtractValue('<a><c/></a>', '/a/b');
+-------------------------------------+
| ExtractValue('<a><c/></a>', '/a/b') |
+-------------------------------------+
|                                     |
+-------------------------------------+
1 row in set (0.00 sec)

However, you can determine whether there was actually a matching element using the following:

mysql> SELECT ExtractValue('<a><b/></a>', 'count(/a/b)');
+-------------------------------------+
| ExtractValue('<a><b/></a>', 'count(/a/b)') |
+-------------------------------------+
| 1                                   |
+-------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ExtractValue('<a><c/></a>', 'count(/a/b)');
+-------------------------------------+
| ExtractValue('<a><c/></a>', 'count(/a/b)') |
+-------------------------------------+
| 0                                   |
+-------------------------------------+
1 row in set (0.01 sec)

Important

ExtractValue() returns only CDATA, and does not return any tags that might be contained within a matching tag, nor any of their content (see the result returned as val1 in the following example).

mysql> SELECT
    ->   ExtractValue('<a>ccc<b>ddd</b></a>', '/a') AS val1,
    ->   ExtractValue('<a>ccc<b>ddd</b></a>', '/a/b') AS val2,
    ->   ExtractValue('<a>ccc<b>ddd</b></a>', '//b') AS val3,
    ->   ExtractValue('<a>ccc<b>ddd</b></a>', '/b') AS val4,
    ->   ExtractValue('<a>ccc<b>ddd</b><b>eee</b></a>', '//b') AS val5;

+------+------+------+------+---------+
| val1 | val2 | val3 | val4 | val5    |
+------+------+------+------+---------+
| ccc  | ddd  | ddd  |      | ddd eee |
+------+------+------+------+---------+

This function uses the current SQL collation for making comparisons with contains(), performing the same collation aggregation as other string functions (such as CONCAT()), in taking into account the collation coercibility of their arguments; see Section 10.8.4, “Collation Coercibility in Expressions”, for an explanation of the rules governing this behavior.

(Previously, binary—that is, case-sensitive—comparison was always used.)

NULL is returned if xml_frag contains elements which are not properly nested or closed, and a warning is generated, as shown in this example:

mysql> SELECT ExtractValue('<a>c</a><b', '//a');
+-----------------------------------+
| ExtractValue('<a>c</a><b', '//a') |
+-----------------------------------+
| NULL                              |
+-----------------------------------+
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS\G
*************************** 1. row ***************************
  Level: Warning
   Code: 1525
Message: Incorrect XML value: 'parse error at line 1 pos 11:
         END-OF-INPUT unexpected ('>' wanted)'
1 row in set (0.00 sec)

mysql> SELECT ExtractValue('<a>c</a><b/>', '//a');
+-------------------------------------+
| ExtractValue('<a>c</a><b/>', '//a') |
+-------------------------------------+
| c                                   |
+-------------------------------------+
1 row in set (0.00 sec)

UpdateXML(xml_target, xpath_expr, new_xml)

This function replaces a single portion of a given fragment of XML markup xml_target with a new XML fragment new_xml, and then returns the changed XML. The portion of xml_target that is replaced matches an XPath expression xpath_expr supplied by the user.

If no expression matching xpath_expr is found, or if multiple matches are found, the function returns the original xml_target XML fragment. All three arguments should be strings.

mysql> SELECT
    ->   UpdateXML('<a><b>ccc</b><d></d></a>', '/a', '<e>fff</e>') AS val1,
    ->   UpdateXML('<a><b>ccc</b><d></d></a>', '/b', '<e>fff</e>') AS val2,
    ->   UpdateXML('<a><b>ccc</b><d></d></a>', '//b', '<e>fff</e>') AS val3,
    ->   UpdateXML('<a><b>ccc</b><d></d></a>', '/a/d', '<e>fff</e>') AS val4,
    ->   UpdateXML('<a><d></d><b>ccc</b><d></d></a>', '/a/d', '<e>fff</e>') AS val5
    -> \G

*************************** 1. row ***************************
val1: <e>fff</e>
val2: <a><b>ccc</b><d></d></a>
val3: <a><e>fff</e><d></d></a>
val4: <a><b>ccc</b><e>fff</e></a>
val5: <a><d></d><b>ccc</b><d></d></a>

Note

A discussion in depth of XPath syntax and usage are beyond the scope of this manual. Please see the XML Path Language (XPath) 1.0 specification for definitive information. A useful resource for those new to XPath or who are wishing a refresher in the basics is the Zvon.org XPath Tutorial, which is available in several languages.

Descriptions and examples of some basic XPath expressions follow:

/tag
Matches <tag/> if and only if <tag/> is the root element.
Example: /a has a match in <a></a> because it matches the outermost (root) tag. It does not match the inner a element in <a/> because in this instance it is the child of another element.
/tag1/tag2
Matches <tag2/> if and only if it is a child of <tag1/>, and <tag1/> is the root element.
Example: /a/b matches the b element in the XML fragment <a></a> because it is a child of the root element a. It does not have a match in <a/> because in this case, b is the root element (and hence the child of no other element). Nor does the XPath expression have a match in <a><c></c></a>; here, b is a descendant of a, but not actually a child of a.
This construct is extendable to three or more elements. For example, the XPath expression /a/b/c matches the c element in the fragment <a><c/></a>.

//tag

Matches any instance of <tag>.

Example: //a matches the a element in any of the following: <a><c/></a>; <c><a></a>; <c><a/></c>.

// can be combined with /. For example, //a/b matches the b element in either of the fragments <a></a> or <c><a></a></c>.

Note

//tag is the equivalent of /descendant-or-self::*/tag. A common error is to confuse this with /descendant-or-self::tag, although the latter expression can actually lead to very different results, as can be seen here:

mysql> SET @xml = '<a><b><c>w</c><b>x</b><d>y</d>z</b></a>';
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT @xml;
+-----------------------------------------+
| @xml                                    |
+-----------------------------------------+
| <a><b><c>w</c><b>x</b><d>y</d>z</b></a> |
+-----------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ExtractValue(@xml, '//b[1]');
+------------------------------+
| ExtractValue(@xml, '//b[1]') |
+------------------------------+
| x z                          |
+------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ExtractValue(@xml, '//b[2]');
+------------------------------+
| ExtractValue(@xml, '//b[2]') |
+------------------------------+
|                              |
+------------------------------+
1 row in set (0.01 sec)

mysql> SELECT ExtractValue(@xml, '/descendant-or-self::*/b[1]');
+---------------------------------------------------+
| ExtractValue(@xml, '/descendant-or-self::*/b[1]') |
+---------------------------------------------------+
| x z                                               |
+---------------------------------------------------+
1 row in set (0.06 sec)

mysql> SELECT ExtractValue(@xml, '/descendant-or-self::*/b[2]');
+---------------------------------------------------+
| ExtractValue(@xml, '/descendant-or-self::*/b[2]') |
+---------------------------------------------------+
|                                                   |
+---------------------------------------------------+
1 row in set (0.00 sec)


mysql> SELECT ExtractValue(@xml, '/descendant-or-self::b[1]');
+-------------------------------------------------+
| ExtractValue(@xml, '/descendant-or-self::b[1]') |
+-------------------------------------------------+
| z                                               |
+-------------------------------------------------+
1 row in set (0.00 sec)

mysql> SELECT ExtractValue(@xml, '/descendant-or-self::b[2]');
+-------------------------------------------------+
| ExtractValue(@xml, '/descendant-or-self::b[2]') |
+-------------------------------------------------+
| x                                               |
+-------------------------------------------------+
1 row in set (0.00 sec)

The * operator acts as a “wildcard” that matches any element. For example, the expression /*/b matches the b element in either of the XML fragments <a></a> or <c></c>. However, the expression does not produce a match in the fragment <a/> because b must be a child of some other element. The wildcard may be used in any position: The expression /*/b/* will match any child of a b element that is itself not the root element.
You can match any of several locators using the | (UNION) operator. For example, the expression //b|//c matches all b and c elements in the XML target.
It is also possible to match an element based on the value of one or more of its attributes. This done using the syntax tag[@attribute="value"]. For example, the expression //b[@id="idB"] matches the second b element in the fragment <a><c/></a>. To match against any element having attribute="value", use the XPath expression //*[attribute="value"].
To filter multiple attribute values, simply use multiple attribute-comparison clauses in succession. For example, the expression //b[@c="x"][@d="y"] matches the element  occurring anywhere in a given XML fragment.
To find elements for which the same attribute matches any of several values, you can use multiple locators joined by the | operator. For example, to match all b elements whose c attributes have either of the values 23 or 17, use the expression //b[@c="23"]|//b[@c="17"]. You can also use the logical or operator for this purpose: //b[@c="23" or @c="17"].

Note

The difference between or and | is that or joins conditions, while | joins result sets.

XPath Limitations. The XPath syntax supported by these functions is currently subject to the following limitations:

Nodeset-to-nodeset comparison (such as '/a/b[@c=@d]') is not supported.
All of the standard XPath comparison operators are supported. (Bug #22823)

Relative locator expressions are resolved in the context of the root node. For example, consider the following query and result:

mysql> SELECT ExtractValue(
    ->   '<a><b c="1">X</b><b c="2">Y</b></a>',
    ->    'a/b'
    -> ) AS result;
+--------+
| result |
+--------+
| X Y    |
+--------+
1 row in set (0.03 sec)

In this case, the locator a/b resolves to /a/b.

Relative locators are also supported within predicates. In the following example, d[../@c="1"] is resolved as /a/b[@c="1"]/d:

mysql> SELECT ExtractValue(
    ->      '<a>
    ->        <b c="1"><d>X</d></b>
    ->        <b c="2"><d>X</d></b>
    ->      </a>',
    ->      'a/b/d[../@c="1"]')
    -> AS result;
+--------+
| result |
+--------+
| X      |
+--------+
1 row in set (0.00 sec)

Locators prefixed with expressions that evaluate as scalar values—including variable references, literals, numbers, and scalar function calls—are not permitted, and their use results in an error.

The :: operator is not supported in combination with node types such as the following:

axis::comment()
axis::text()
axis::processing-instructions()
axis::node()

However, name tests (such as axis::name and axis::*) are supported, as shown in these examples:

mysql> SELECT ExtractValue('<a><b>x</b><c>y</c></a>','/a/child::b');
+-------------------------------------------------------+
| ExtractValue('<a><b>x</b><c>y</c></a>','/a/child::b') |
+-------------------------------------------------------+
| x                                                     |
+-------------------------------------------------------+
1 row in set (0.02 sec)

mysql> SELECT ExtractValue('<a><b>x</b><c>y</c></a>','/a/child::*');
+-------------------------------------------------------+
| ExtractValue('<a><b>x</b><c>y</c></a>','/a/child::*') |
+-------------------------------------------------------+
| x y                                                   |
+-------------------------------------------------------+
1 row in set (0.01 sec)

“Up-and-down” navigation is not supported in cases where the path would lead “above” the root element. That is, you cannot use expressions which match on descendants of ancestors of a given element, where one or more of the ancestors of the current element is also an ancestor of the root element (see Bug #16321).
The following XPath functions are not supported, or have known issues as indicated:
- id()
- lang()
- local-name()
- name()
- namespace-uri()
- normalize-space()
- starts-with()
- string()
- substring-after()
- substring-before()
- translate()
The following axes are not supported:
- following-sibling
- following
- preceding-sibling
- preceding

XPath expressions passed as arguments to ExtractValue() and UpdateXML() may contain the colon character (:) in element selectors, which enables their use with markup employing XML namespaces notation. For example:

mysql> SET @xml = '<a>111<b:c>222<d>333</d><e:f>444</e:f></b:c></a>';
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT ExtractValue(@xml, '//e:f');
+-----------------------------+
| ExtractValue(@xml, '//e:f') |
+-----------------------------+
| 444                         |
+-----------------------------+
1 row in set (0.00 sec)

mysql> SELECT UpdateXML(@xml, '//b:c', '<g:h>555</g:h>');
+--------------------------------------------+
| UpdateXML(@xml, '//b:c', '<g:h>555</g:h>') |
+--------------------------------------------+
| <a>111<g:h>555</g:h></a>                   |
+--------------------------------------------+
1 row in set (0.00 sec)

This is similar in some respects to what is permitted by Apache Xalan and some other parsers, and is much simpler than requiring namespace declarations or the use of the namespace-uri() and local-name() functions.

Error handling. For both ExtractValue() and UpdateXML(), the XPath locator used must be valid and the XML to be searched must consist of elements which are properly nested and closed. If the locator is invalid, an error is generated:

mysql> SELECT ExtractValue('<a>c</a><b/>', '/&a');
ERROR 1105 (HY000): XPATH syntax error: '&a'

If xml_frag does not consist of elements which are properly nested and closed, NULL is returned and a warning is generated, as shown in this example:

mysql> SELECT ExtractValue('<a>c</a><b', '//a');
+-----------------------------------+
| ExtractValue('<a>c</a><b', '//a') |
+-----------------------------------+
| NULL                              |
+-----------------------------------+
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS\G
*************************** 1. row ***************************
  Level: Warning
   Code: 1525
Message: Incorrect XML value: 'parse error at line 1 pos 11:
         END-OF-INPUT unexpected ('>' wanted)'
1 row in set (0.00 sec)

mysql> SELECT ExtractValue('<a>c</a><b/>', '//a');
+-------------------------------------+
| ExtractValue('<a>c</a><b/>', '//a') |
+-------------------------------------+
| c                                   |
+-------------------------------------+
1 row in set (0.00 sec)

Important

The replacement XML used as the third argument to UpdateXML() is not checked to determine whether it consists solely of elements which are properly nested and closed.

XPath Injection. code injection occurs when malicious code is introduced into the system to gain unauthorized access to privileges and data. It is based on exploiting assumptions made by developers about the type and content of data input from users. XPath is no exception in this regard.

A common scenario in which this can happen is the case of application which handles authorization by matching the combination of a login name and password with those found in an XML file, using an XPath expression like this one:

//user[login/text()='neapolitan' and password/text()='1c3cr34m']/attribute::id

This is the XPath equivalent of an SQL statement like this one:

SELECT id FROM users WHERE login='neapolitan' AND password='1c3cr34m';

A PHP application employing XPath might handle the login process like this:

<?php

  $file     =   "users.xml";

  $login    =   $POST["login"];
  $password =   $POST["password"];

  $xpath = "//user[login/text()=$login and password/text()=$password]/attribute::id";

  if( file_exists($file) )
  {
    $xml = simplexml_load_file($file);

    if($result = $xml->xpath($xpath))
      echo "You are now logged in as user $result[0].";
    else
      echo "Invalid login name or password.";
  }
  else
    exit("Failed to open $file.");

?>

No checks are performed on the input. This means that a malevolent user can “short-circuit” the test by entering ' or 1=1 for both the login name and password, resulting in $xpath being evaluated as shown here:

//user[login/text()='' or 1=1 and password/text()='' or 1=1]/attribute::id

Since the expression inside the square brackets always evaluates as true, it is effectively the same as this one, which matches the id attribute of every user element in the XML document:

//user/attribute::id

One way in which this particular attack can be circumvented is simply by quoting the variable names to be interpolated in the definition of $xpath, forcing the values passed from a Web form to be converted to strings:

$xpath = "//user[login/text()='$login' and password/text()='$password']/attribute::id";

This is the same strategy that is often recommended for preventing SQL injection attacks. In general, the practices you should follow for preventing XPath injection attacks are the same as for preventing SQL injection:

Never accepted untested data from users in your application.
Check all user-submitted data for type; reject or convert data that is of the wrong type
Test numeric data for out of range values; truncate, round, or reject values that are out of range. Test strings for illegal characters and either strip them out or reject input containing them.
Do not output explicit error messages that might provide an unauthorized user with clues that could be used to compromise the system; log these to a file or database table instead.

Just as SQL injection attacks can be used to obtain information about database schemas, so can XPath injection be used to traverse XML files to uncover their structure, as discussed in Amit Klein's paper Blind XPath Injection (PDF file, 46KB).

It is also important to check the output being sent back to the client. Consider what can happen when we use the MySQL ExtractValue() function:

mysql> SELECT ExtractValue(
    ->     LOAD_FILE('users.xml'),
    ->     '//user[login/text()="" or 1=1 and password/text()="" or 1=1]/attribute::id'
    -> ) AS id;
+-------------------------------+
| id                            |
+-------------------------------+
| 00327 13579 02403 42354 28570 |
+-------------------------------+
1 row in set (0.01 sec)

Because ExtractValue() returns multiple matches as a single space-delimited string, this injection attack provides every valid ID contained within users.xml to the user as a single row of output. As an extra safeguard, you should also test output before returning it to the user. Here is a simple example:

mysql> SELECT @id = ExtractValue(
    ->     LOAD_FILE('users.xml'),
    ->     '//user[login/text()="" or 1=1 and password/text()="" or 1=1]/attribute::id'
    -> );
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT IF(
    ->     INSTR(@id, ' ') = 0,
    ->     @id,
    ->     'Unable to retrieve user ID')
    -> AS singleID;
+----------------------------+
| singleID                   |
+----------------------------+
| Unable to retrieve user ID |
+----------------------------+
1 row in set (0.00 sec)

In general, the guidelines for returning data to users securely are the same as for accepting user input. These can be summed up as:

Always test outgoing data for type and permissible values.
Never permit unauthorized users to view error messages that might provide information about the application that could be used to exploit it.

12.12 Bit Functions and Operators

Table 12.16 Bit Functions and Operators

Name	Description
`BIT_COUNT()`	Return the number of bits that are set
`&`	Bitwise AND
`~`	Bitwise inversion
`\|`	Bitwise OR
`^`	Bitwise XOR
`<<`	Left shift
`>>`	Right shift

Bit functions and operators comprise BIT_COUNT(), BIT_AND(), BIT_OR(), BIT_XOR(), &, |, ^, ~, <<, and >>. (The BIT_AND(), BIT_OR(), and BIT_XOR() aggregate functions are described in Section 12.19.1, “Aggregate (GROUP BY) Function Descriptions”.) Prior to MySQL 8.0, bit functions and operators required BIGINT (64-bit integer) arguments and returned BIGINT values, so they had a maximum range of 64 bits. Non-BIGINT arguments were converted to BIGINT prior to performing the operation and truncation could occur.

In MySQL 8.0, bit functions and operators permit binary string type arguments (BINARY, VARBINARY, and the BLOB types) and return a value of like type, which enables them to take arguments and produce return values larger than 64 bits. Nonbinary string arguments are converted to BIGINT and processed as such, as before.

An implication of this change in behavior is that bit operations on binary string arguments might produce a different result in MySQL 8.0 than in 5.7. For information about how to prepare in MySQL 5.7 for potential incompatibilities between MySQL 5.7 and 8.0, see Bit Functions and Operators, in MySQL 5.7 Reference Manual.

Bit Operations Prior to MySQL 8.0

Bit operations prior to MySQL 8.0 handle only unsigned 64-bit integer argument and result values (that is, unsigned BIGINT values). Conversion of arguments of other types to BIGINT occurs as necessary. Examples:

This statement operates on numeric literals, treated as unsigned 64-bit integers:

mysql> SELECT 127 | 128, 128 << 2, BIT_COUNT(15);
+-----------+----------+---------------+
| 127 | 128 | 128 << 2 | BIT_COUNT(15) |
+-----------+----------+---------------+
|       255 |      512 |             4 |
+-----------+----------+---------------+

This statement performs to-number conversions on the string arguments ('127' to 127, and so forth) before performing the same operations as the first statement and producing the same results:

mysql> SELECT '127' | '128', '128' << 2, BIT_COUNT('15');
+---------------+------------+-----------------+
| '127' | '128' | '128' << 2 | BIT_COUNT('15') |
+---------------+------------+-----------------+
|           255 |        512 |               4 |
+---------------+------------+-----------------+

This statement uses hexadecimal literals for the bit-operation arguments. MySQL by default treats hexadecimal literals as binary strings, but in numeric context evaluates them as numbers (see Section 9.1.4, “Hexadecimal Literals”). Prior to MySQL 8.0, numeric context includes bit operations. Examples:
```
mysql> SELECT X'7F' | X'80', X'80' << 2, BIT_COUNT(X'0F');
+---------------+------------+------------------+
| X'7F' | X'80' | X'80' << 2 | BIT_COUNT(X'0F') |
+---------------+------------+------------------+
| 255 | 512 | 4 |
+---------------+------------+------------------+
```
Handling of bit-value literals in bit operations is similar to hexadecimal literals (that is, as numbers).

Bit Operations in MySQL 8.0

MySQL 8.0 extends bit operations to handle binary string arguments directly (without conversion) and produce binary string results. (Arguments that are not integers or binary strings are still converted to integers, as before.) This extension enhances bit operations in the following ways:

Bit operations become possible on values longer than 64 bits.
It is easier to perform bit operations on values that are more naturally represented as binary strings than as integers.

For example, consider UUID values and IPv6 addresses, which have human-readable text formats like this:

UUID: 6ccd780c-baba-1026-9564-5b8c656024db
IPv6: fe80::219:d1ff:fe91:1a72

It is cumbersome to operate on text strings in those formats. An alternative is convert them to fixed-length binary strings without delimiters. UUID_TO_BIN() and INET6_ATON() each produce a value of data type BINARY(16), a binary string 16 bytes (128 bits) long. The following statements illustrate this (HEX() is used to produce displayable values):

mysql> SELECT HEX(UUID_TO_BIN('6ccd780c-baba-1026-9564-5b8c656024db'));
+----------------------------------------------------------+
| HEX(UUID_TO_BIN('6ccd780c-baba-1026-9564-5b8c656024db')) |
+----------------------------------------------------------+
| 6CCD780CBABA102695645B8C656024DB                         |
+----------------------------------------------------------+
mysql> SELECT HEX(INET6_ATON('fe80::219:d1ff:fe91:1a72'));
+---------------------------------------------+
| HEX(INET6_ATON('fe80::219:d1ff:fe91:1a72')) |
+---------------------------------------------+
| FE800000000000000219D1FFFE911A72            |
+---------------------------------------------+

Those binary values are easily manipulable with bit operations to perform actions such as extracting the timestamp from UUID values, or extracting the network and host parts of IPv6 addresses. (For examples, see later in this discussion.)

Arguments that count as binary strings include column values, routine parameters, local variables, and user-defined variables that have a binary string type: BINARY, VARBINARY, or one of the BLOB types.

What about hexadecimal literals and bit literals? Recall that those are binary strings by default in MySQL, but numbers in numeric context. How are they handled for bit operations in MySQL 8.0? Does MySQL continue to evaluate them in numeric context, as is done prior to MySQL 8.0? Or do bit operations evaluate them as binary strings, now that binary strings can be handled “natively” without conversion?

Answer: It has been common to specify arguments to bit operations using hexadecimal literals or bit literals with the intent that they represent numbers, so MySQL continues to evaluate bit operations in numeric context when all bit arguments are hexadecimal or bit literals, for backward compatility. If you require evaluation as binary strings instead, that is easily accomplished: Use the _binary introducer for at least one literal.

These bit operations evaluate the hexadecimal literals and bit literals as integers:

mysql> SELECT X'40' | X'01', b'11110001' & b'01001111';
+---------------+---------------------------+
| X'40' | X'01' | b'11110001' & b'01001111' |
+---------------+---------------------------+
|            65 |                        65 |
+---------------+---------------------------+

These bit operations evaluate the hexadecimal literals and bit literals as binary strings, due to the _binary introducer:

mysql> SELECT _binary X'40' | X'01', b'11110001' & _binary b'01001111';
+-----------------------+-----------------------------------+
| _binary X'40' | X'01' | b'11110001' & _binary b'01001111' |
+-----------------------+-----------------------------------+
| A                     | A                                 |
+-----------------------+-----------------------------------+

Although the bit operations in both statements produce a result with a numeric value of 65, the second statement operates in binary-string context, for which 65 is ASCII A.

In numeric evaluation context, permitted values of hexadecimal literal and bit literal arguments have a maximum of 64 bits, as do results. By contrast, in binary-string evaluation context, permitted arguments (and results) can exceed 64 bits:

mysql> SELECT _binary X'4040404040404040' | X'0102030405060708';
+---------------------------------------------------+
| _binary X'4040404040404040' | X'0102030405060708' |
+---------------------------------------------------+
| ABCDEFGH                                          |
+---------------------------------------------------+

There are several ways to refer to a hexadecimal literal or bit literal in a bit operation to cause binary-string evaluation:

_binary literal
BINARY literal
CAST(literal AS BINARY)

Another way to produce binary-string evaluation of hexadecimal literals or bit literals is to assign them to user-defined variables, which results in variables that have a binary string type:

mysql> SET @v1 = X'40', @v2 = X'01', @v3 = b'11110001', @v4 = b'01001111';
mysql> SELECT @v1 | @v2, @v3 & @v4;
+-----------+-----------+
| @v1 | @v2 | @v3 & @v4 |
+-----------+-----------+
| A         | A         |
+-----------+-----------+

In binary-string context, bitwise operation arguments must have the same length or an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs:

mysql> SELECT _binary X'40' | X'0001';
ERROR 3513 (HY000): Binary operands of bitwise
operators must be of equal length

To satisfy the equal-length requirement, pad the shorter value with leading zero digits or, if the longer value begins with leading zero digits and a shorter result value is acceptable, strip them:

mysql> SELECT _binary X'0040' | X'0001';
+---------------------------+
| _binary X'0040' | X'0001' |
+---------------------------+
|  A                        |
+---------------------------+
mysql> SELECT _binary X'40' | X'01';
+-----------------------+
| _binary X'40' | X'01' |
+-----------------------+
| A                     |
+-----------------------+

Padding or stripping can also be accomplished using functions such as LPAD(), RPAD(), SUBSTR(), or CAST(). In such cases, the expression arguments are no longer all literals and _binary becomes unnecessary. Examples:

mysql> SELECT LPAD(X'40', 2, X'00') | X'0001';
+---------------------------------+
| LPAD(X'40', 2, X'00') | X'0001' |
+---------------------------------+
|  A                              |
+---------------------------------+
mysql> SELECT X'40' | SUBSTR(X'0001', 2, 1);
+-------------------------------+
| X'40' | SUBSTR(X'0001', 2, 1) |
+-------------------------------+
| A                             |
+-------------------------------+

Binary String Bit-Operation Examples

The following example illustrates use of bit operations to extract parts of a UUID value, in this case, the timestamp and IEEE 802 node number. This technique requires bitmasks for each extracted part.

Convert the text UUID to the corresponding 16-byte binary value so that it can be manipulated using bit operations in binary-string context:

mysql> SET @uuid = UUID_TO_BIN('6ccd780c-baba-1026-9564-5b8c656024db');
mysql> SELECT HEX(@uuid);
+----------------------------------+
| HEX(@uuid)                       |
+----------------------------------+
| 6CCD780CBABA102695645B8C656024DB |
+----------------------------------+

Construct bitmasks for the timestamp and node number parts of the value. The timestamp comprises the first three parts (64 bits, bits 0 to 63) and the node number is the last part (48 bits, bits 80 to 127):

mysql> SET @ts_mask = CAST(X'FFFFFFFFFFFFFFFF' AS BINARY(16));
mysql> SET @node_mask = CAST(X'FFFFFFFFFFFF' AS BINARY(16)) >> 80;
mysql> SELECT HEX(@ts_mask);
+----------------------------------+
| HEX(@ts_mask)                    |
+----------------------------------+
| FFFFFFFFFFFFFFFF0000000000000000 |
+----------------------------------+
mysql> SELECT HEX(@node_mask);
+----------------------------------+
| HEX(@node_mask)                  |
+----------------------------------+
| 00000000000000000000FFFFFFFFFFFF |
+----------------------------------+

The CAST(... AS BINARY(16)) function is used here because the masks must be the same length as the UUID value against which they are applied. The same result can be produced using other functions to pad the masks to the required length:

SET @ts_mask= RPAD(X'FFFFFFFFFFFFFFFF' , 16, X'00');
SET @node_mask = LPAD(X'FFFFFFFFFFFF', 16, X'00') ;

Use the masks to extract the timestamp and node number parts:

mysql> SELECT HEX(@uuid & @ts_mask) AS 'timestamp part';
+----------------------------------+
| timestamp part                   |
+----------------------------------+
| 6CCD780CBABA10260000000000000000 |
+----------------------------------+
mysql> SELECT HEX(@uuid & @node_mask) AS 'node part';
+----------------------------------+
| node part                        |
+----------------------------------+
| 000000000000000000005B8C656024DB |
+----------------------------------+

The preceding example uses these bit operations: right shift (>>) and bitwise AND (&).

Note

UUID_TO_BIN() takes a flag that causes some bit rearrangement in the resulting binary UUID value. If you use that flag, modify the extraction masks accordingly.

The next example uses bit operations to extract the network and host parts of an IPv6 address. Suppose that the network part has a length of 80 bits. Then the host part has a length of 128 − 80 = 48 bits. To extract the network and host parts of the address, convert it to a binary string, then use bit operations in binary-string context.

Convert the text IPv6 address to the corresponding binary string:

mysql> SET @ip = INET6_ATON('fe80::219:d1ff:fe91:1a72');

Define the network length in bits:

mysql> SET @net_len = 80;

Construct network and host masks by shifting the all-ones address left or right. To do this, begin with the address ::, which is shorthand for all zeros, as you can see by converting it to a binary string like this:

mysql> SELECT HEX(INET6_ATON('::')) AS 'all zeros';
+----------------------------------+
| all zeros                        |
+----------------------------------+
| 00000000000000000000000000000000 |
+----------------------------------+

To produce the complementary value (all ones), use the ~ operator to invert the bits:

mysql> SELECT HEX(~INET6_ATON('::')) AS 'all ones';
+----------------------------------+
| all ones                         |
+----------------------------------+
| FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF |
+----------------------------------+

Shift the all-ones value left or right to produce the network and host masks:

mysql> SET @net_mask = ~INET6_ATON('::') << (128 - @net_len);
mysql> SET @host_mask = ~INET6_ATON('::') >> @net_len;

Display the masks to verify that they cover the correct parts of the address:

mysql> SELECT INET6_NTOA(@net_mask) AS 'network mask';
+----------------------------+
| network mask               |
+----------------------------+
| ffff:ffff:ffff:ffff:ffff:: |
+----------------------------+
mysql> SELECT INET6_NTOA(@host_mask) AS 'host mask';
+------------------------+
| host mask              |
+------------------------+
| ::ffff:255.255.255.255 |
+------------------------+

Extract and display the network and host parts of the address:

mysql> SET @net_part = @ip & @net_mask;
mysql> SET @host_part = @ip & @host_mask;
mysql> SELECT INET6_NTOA(@net_part) AS 'network part';
+-----------------+
| network part    |
+-----------------+
| fe80::219:0:0:0 |
+-----------------+
mysql> SELECT INET6_NTOA(@host_part) AS 'host part';
+------------------+
| host part        |
+------------------+
| ::d1ff:fe91:1a72 |
+------------------+

The preceding example uses these bit operations: Complement (~), left shift (<<), and bitwise AND (&).

The remaining discussion provides details on argument handling for each group of bit operations, more information about literal-value handling in bit operations, and potential incompatibilities between MySQL 8.0 and older MySQL versions.

Bitwise AND, OR, and XOR Operations

For &, |, and ^ bit operations, the result type depends on whether the arguments are evaluated as binary strings or numbers:

Binary-string evaluation occurs when the arguments have a binary string type, and at least one of them is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to unsigned 64-bit integers as necessary.
Binary-string evaluation produces a binary string of the same length as the arguments. If the arguments have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.

Examples of numeric evaluation:

mysql> SELECT 64 | 1, X'40' | X'01';
+--------+---------------+
| 64 | 1 | X'40' | X'01' |
+--------+---------------+
|     65 |            65 |
+--------+---------------+

Examples of binary-string evaluation:

mysql> SELECT _binary X'40' | X'01';
+-----------------------+
| _binary X'40' | X'01' |
+-----------------------+
| A                     |
+-----------------------+
mysql> SET @var1 = X'40', @var2 = X'01';
mysql> SELECT @var1 | @var2;
+---------------+
| @var1 | @var2 |
+---------------+
| A             |
+---------------+

Bitwise Complement and Shift Operations

For ~, <<, and >> bit operations, the result type depends on whether the bit argument is evaluated as a binary string or number:

Binary-string evaluation occurs when the bit argument has a binary string type, and is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to an unsigned 64-bit integer as necessary.
Binary-string evaluation produces a binary string of the same length as the bit argument. Numeric evaluation produces an unsigned 64-bit integer.

For shift operations, bits shifted off the end of the value are lost without warning, regardless of the argument type. In particular, if the shift count is greater or equal to the number of bits in the bit argument, all bits in the result are 0.

Examples of numeric evaluation:

mysql> SELECT ~0, 64 << 2, X'40' << 2;
+----------------------+---------+------------+
| ~0                   | 64 << 2 | X'40' << 2 |
+----------------------+---------+------------+
| 18446744073709551615 |     256 |        256 |
+----------------------+---------+------------+

Examples of binary-string evaluation:

mysql> SELECT HEX(_binary X'1111000022220000' >> 16);
+----------------------------------------+
| HEX(_binary X'1111000022220000' >> 16) |
+----------------------------------------+
| 0000111100002222                       |
+----------------------------------------+
mysql> SELECT HEX(_binary X'1111000022220000' << 16);
+----------------------------------------+
| HEX(_binary X'1111000022220000' << 16) |
+----------------------------------------+
| 0000222200000000                       |
+----------------------------------------+
mysql> SET @var1 = X'F0F0F0F0';
mysql> SELECT HEX(~@var1);
+-------------+
| HEX(~@var1) |
+-------------+
| 0F0F0F0F    |
+-------------+

BIT_COUNT() Operations

The BIT_COUNT() function always returns an unsigned 64-bit integer, or NULL if the argument is NULL.

mysql> SELECT BIT_COUNT(127);
+----------------+
| BIT_COUNT(127) |
+----------------+
|              7 |
+----------------+
mysql> SELECT BIT_COUNT(b'010101'), BIT_COUNT(_binary b'010101');
+----------------------+------------------------------+
| BIT_COUNT(b'010101') | BIT_COUNT(_binary b'010101') |
+----------------------+------------------------------+
|                    3 |                            3 |
+----------------------+------------------------------+

BIT_AND(), BIT_OR(), and BIT_XOR() Operations

For the BIT_AND(), BIT_OR(), and BIT_XOR() bit functions, the result type depends on whether the function argument values are evaluated as binary strings or numbers:

Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.
Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. If the argument size exceeds 511 bytes, an ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.

NULL values do not affect the result unless all values are NULL. In that case, the result is a neutral value having the same length as the length of the argument values (all bits 1 for BIT_AND(), all bits 0 for BIT_OR(), and BIT_XOR()).

Example:


mysql> CREATE TABLE t (group_id INT, a VARBINARY(6));
mysql> INSERT INTO t VALUES (1, NULL);
mysql> INSERT INTO t VALUES (1, NULL);
mysql> INSERT INTO t VALUES (2, NULL);
mysql> INSERT INTO t VALUES (2, X'1234');
mysql> INSERT INTO t VALUES (2, X'FF34');
mysql> SELECT HEX(BIT_AND(a)), HEX(BIT_OR(a)), HEX(BIT_XOR(a))
       FROM t GROUP BY group_id;
+-----------------+----------------+-----------------+
| HEX(BIT_AND(a)) | HEX(BIT_OR(a)) | HEX(BIT_XOR(a)) |
+-----------------+----------------+-----------------+
| FFFFFFFFFFFF    | 000000000000   | 000000000000    |
| 1234            | FF34           | ED00            |
+-----------------+----------------+-----------------+

Special Handling of Hexadecimal Literals, Bit Literals, and NULL Literals

For backward compatibility, MySQL 8.0 evaluates bit operations in numeric context when all bit arguments are hexadecimal literals, bit literals, or NULL literals. That is, bit operations on binary-string bit arguments do not use binary-string evaluation if all bit arguments are unadorned hexadecimal literals, bit literals, or NULL literals. (This does not apply to such literals if they are written with a _binary introducer, BINARY operator, or other way of specifying them explicitly as binary strings.)

The literal handling just described is the same as prior to MySQL 8.0. Examples:

These bit operations evaluate the literals in numeric context and produce a BIGINT result:
```
b'0001' | b'0010'
X'0008' << 8
```
These bit operations evaluate NULL in numeric context and produce a BIGINT result that has a NULL value:
```
NULL & NULL
NULL >> 4
```

In MySQL 8.0, you can cause those operations to evaluate the arguments in binary-string context by indicating explicitly that at least one argument is a binary string:

_binary b'0001' | b'0010'
_binary X'0008' << 8
BINARY NULL & NULL
BINARY NULL >> 4

The result of the last two expressions is NULL, just as without the BINARY operator, but the data type of the result is a binary string type rather than an integer type.

Bit-Operation Incompatibilities with MySQL 5.7

Because bit operations can handle binary string arguments natively in MySQL 8.0, some expressions produce a different result in MySQL 8.0 than in 5.7. The five problematic expression types to watch out for are:

nonliteral_binary { & | ^ } binary
binary  { & | ^ } nonliteral_binary
nonliteral_binary { << >> } anything
~ nonliteral_binary
AGGR_BIT_FUNC(nonliteral_binary)

Those expressions return BIGINT in MySQL 5.7, binary string in 8.0.

Explanation of notation:

{ op1 op2 ... }: List of operators that apply to the given expression type.
binary: Any kind of binary string argument, including a hexadecimal literal, bit literal, or NULL literal.
nonliteral_binary: An argument that is a binary string value other than a hexadecimal literal, bit literal, or NULL literal.
AGGR_BIT_FUNC: An aggregate function that takes bit-value arguments: BIT_AND(), BIT_OR(), BIT_XOR().

For information about how to prepare in MySQL 5.7 for potential incompatibilities between MySQL 5.7 and 8.0, see Bit Functions and Operators, in MySQL 5.7 Reference Manual.

The following list describes available bit functions and operators:

|
Bitwise OR.
The result type depends on whether the arguments are evaluated as binary strings or numbers:
- Binary-string evaluation occurs when the arguments have a binary string type, and at least one of them is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to unsigned 64-bit integers as necessary.
- Binary-string evaluation produces a binary string of the same length as the arguments. If the arguments have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.
For more information, see the introductory discussion in this section.
```
mysql> SELECT 29 | 15;
        -> 31
mysql> SELECT _binary X'40404040' | X'01020304';
        -> 'ABCD'
```
&
Bitwise AND.
The result type depends on whether the arguments are evaluated as binary strings or numbers:
- Binary-string evaluation occurs when the arguments have a binary string type, and at least one of them is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to unsigned 64-bit integers as necessary.
- Binary-string evaluation produces a binary string of the same length as the arguments. If the arguments have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.
For more information, see the introductory discussion in this section.
```
mysql> SELECT 29 & 15;
        -> 13
mysql> SELECT HEX(_binary X'FF' & b'11110000');
        -> 'F0'
```
^
Bitwise XOR.
The result type depends on whether the arguments are evaluated as binary strings or numbers:
- Binary-string evaluation occurs when the arguments have a binary string type, and at least one of them is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to unsigned 64-bit integers as necessary.
- Binary-string evaluation produces a binary string of the same length as the arguments. If the arguments have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.
For more information, see the introductory discussion in this section.
```
mysql> SELECT 1 ^ 1;
        -> 0
mysql> SELECT 1 ^ 0;
        -> 1
mysql> SELECT 11 ^ 3;
        -> 8
mysql> SELECT HEX(_binary X'FEDC' ^ X'1111');
        -> 'EFCD'
```
<<
Shifts a longlong (BIGINT) number or binary string to the left.
The result type depends on whether the bit argument is evaluated as a binary string or number:
- Binary-string evaluation occurs when the bit argument has a binary string type, and is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to an unsigned 64-bit integer as necessary.
- Binary-string evaluation produces a binary string of the same length as the bit argument. Numeric evaluation produces an unsigned 64-bit integer.
Bits shifted off the end of the value are lost without warning, regardless of the argument type. In particular, if the shift count is greater or equal to the number of bits in the bit argument, all bits in the result are 0.
For more information, see the introductory discussion in this section.
```
mysql> SELECT 1 << 2;
 -> 4
mysql> SELECT HEX(_binary X'00FF00FF00FF' << 8);
 -> 'FF00FF00FF00'
```
>>
Shifts a longlong (BIGINT) number or binary string to the right.
The result type depends on whether the bit argument is evaluated as a binary string or number:
- Binary-string evaluation occurs when the bit argument has a binary string type, and is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to an unsigned 64-bit integer as necessary.
- Binary-string evaluation produces a binary string of the same length as the bit argument. Numeric evaluation produces an unsigned 64-bit integer.
Bits shifted off the end of the value are lost without warning, regardless of the argument type. In particular, if the shift count is greater or equal to the number of bits in the bit argument, all bits in the result are 0.
For more information, see the introductory discussion in this section.
```
mysql> SELECT 4 >> 2;
        -> 1
mysql> SELECT HEX(_binary X'00FF00FF00FF' >> 8);
        -> '0000FF00FF00'
```
~
Invert all bits.
The result type depends on whether the bit argument is evaluated as a binary string or number:
- Binary-string evaluation occurs when the bit argument has a binary string type, and is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument conversion to an unsigned 64-bit integer as necessary.
- Binary-string evaluation produces a binary string of the same length as the bit argument. Numeric evaluation produces an unsigned 64-bit integer.
For more information, see the introductory discussion in this section.
```
mysql> SELECT 5 & ~1;
        -> 4
mysql> SELECT HEX(~X'0000FFFF1111EEEE');
        -> 'FFFF0000EEEE1111'
```

BIT_COUNT(N)

Returns the number of bits that are set in the argument N as an unsigned 64-bit integer, or NULL if the argument is NULL.

mysql> SELECT BIT_COUNT(64), BIT_COUNT(BINARY 64);
        -> 1, 7
mysql> SELECT BIT_COUNT('64'), BIT_COUNT(_binary '64');
        -> 1, 7
mysql> SELECT BIT_COUNT(X'40'), BIT_COUNT(_binary X'40');
        -> 1, 1

12.13 Encryption and Compression Functions

Table 12.17 Encryption Functions

Name	Description
`AES_DECRYPT()`	Decrypt using AES
`AES_ENCRYPT()`	Encrypt using AES
`ASYMMETRIC_DECRYPT()`	Decrypt ciphertext using private or public key
`ASYMMETRIC_DERIVE()`	Derive symmetric key from asymmetric keys
`ASYMMETRIC_ENCRYPT()`	Encrypt cleartext using private or public key
`ASYMMETRIC_SIGN()`	Generate signature from digest
`ASYMMETRIC_VERIFY()`	Verify that signature matches digest
`COMPRESS()`	Return result as a binary string
`CREATE_ASYMMETRIC_PRIV_KEY()`	Create private key
`CREATE_ASYMMETRIC_PUB_KEY()`	Create public key
`CREATE_DH_PARAMETERS()`	Generate shared DH secret
`CREATE_DIGEST()`	Generate digest from string
`DECODE()`	Decodes a string encrypted using ENCODE()
`DES_DECRYPT()`	Decrypt a string
`DES_ENCRYPT()`	Encrypt a string
`ENCODE()`	Encode a string
`ENCRYPT()`	Encrypt a string
`MD5()`	Calculate MD5 checksum
`PASSWORD()`	Calculate and return a password string
`RANDOM_BYTES()`	Return a random byte vector
`SHA1()`, `SHA()`	Calculate an SHA-1 160-bit checksum
`SHA2()`	Calculate an SHA-2 checksum
`STATEMENT_DIGEST()`	Compute statement digest hash value
`STATEMENT_DIGEST_TEXT()`	Compute normalized statement digest
`UNCOMPRESS()`	Uncompress a string compressed
`UNCOMPRESSED_LENGTH()`	Return the length of a string before compression
`VALIDATE_PASSWORD_STRENGTH()`	Determine strength of password

Many encryption and compression functions return strings for which the result might contain arbitrary byte values. If you want to store these results, use a column with a VARBINARY or BLOB binary string data type. This will avoid potential problems with trailing space removal or character set conversion that would change data values, such as may occur if you use a nonbinary string data type (CHAR, VARCHAR, TEXT).

Some encryption functions return strings of ASCII characters: MD5(), SHA(), SHA1(), SHA2(), STATEMENT_DIGEST(), STATEMENT_DIGEST_TEXT(). Their return value is a string that has a character set and collation determined by the character_set_connection and collation_connection system variables. This is a nonbinary string unless the character set is binary.

If an application stores values from a function such as MD5() or SHA1() that returns a string of hex digits, more efficient storage and comparisons can be obtained by converting the hex representation to binary using UNHEX() and storing the result in a BINARY(N) column. Each pair of hexadecimal digits requires one byte in binary form, so the value of N depends on the length of the hex string. N is 16 for an MD5() value and 20 for a SHA1() value. For SHA2(), N ranges from 28 to 32 depending on the argument specifying the desired bit length of the result.

The size penalty for storing the hex string in a CHAR column is at least two times, up to eight times if the value is stored in a column that uses the utf8 character set (where each character uses 4 bytes). Storing the string also results in slower comparisons because of the larger values and the need to take character set collation rules into account.

Suppose that an application stores MD5() string values in a CHAR(32) column:

CREATE TABLE md5_tbl (md5_val CHAR(32), ...);
INSERT INTO md5_tbl (md5_val, ...) VALUES(MD5('abcdef'), ...);

To convert hex strings to more compact form, modify the application to use UNHEX() and BINARY(16) instead as follows:

CREATE TABLE md5_tbl (md5_val BINARY(16), ...);
INSERT INTO md5_tbl (md5_val, ...) VALUES(UNHEX(MD5('abcdef')), ...);

Applications should be prepared to handle the very rare case that a hashing function produces the same value for two different input values. One way to make collisions detectable is to make the hash column a primary key.

Note

Exploits for the MD5 and SHA-1 algorithms have become known. You may wish to consider using another one-way encryption function described in this section instead, such as SHA2().

Caution

Passwords or other sensitive values supplied as arguments to encryption functions are sent in cleartext to the MySQL server unless an SSL connection is used. Also, such values will appear in any MySQL logs to which they are written. To avoid these types of exposure, applications can encrypt sensitive values on the client side before sending them to the server. The same considerations apply to encryption keys. To avoid exposing these, applications can use stored procedures to encrypt and decrypt values on the server side.

AES_DECRYPT(crypt_str,key_str[,init_vector])
This function decrypts data using the official AES (Advanced Encryption Standard) algorithm. For more information, see the description of AES_ENCRYPT().
The optional initialization vector argument, init_vector. Statements that use AES_DECRYPT() are unsafe for statement-based replication.

AES_ENCRYPT(str,key_str[,init_vector])

AES_ENCRYPT() and AES_DECRYPT() implement encryption and decryption of data using the official AES (Advanced Encryption Standard) algorithm, previously known as “Rijndael.” The AES standard permits various key lengths. By default these functions implement AES with a 128-bit key length. Key lengths of 196 or 256 bits can be used, as described later. The key length is a trade off between performance and security.

AES_ENCRYPT() encrypts the string str using the key string key_str and returns a binary string containing the encrypted output. AES_DECRYPT() decrypts the encrypted string crypt_str using the key string key_str and returns the original cleartext string. If either function argument is NULL, the function returns NULL.

The str and crypt_str arguments can be any length, and padding is automatically added to str so it is a multiple of a block as required by block-based algorithms such as AES. This padding is automatically removed by the AES_DECRYPT() function. The length of crypt_str can be calculated using this formula:

16 * (trunc(string_length / 16) + 1)

For a key length of 128 bits, the most secure way to pass a key to the key_str argument is to create a truly random 128-bit value and pass it as a binary value. For example:

INSERT INTO t
VALUES (1,AES_ENCRYPT('text',UNHEX('F3229A0B371ED2D9441B830D21A390C3')));

A passphrase can be used to generate an AES key by hashing the passphrase. For example:

INSERT INTO t
VALUES (1,AES_ENCRYPT('text', UNHEX(SHA2('My secret passphrase',512))));

Do not pass a password or passphrase directly to crypt_str, hash it first. Previous versions of this documentation suggested the former approach, but it is no longer recommended as the examples shown here are more secure.

If AES_DECRYPT() detects invalid data or incorrect padding, it returns NULL. However, it is possible for AES_DECRYPT() to return a non-NULL value (possibly garbage) if the input data or the key is invalid.

AES_ENCRYPT() and AES_DECRYPT() permit control of the block encryption mode and take an optional init_vector initialization vector argument:

The block_encryption_mode system variable controls the mode for block-based encryption algorithms. Its default value is aes-128-ecb, which signifies encryption using a key length of 128 bits and ECB mode. For a description of the permitted values of this variable, see Section 5.1.7, “Server System Variables”.
The optional init_vector argument provides an initialization vector for block encryption modes that require it.

For modes that require the optional init_vector argument, it must be 16 bytes or longer (bytes in excess of 16 are ignored). An error occurs if init_vector is missing.

For modes that do not require init_vector, it is ignored and a warning is generated if it is specified.

A random string of bytes to use for the initialization vector can be produced by calling RANDOM_BYTES(16). For encryption modes that require an initialization vector, the same vector must be used for encryption and decryption.

mysql> SET block_encryption_mode = 'aes-256-cbc';
mysql> SET @key_str = SHA2('My secret passphrase',512);
mysql> SET @init_vector = RANDOM_BYTES(16);
mysql> SET @crypt_str = AES_ENCRYPT('text',@key_str,@init_vector);
mysql> SELECT AES_DECRYPT(@crypt_str,@key_str,@init_vector);
+-----------------------------------------------+
| AES_DECRYPT(@crypt_str,@key_str,@init_vector) |
+-----------------------------------------------+
| text                                          |
+-----------------------------------------------+

The following table lists each permitted block encryption mode, the SSL libraries that support it, and whether the initialization vector argument is required.

Block Encryption Mode	SSL Libraries that Support Mode	Initialization Vector Required
ECB	OpenSSL, wolfSSL	No
CBC	OpenSSL, wolfSSL	Yes
CFB1	OpenSSL	Yes
CFB8	OpenSSL	Yes
CFB128	OpenSSL	Yes
OFB	OpenSSL	Yes

Statements that use AES_ENCRYPT() or AES_DECRYPT() are unsafe for statement-based replication.

COMPRESS(string_to_compress)
Compresses a string and returns the result as a binary string. This function requires MySQL to have been compiled with a compression library such as zlib. Otherwise, the return value is always NULL. The compressed string can be uncompressed with UNCOMPRESS().
```
mysql> SELECT LENGTH(COMPRESS(REPEAT('a',1000)));
        -> 21
mysql> SELECT LENGTH(COMPRESS(''));
        -> 0
mysql> SELECT LENGTH(COMPRESS('a'));
        -> 13
mysql> SELECT LENGTH(COMPRESS(REPEAT('a',16)));
        -> 15
```
The compressed string contents are stored the following way:
- Empty strings are stored as empty strings.
- Nonempty strings are stored as a 4-byte length of the uncompressed string (low byte first), followed by the compressed string. If the string ends with space, an extra . character is added to avoid problems with endspace trimming should the result be stored in a CHAR or VARCHAR column. (However, use of nonbinary string data types such as CHAR or VARCHAR to store compressed strings is not recommended anyway because character set conversion may occur. Use a VARBINARY or BLOB binary string column instead.)
DECODE(crypt_str,pass_str)
This function was removed in MySQL 8.0.3.
Consider using AES_ENCRYPT() and AES_DECRYPT() instead.
DES_DECRYPT(crypt_str[,key_str])
This function was removed in MySQL 8.0.3.
Consider using AES_ENCRYPT() and AES_DECRYPT() instead.
DES_ENCRYPT(str[,{key_num|key_str}])
This function was removed in MySQL 8.0.3.
Consider using AES_ENCRYPT() and AES_DECRYPT() instead.
ENCODE(str,pass_str)
This function was removed in MySQL 8.0.3.
Consider using AES_ENCRYPT() and AES_DECRYPT() instead.
ENCRYPT(str[,salt])
This function was removed in MySQL 8.0.3. For one-way hashing, consider using SHA2() instead.
MD5(str)
Calculates an MD5 128-bit checksum for the string. The value is returned as a string of 32 hexadecimal digits, or NULL if the argument was NULL. The return value can, for example, be used as a hash key. See the notes at the beginning of this section about storing hash values efficiently.
The return value is a string in the connection character set.
If FIPS mode is enabled, MD5() returns NULL. See Section 6.6, “FIPS Support”.
```
mysql> SELECT MD5('testing');
        -> 'ae2b1fca515949e5d54fb22b8ed95575'
```
This is the “RSA Data Security, Inc. MD5 Message-Digest Algorithm.”
See the note regarding the MD5 algorithm at the beginning this section.
PASSWORD(str)
This function was removed in MySQL 8.0.11.
RANDOM_BYTES(len)
This function returns a binary string of len random bytes generated using the random number generator of the SSL library. Permitted values of len range from 1 to 1024. For values outside that range, RANDOM_BYTES() generates a warning and returns NULL.
RANDOM_BYTES() can be used to provide the initialization vector for the AES_DECRYPT() and AES_ENCRYPT() functions. For use in that context, len must be at least 16. Larger values are permitted, but bytes in excess of 16 are ignored.
RANDOM_BYTES() generates a random value, which makes its result nondeterministic. Consequently, statements that use this function are unsafe for statement-based replication.
SHA1(str), SHA(str)
Calculates an SHA-1 160-bit checksum for the string, as described in RFC 3174 (Secure Hash Algorithm). The value is returned as a string of 40 hexadecimal digits, or NULL if the argument was NULL. One of the possible uses for this function is as a hash key. See the notes at the beginning of this section about storing hash values efficiently. You can also use SHA1() as a cryptographic function for storing passwords. SHA() is synonymous with SHA1().
The return value is a string in the connection character set.
```
mysql> SELECT SHA1('abc');
        -> 'a9993e364706816aba3e25717850c26c9cd0d89d'
```
SHA1() can be considered a cryptographically more secure equivalent of MD5(). However, see the note regarding the MD5 and SHA-1 algorithms at the beginning this section.
SHA2(str, hash_length)
Calculates the SHA-2 family of hash functions (SHA-224, SHA-256, SHA-384, and SHA-512). The first argument is the cleartext string to be hashed. The second argument indicates the desired bit length of the result, which must have a value of 224, 256, 384, 512, or 0 (which is equivalent to 256). If either argument is NULL or the hash length is not one of the permitted values, the return value is NULL. Otherwise, the function result is a hash value containing the desired number of bits. See the notes at the beginning of this section about storing hash values efficiently.
The return value is a string in the connection character set.
```
mysql> SELECT SHA2('abc', 224);
        -> '23097d223405d8228642a477bda255b32aadbce4bda0b3f7e36c9da7'
```
This function works only if MySQL has been configured with SSL support. See Section 6.4, “Using Encrypted Connections”.
SHA2() can be considered cryptographically more secure than MD5() or SHA1().

STATEMENT_DIGEST(statement)

Given an SQL statement as a string, returns the statement digest hash value as a string in the connection character set, or NULL if the argument is NULL. The related STATEMENT_DIGEST_TEXT() function returns the normalized statement digest. For information about statement digesting, see Section 25.9, “Performance Schema Statement Digests and Sampling”.

Both functions use the MySQL parser to parse the statement. If parsing fails, an error occurs. The error message includes the parse error only if the statement is provided as a literal string.

The max_digest_length system variable determines the maximum number of bytes available to these functions for computing normalized statement digests.

mysql> SET @stmt = 'SELECT * FROM mytable WHERE cola = 10 AND colb = 20';
mysql> SELECT STATEMENT_DIGEST(@stmt);
+------------------------------------------------------------------+
| STATEMENT_DIGEST(@stmt)                                          |
+------------------------------------------------------------------+
| 3bb95eeade896657c4526e74ff2a2862039d0a0fe8a9e7155b5fe492cbd78387 |
+------------------------------------------------------------------+
mysql> SELECT STATEMENT_DIGEST_TEXT(@stmt);
+----------------------------------------------------------+
| STATEMENT_DIGEST_TEXT(@stmt)                             |
+----------------------------------------------------------+
| SELECT * FROM `mytable` WHERE `cola` = ? AND `colb` = ?  |
+----------------------------------------------------------+

STATEMENT_DIGEST_TEXT(statement)
Given an SQL statement as a string, returns the normalized statement digest as a string in the connection character set, or NULL if the argument is NULL. For additional discussion and examples, see the description of the related STATEMENT_DIGEST() function.
UNCOMPRESS(string_to_uncompress)
Uncompresses a string compressed by the COMPRESS() function. If the argument is not a compressed value, the result is NULL. This function requires MySQL to have been compiled with a compression library such as zlib. Otherwise, the return value is always NULL.
```
mysql> SELECT UNCOMPRESS(COMPRESS('any string'));
        -> 'any string'
mysql> SELECT UNCOMPRESS('any string');
        -> NULL
```
UNCOMPRESSED_LENGTH(compressed_string)
Returns the length that the compressed string had before being compressed.
```
mysql> SELECT UNCOMPRESSED_LENGTH(COMPRESS(REPEAT('a',30)));
        -> 30
```

VALIDATE_PASSWORD_STRENGTH(str)

Given an argument representing a cleartext password, this function returns an integer to indicate how strong the password is. The return value ranges from 0 (weak) to 100 (strong).

Password assessment by VALIDATE_PASSWORD_STRENGTH() is done by the validate_password component. If that component is not installed, the function always returns 0. For information about installing validate_password, see Section 6.5.3, “The Password Validation Component”. To examine or configure the parameters that affect password testing, check or set the system variables implemented by validate_password. See Section 6.5.3.2, “Password Validation Options and Variables”.

The password is subjected to increasingly strict tests and the return value reflects which tests were satisfied, as shown in the following table. In addition, if the validate_password.check_user_name system variable is enabled and the password matches the user name, VALIDATE_PASSWORD_STRENGTH() returns 0 regardless of how other validate_password system variables are set.

Password Test	Return Value
Length < 4	0
Length ≥ 4 and < `validate_password.length`	25
Satisfies policy 1 (`LOW`)	50
Satisfies policy 2 (`MEDIUM`)	75
Satisfies policy 3 (`STRONG`)	100

12.14 Information Functions

Table 12.18 Information Functions

Name	Description
`BENCHMARK()`	Repeatedly execute an expression
`CHARSET()`	Return the character set of the argument
`COERCIBILITY()`	Return the collation coercibility value of the string argument
`COLLATION()`	Return the collation of the string argument
`CONNECTION_ID()`	Return the connection ID (thread ID) for the connection
`CURRENT_ROLE()`	Returns the current active roles
`CURRENT_USER()`, `CURRENT_USER`	The authenticated user name and host name
`DATABASE()`	Return the default (current) database name
`FOUND_ROWS()`	For a SELECT with a LIMIT clause, the number of rows that would be returned were there no LIMIT clause
`ICU_VERSION()`	ICU library version
`LAST_INSERT_ID()`	Value of the AUTOINCREMENT column for the last INSERT
`ROLES_GRAPHML()`	Returns a GraphML document representing memory role subgraphs
`ROW_COUNT()`	The number of rows updated
`SCHEMA()`	Synonym for DATABASE()
`SESSION_USER()`	Synonym for USER()
`SYSTEM_USER()`	Synonym for USER()
`USER()`	The user name and host name provided by the client
`VERSION()`	Return a string that indicates the MySQL server version

BENCHMARK(count,expr)
The BENCHMARK() function executes the expression expr repeatedly count times. It may be used to time how quickly MySQL processes the expression. The result value is always 0. The intended use is from within the mysql client, which reports query execution times:
```
mysql> SELECT BENCHMARK(1000000,AES_ENCRYPT('hello','goodbye'));
+---------------------------------------------------+
| BENCHMARK(1000000,AES_ENCRYPT('hello','goodbye')) |
+---------------------------------------------------+
|                                                 0 |
+---------------------------------------------------+
1 row in set (4.74 sec)
```
The time reported is elapsed time on the client end, not CPU time on the server end. It is advisable to execute BENCHMARK() several times, and to interpret the result with regard to how heavily loaded the server machine is.
BENCHMARK() is intended for measuring the runtime performance of scalar expressions, which has some significant implications for the way that you use it and interpret the results:
- Only scalar expressions can be used. Although the expression can be a subquery, it must return a single column and at most a single row. For example, BENCHMARK(10, (SELECT * FROM t)) will fail if the table t has more than one column or more than one row.
- Executing a SELECT expr statement N times differs from executing SELECT BENCHMARK(N, expr) in terms of the amount of overhead involved. The two have very different execution profiles and you should not expect them to take the same amount of time. The former involves the parser, optimizer, table locking, and runtime evaluation N times each. The latter involves only runtime evaluation N times, and all the other components just once. Memory structures already allocated are reused, and runtime optimizations such as local caching of results already evaluated for aggregate functions can alter the results. Use of BENCHMARK() thus measures performance of the runtime component by giving more weight to that component and removing the “noise” introduced by the network, parser, optimizer, and so forth.

CHARSET(str)

Returns the character set of the string argument.

mysql> SELECT CHARSET('abc');
        -> 'utf8'
mysql> SELECT CHARSET(CONVERT('abc' USING latin1));
        -> 'latin1'
mysql> SELECT CHARSET(USER());
        -> 'utf8'

COERCIBILITY(str)

Returns the collation coercibility value of the string argument.

mysql> SELECT COERCIBILITY('abc' COLLATE utf8_swedish_ci);
        -> 0
mysql> SELECT COERCIBILITY(USER());
        -> 3
mysql> SELECT COERCIBILITY('abc');
        -> 4
mysql> SELECT COERCIBILITY(1000);
        -> 5

The return values have the meanings shown in the following table. Lower values have higher precedence.

Coercibility	Meaning	Example
`0`	Explicit collation	Value with `COLLATE` clause
`1`	No collation	Concatenation of strings with different collations
`2`	Implicit collation	Column value, stored routine parameter or local variable
`3`	System constant	`USER()` return value
`4`	Coercible	Literal string
`5`	Numeric	Numeric or temporal value
`5`	Ignorable	`NULL` or an expression derived from `NULL`

For more information, see Section 10.8.4, “Collation Coercibility in Expressions”.

COLLATION(str)

Returns the collation of the string argument.

mysql> SELECT COLLATION('abc');
        -> 'utf8_general_ci'
mysql> SELECT COLLATION(_utf8mb4'abc');
        -> 'utf8mb4_0900_ai_ci'
mysql> SELECT COLLATION(_latin1'abc');
        -> 'latin1_swedish_ci'

CONNECTION_ID()
Returns the connection ID (thread ID) for the connection. Every connection has an ID that is unique among the set of currently connected clients.
The value returned by CONNECTION_ID() is the same type of value as displayed in the ID column of the INFORMATION_SCHEMA.PROCESSLIST table, the Id column of SHOW PROCESSLIST output, and the PROCESSLIST_ID column of the Performance Schema threads table.
```
mysql> SELECT CONNECTION_ID();
        -> 23786
```
CURRENT_ROLE()
Returns a utf8 string containing the current active roles for the current session, separated by commas, or NONE if there are none. The value reflects the setting of the sql_quote_show_create system variable.
Suppose that an account is granted roles as follows:
```
GRANT 'r1', 'r2' TO 'u1'@'localhost';
SET DEFAULT ROLE ALL TO 'u1'@'localhost';
```
In sessions for u1, the initial CURRENT_ROLE() value names the default account roles. Using SET ROLE changes that:
```
mysql> SELECT CURRENT_ROLE();
+-------------------+
| CURRENT_ROLE()    |
+-------------------+
| `r1`@`%`,`r2`@`%` |
+-------------------+
mysql> SET ROLE 'r1'; SELECT CURRENT_ROLE();
+----------------+
| CURRENT_ROLE() |
+----------------+
| `r1`@`%`       |
+----------------+
```
CURRENT_USER, CURRENT_USER()
Returns the user name and host name combination for the MySQL account that the server used to authenticate the current client. This account determines your access privileges. The return value is a string in the utf8 character set.
The value of CURRENT_USER() can differ from the value of USER().
```
mysql> SELECT USER();
        -> 'davida@localhost'
mysql> SELECT * FROM mysql.user;
ERROR 1044: Access denied for user ''@'localhost' to
database 'mysql'
mysql> SELECT CURRENT_USER();
        -> '@localhost'
```
The example illustrates that although the client specified a user name of davida (as indicated by the value of the USER() function), the server authenticated the client using an anonymous user account (as seen by the empty user name part of the CURRENT_USER() value). One way this might occur is that there is no account listed in the grant tables for davida.
Within a stored program or view, CURRENT_USER() returns the account for the user who defined the object (as given by its DEFINER value) unless defined with the SQL SECURITY INVOKER characteristic. In the latter case, CURRENT_USER() returns the object's invoker.
Triggers and events have no option to define the SQL SECURITY characteristic, so for these objects, CURRENT_USER() returns the account for the user who defined the object. To return the invoker, use USER() or SESSION_USER().
The following statements support use of the CURRENT_USER() function to take the place of the name of (and, possibly, a host for) an affected user or a definer; in such cases, CURRENT_USER() is expanded where and as needed:
For information about the implications that this expansion of CURRENT_USER() has for replication, see Section 17.4.1.8, “Replication of CURRENT_USER()”.
DATABASE()
Returns the default (current) database name as a string in the utf8 character set. If there is no default database, DATABASE() returns NULL. Within a stored routine, the default database is the database that the routine is associated with, which is not necessarily the same as the database that is the default in the calling context.
```
mysql> SELECT DATABASE();
        -> 'test'
```
If there is no default database, DATABASE() returns NULL.
FOUND_ROWS()
A SELECT statement may include a LIMIT clause to restrict the number of rows the server returns to the client. In some cases, it is desirable to know how many rows the statement would have returned without the LIMIT, but without running the statement again. To obtain this row count, include an SQL_CALC_FOUND_ROWS option in the SELECT statement, and then invoke FOUND_ROWS() afterward:
```
mysql> SELECT SQL_CALC_FOUND_ROWS * FROM tbl_name
    -> WHERE id > 100 LIMIT 10;
mysql> SELECT FOUND_ROWS();
```
The second SELECT returns a number indicating how many rows the first SELECT would have returned had it been written without the LIMIT clause.
In the absence of the SQL_CALC_FOUND_ROWS option in the most recent successful SELECT statement, FOUND_ROWS() returns the number of rows in the result set returned by that statement. If the statement includes a LIMIT clause, FOUND_ROWS() returns the number of rows up to the limit. For example, FOUND_ROWS() returns 10 or 60, respectively, if the statement includes LIMIT 10 or LIMIT 50, 10.
The row count available through FOUND_ROWS() is transient and not intended to be available past the statement following the SELECT SQL_CALC_FOUND_ROWS statement. If you need to refer to the value later, save it:
```
mysql> SELECT SQL_CALC_FOUND_ROWS * FROM ... ;
mysql> SET @rows = FOUND_ROWS();
```
If you are using SELECT SQL_CALC_FOUND_ROWS, MySQL must calculate how many rows are in the full result set. However, this is faster than running the query again without LIMIT, because the result set need not be sent to the client.
SQL_CALC_FOUND_ROWS and FOUND_ROWS() can be useful in situations when you want to restrict the number of rows that a query returns, but also determine the number of rows in the full result set without running the query again. An example is a Web script that presents a paged display containing links to the pages that show other sections of a search result. Using FOUND_ROWS() enables you to determine how many other pages are needed for the rest of the result.
The use of SQL_CALC_FOUND_ROWS and FOUND_ROWS() is more complex for UNION statements than for simple SELECT statements, because LIMIT may occur at multiple places in a UNION. It may be applied to individual SELECT statements in the UNION, or global to the UNION result as a whole.
The intent of SQL_CALC_FOUND_ROWS for UNION is that it should return the row count that would be returned without a global LIMIT. The conditions for use of SQL_CALC_FOUND_ROWS with UNION are:
- The SQL_CALC_FOUND_ROWS keyword must appear in the first SELECT of the UNION.
- The value of FOUND_ROWS() is exact only if UNION ALL is used. If UNION without ALL is used, duplicate removal occurs and the value of FOUND_ROWS() is only approximate.
- If no LIMIT is present in the UNION, SQL_CALC_FOUND_ROWS is ignored and returns the number of rows in the temporary table that is created to process the UNION.
Beyond the cases described here, the behavior of FOUND_ROWS() is undefined (for example, its value following a SELECT statement that fails with an error).

Important

FOUND_ROWS() is not replicated reliably using statement-based replication. This function is automatically replicated using row-based replication.
ICU_VERSION()
The version of the International Components for Unicode (ICU) library used to support regular expression operations (see Section 12.5.2, “Regular Expressions”). This function is primarily intended for use in test cases.
LAST_INSERT_ID(), LAST_INSERT_ID(expr)
With no argument, LAST_INSERT_ID() returns a BIGINT UNSIGNED (64-bit) value representing the first automatically generated value successfully inserted for an AUTO_INCREMENT column as a result of the most recently executed INSERT statement. The value of LAST_INSERT_ID() remains unchanged if no rows are successfully inserted.
With an argument, LAST_INSERT_ID() returns an unsigned integer.
For example, after inserting a row that generates an AUTO_INCREMENT value, you can get the value like this:
```
mysql> SELECT LAST_INSERT_ID();
        -> 195
```
The currently executing statement does not affect the value of LAST_INSERT_ID(). Suppose that you generate an AUTO_INCREMENT value with one statement, and then refer to LAST_INSERT_ID() in a multiple-row INSERT statement that inserts rows into a table with its own AUTO_INCREMENT column. The value of LAST_INSERT_ID() will remain stable in the second statement; its value for the second and later rows is not affected by the earlier row insertions. (However, if you mix references to LAST_INSERT_ID() and LAST_INSERT_ID(expr), the effect is undefined.)
If the previous statement returned an error, the value of LAST_INSERT_ID() is undefined. For transactional tables, if the statement is rolled back due to an error, the value of LAST_INSERT_ID() is left undefined. For manual ROLLBACK, the value of LAST_INSERT_ID() is not restored to that before the transaction; it remains as it was at the point of the ROLLBACK.
Within the body of a stored routine (procedure or function) or a trigger, the value of LAST_INSERT_ID() changes the same way as for statements executed outside the body of these kinds of objects. The effect of a stored routine or trigger upon the value of LAST_INSERT_ID() that is seen by following statements depends on the kind of routine:
- If a stored procedure executes statements that change the value of LAST_INSERT_ID(), the changed value is seen by statements that follow the procedure call.
- For stored functions and triggers that change the value, the value is restored when the function or trigger ends, so following statements will not see a changed value.
The ID that was generated is maintained in the server on a per-connection basis. This means that the value returned by the function to a given client is the first AUTO_INCREMENT value generated for most recent statement affecting an AUTO_INCREMENT column by that client. This value cannot be affected by other clients, even if they generate AUTO_INCREMENT values of their own. This behavior ensures that each client can retrieve its own ID without concern for the activity of other clients, and without the need for locks or transactions.
The value of LAST_INSERT_ID() is not changed if you set the AUTO_INCREMENT column of a row to a non-“magic” value (that is, a value that is not NULL and not 0).

Important

If you insert multiple rows using a single INSERT statement, LAST_INSERT_ID() returns the value generated for the first inserted row only. The reason for this is to make it possible to reproduce easily the same INSERT statement against some other server.

For example:
```
mysql> USE test;

mysql> CREATE TABLE t (
       id INT AUTO_INCREMENT NOT NULL PRIMARY KEY,
       name VARCHAR(10) NOT NULL
       );

mysql> INSERT INTO t VALUES (NULL, 'Bob');

mysql> SELECT * FROM t;
+----+------+
| id | name |
+----+------+
|  1 | Bob  |
+----+------+

mysql> SELECT LAST_INSERT_ID();
+------------------+
| LAST_INSERT_ID() |
+------------------+
|                1 |
+------------------+

mysql> INSERT INTO t VALUES
       (NULL, 'Mary'), (NULL, 'Jane'), (NULL, 'Lisa');

mysql> SELECT * FROM t;
+----+------+
| id | name |
+----+------+
|  1 | Bob  |
|  2 | Mary |
|  3 | Jane |
|  4 | Lisa |
+----+------+

mysql> SELECT LAST_INSERT_ID();
+------------------+
| LAST_INSERT_ID() |
+------------------+
|                2 |
+------------------+
```
Although the second INSERT statement inserted three new rows into t, the ID generated for the first of these rows was 2, and it is this value that is returned by LAST_INSERT_ID() for the following SELECT statement.
If you use INSERT IGNORE and the row is ignored, the LAST_INSERT_ID() remains unchanged from the current value (or 0 is returned if the connection has not yet performed a successful INSERT) and, for non-transactional tables, the AUTO_INCREMENT counter is not incremented. For InnoDB tables, the AUTO_INCREMENT counter is incremented if innodb_autoinc_lock_mode is set to 1 or 2, as demonstrated in the following example:
```
mysql> USE test;

mysql> SELECT @@innodb_autoinc_lock_mode;
+----------------------------+
| @@innodb_autoinc_lock_mode |
+----------------------------+
|                          1 |
+----------------------------+

mysql> CREATE TABLE `t` (
       `id` INT(11) NOT NULL AUTO_INCREMENT,
       `val` INT(11) DEFAULT NULL,
       PRIMARY KEY (`id`),
       UNIQUE KEY `i1` (`val`)
       ) ENGINE=InnoDB DEFAULT CHARSET=latin1;

# Insert two rows

mysql> INSERT INTO t (val) VALUES (1),(2);

# With auto_increment_offset=1, the inserted rows
# result in an AUTO_INCREMENT value of 3

mysql> SHOW CREATE TABLE t\G
*************************** 1. row ***************************
       Table: t
Create Table: CREATE TABLE `t` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `val` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`),
  UNIQUE KEY `i1` (`val`)
) ENGINE=InnoDB AUTO_INCREMENT=3 DEFAULT CHARSET=latin1

# LAST_INSERT_ID() returns the first automatically generated
# value that is successfully inserted for the AUTO_INCREMENT column

mysql> SELECT LAST_INSERT_ID();
+------------------+
| LAST_INSERT_ID() |
+------------------+
|                1 |
+------------------+

# The attempted insertion of duplicate rows fail but errors are ignored   

mysql> INSERT IGNORE INTO t (val) VALUES (1),(2);
Query OK, 0 rows affected (0.00 sec)
Records: 2  Duplicates: 2  Warnings: 0

# With innodb_autoinc_lock_mode=1, the AUTO_INCREMENT counter
# is incremented for the ignored rows

mysql> SHOW CREATE TABLE t\G
*************************** 1. row ***************************
       Table: t
Create Table: CREATE TABLE `t` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `val` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`),
  UNIQUE KEY `i1` (`val`)
) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=latin1

# The LAST_INSERT_ID is unchanged because the previous insert was unsuccessful

mysql> SELECT LAST_INSERT_ID();
+------------------+
| LAST_INSERT_ID() |
+------------------+
|                1 |
+------------------+
```
For more information, see Section 15.8.1.5, “AUTO_INCREMENT Handling in InnoDB”.
If expr is given as an argument to LAST_INSERT_ID(), the value of the argument is returned by the function and is remembered as the next value to be returned by LAST_INSERT_ID(). This can be used to simulate sequences:
1. Create a table to hold the sequence counter and initialize it:
```
mysql> CREATE TABLE sequence (id INT NOT NULL);
mysql> INSERT INTO sequence VALUES (0);
```
2. Use the table to generate sequence numbers like this:
```
mysql> UPDATE sequence SET id=LAST_INSERT_ID(id+1);
mysql> SELECT LAST_INSERT_ID();
```
  The UPDATE statement increments the sequence counter and causes the next call to LAST_INSERT_ID() to return the updated value. The SELECT statement retrieves that value. The mysql_insert_id() C API function can also be used to get the value. See Section 27.7.7.38, “mysql_insert_id()”.
You can generate sequences without calling LAST_INSERT_ID(), but the utility of using the function this way is that the ID value is maintained in the server as the last automatically generated value. It is multi-user safe because multiple clients can issue the UPDATE statement and get their own sequence value with the SELECT statement (or mysql_insert_id()), without affecting or being affected by other clients that generate their own sequence values.
Note that mysql_insert_id() is only updated after INSERT and UPDATE statements, so you cannot use the C API function to retrieve the value for LAST_INSERT_ID(expr) after executing other SQL statements like SELECT or SET.

ROLES_GRAPHML()

Returns a utf8 string containing a GraphML document representing memory role subgraphs. The ROLE_ADMIN or SUPER privilege is required to see content in the <graphml> element. Otherwise, the result shows only an empty element:

mysql> SELECT ROLES_GRAPHML();
+---------------------------------------------------+
| ROLES_GRAPHML()                                   |
+---------------------------------------------------+
| <?xml version="1.0" encoding="UTF-8"?><graphml /> |
+---------------------------------------------------+

ROW_COUNT()
ROW_COUNT() returns a value as follows:
- DDL statements: 0. This applies to statements such as CREATE TABLE or DROP TABLE.
- DML statements other than SELECT: The number of affected rows. This applies to statements such as UPDATE, INSERT, or DELETE (as before), but now also to statements such as ALTER TABLE and LOAD DATA INFILE.
- SELECT: -1 if the statement returns a result set, or the number of rows “affected” if it does not. For example, for SELECT * FROM t1, ROW_COUNT() returns -1. For SELECT * FROM t1 INTO OUTFILE 'file_name', ROW_COUNT() returns the number of rows written to the file.
- SIGNAL statements: 0.
For UPDATE statements, the affected-rows value by default is the number of rows actually changed. If you specify the CLIENT_FOUND_ROWS flag to mysql_real_connect() when connecting to mysqld, the affected-rows value is the number of rows “found”; that is, matched by the WHERE clause.
For REPLACE statements, the affected-rows value is 2 if the new row replaced an old row, because in this case, one row was inserted after the duplicate was deleted.
For INSERT ... ON DUPLICATE KEY UPDATE statements, the affected-rows value per row is 1 if the row is inserted as a new row, 2 if an existing row is updated, and 0 if an existing row is set to its current values. If you specify the CLIENT_FOUND_ROWS flag, the affected-rows value is 1 (not 0) if an existing row is set to its current values.
The ROW_COUNT() value is similar to the value from the mysql_affected_rows() C API function and the row count that the mysql client displays following statement execution.
```
mysql> INSERT INTO t VALUES(1),(2),(3);
Query OK, 3 rows affected (0.00 sec)
Records: 3  Duplicates: 0  Warnings: 0

mysql> SELECT ROW_COUNT();
+-------------+
| ROW_COUNT() |
+-------------+
|           3 |
+-------------+
1 row in set (0.00 sec)

mysql> DELETE FROM t WHERE i IN(1,2);
Query OK, 2 rows affected (0.00 sec)

mysql> SELECT ROW_COUNT();
+-------------+
| ROW_COUNT() |
+-------------+
|           2 |
+-------------+
1 row in set (0.00 sec)
```
Important

ROW_COUNT() is not replicated reliably using statement-based replication. This function is automatically replicated using row-based replication.
SCHEMA()
This function is a synonym for DATABASE().
SESSION_USER()
SESSION_USER() is a synonym for USER().
SYSTEM_USER()
SYSTEM_USER() is a synonym for USER().
USER()
Returns the current MySQL user name and host name as a string in the utf8 character set.
```
mysql> SELECT USER();
        -> 'davida@localhost'
```
The value indicates the user name you specified when connecting to the server, and the client host from which you connected. The value can be different from that of CURRENT_USER().
VERSION()
Returns a string that indicates the MySQL server version. The string uses the utf8 character set. The value might have a suffix in addition to the version number. See the description of the version system variable in Section 5.1.7, “Server System Variables”.
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
```
mysql> SELECT VERSION();
        -> '8.0.13-standard'
```

12.15 Spatial Analysis Functions

12.15.1 Spatial Function Reference
12.15.2 Argument Handling by Spatial Functions
12.15.3 Functions That Create Geometry Values from WKT Values
12.15.4 Functions That Create Geometry Values from WKB Values
12.15.5 MySQL-Specific Functions That Create Geometry Values
12.15.6 Geometry Format Conversion Functions
12.15.7 Geometry Property Functions
12.15.8 Spatial Operator Functions
12.15.9 Functions That Test Spatial Relations Between Geometry Objects
12.15.10 Spatial Geohash Functions
12.15.11 Spatial GeoJSON Functions
12.15.12 Spatial Convenience Functions

MySQL provides functions to perform various operations on spatial data. These functions can be grouped into several major categories according to the type of operation they perform:

Functions that create geometries in various formats (WKT, WKB, internal)
Functions that convert geometries between formats
Functions that access qualitative or quantitative properties of a geometry
Functions that describe relations between two geometries
Functions that create new geometries from existing ones

For general background about MySQL support for using spatial data, see Section 11.5, “Spatial Data Types”.

12.15.1 Spatial Function Reference

The following table lists each spatial function and provides a short description of each one.

Table 12.19 Spatial Functions

Name	Description
`GeomCollection()`	Construct geometry collection from geometries
`GeometryCollection()`	Construct geometry collection from geometries
`LineString()`	Construct LineString from Point values
`MBRContains()`	Whether MBR of one geometry contains MBR of another
`MBRCoveredBy()`	Whether one MBR is covered by another
`MBRCovers()`	Whether one MBR covers another
`MBRDisjoint()`	Whether MBRs of two geometries are disjoint
`MBREquals()`	Whether MBRs of two geometries are equal
`MBRIntersects()`	Whether MBRs of two geometries intersect
`MBROverlaps()`	Whether MBRs of two geometries overlap
`MBRTouches()`	Whether MBRs of two geometries touch
`MBRWithin()`	Whether MBR of one geometry is within MBR of another
`MultiLineString()`	Contruct MultiLineString from LineString values
`MultiPoint()`	Construct MultiPoint from Point values
`MultiPolygon()`	Construct MultiPolygon from Polygon values
`Point()`	Construct Point from coordinates
`Polygon()`	Construct Polygon from LineString arguments
`ST_Area()`	Return Polygon or MultiPolygon area
`ST_AsBinary()`, `ST_AsWKB()`	Convert from internal geometry format to WKB
`ST_AsGeoJSON()`	Generate GeoJSON object from geometry
`ST_AsText()`, `ST_AsWKT()`	Convert from internal geometry format to WKT
`ST_Buffer()`	Return geometry of points within given distance from geometry
`ST_Buffer_Strategy()`	Produce strategy option for ST_Buffer()
`ST_Centroid()`	Return centroid as a point
`ST_Contains()`	Whether one geometry contains another
`ST_ConvexHull()`	Return convex hull of geometry
`ST_Crosses()`	Whether one geometry crosses another
`ST_Difference()`	Return point set difference of two geometries
`ST_Dimension()`	Dimension of geometry
`ST_Disjoint()`	Whether one geometry is disjoint from another
`ST_Distance()`	The distance of one geometry from another
`ST_Distance_Sphere()`	Minimum distance on earth between two geometries
`ST_EndPoint()`	End Point of LineString
`ST_Envelope()`	Return MBR of geometry
`ST_Equals()`	Whether one geometry is equal to another
`ST_ExteriorRing()`	Return exterior ring of Polygon
`ST_GeoHash()`	Produce a geohash value
`ST_GeomCollFromText()`, `ST_GeometryCollectionFromText()`, `ST_GeomCollFromTxt()`	Return geometry collection from WKT
`ST_GeomCollFromWKB()`, `ST_GeometryCollectionFromWKB()`	Return geometry collection from WKB
`ST_GeometryN()`	Return N-th geometry from geometry collection
`ST_GeometryType()`	Return name of geometry type
`ST_GeomFromGeoJSON()`	Generate geometry from GeoJSON object
`ST_GeomFromText()`, `ST_GeometryFromText()`	Return geometry from WKT
`ST_GeomFromWKB()`, `ST_GeometryFromWKB()`	Return geometry from WKB
`ST_InteriorRingN()`	Return N-th interior ring of Polygon
`ST_Intersection()`	Return point set intersection of two geometries
`ST_Intersects()`	Whether one geometry intersects another
`ST_IsClosed()`	Whether a geometry is closed and simple
`ST_IsEmpty()`	Placeholder function
`ST_IsSimple()`	Whether a geometry is simple
`ST_IsValid()`	Whether a geometry is valid
`ST_LatFromGeoHash()`	Return latitude from geohash value
`ST_Latitude()`	Return latitude of Point
`ST_Length()`	Return length of LineString
`ST_LineFromText()`, `ST_LineStringFromText()`	Construct LineString from WKT
`ST_LineFromWKB()`, `ST_LineStringFromWKB()`	Construct LineString from WKB
`ST_LongFromGeoHash()`	Return longitude from geohash value
`ST_Longitude()`	Return longitude of Point
`ST_MakeEnvelope()`	Rectangle around two points
`ST_MLineFromText()`, `ST_MultiLineStringFromText()`	Construct MultiLineString from WKT
`ST_MLineFromWKB()`, `ST_MultiLineStringFromWKB()`	Construct MultiLineString from WKB
`ST_MPointFromText()`, `ST_MultiPointFromText()`	Construct MultiPoint from WKT
`ST_MPointFromWKB()`, `ST_MultiPointFromWKB()`	Construct MultiPoint from WKB
`ST_MPolyFromText()`, `ST_MultiPolygonFromText()`	Construct MultiPolygon from WKT
`ST_MPolyFromWKB()`, `ST_MultiPolygonFromWKB()`	Construct MultiPolygon from WKB
`ST_NumGeometries()`	Return number of geometries in geometry collection
`ST_NumInteriorRing()`, `ST_NumInteriorRings()`	Return number of interior rings in Polygon
`ST_NumPoints()`	Return number of points in LineString
`ST_Overlaps()`	Whether one geometry overlaps another
`ST_PointFromGeoHash()`	Convert geohash value to POINT value
`ST_PointFromText()`	Construct Point from WKT
`ST_PointFromWKB()`	Construct Point from WKB
`ST_PointN()`	Return N-th point from LineString
`ST_PolyFromText()`, `ST_PolygonFromText()`	Construct Polygon from WKT
`ST_PolyFromWKB()`, `ST_PolygonFromWKB()`	Construct Polygon from WKB
`ST_Simplify()`	Return simplified geometry
`ST_SRID()`	Return spatial reference system ID for geometry
`ST_StartPoint()`	Start Point of LineString
`ST_SwapXY()`	Return argument with X/Y coordinates swapped
`ST_SymDifference()`	Return point set symmetric difference of two geometries
`ST_Touches()`	Whether one geometry touches another
`ST_Union()`	Return point set union of two geometries
`ST_Validate()`	Return validated geometry
`ST_Within()`	Whether one geometry is within another
`ST_X()`	Return X coordinate of Point
`ST_Y()`	Return Y coordinate of Point

12.15.2 Argument Handling by Spatial Functions

Spatial values, or geometries, have the properties described at Section 11.5.2.2, “Geometry Class”. The following discussion lists general spatial function argument-handling characteristics. Specific functions or groups of functions may have additional argument-handling characteristics, as discussed in the sections where those function descriptions occur.

Spatial functions are defined only for valid geometry values.

The spatial reference identifier (SRID) of a geometry identifies the coordinate space in which the geometry is defined. In MySQL, the SRID value is an integer associated with the geometry value. The maximum usable SRID value is 2³²−1. If a larger value is given, only the lower 32 bits are used.

SRID 0 represents an infinite flat Cartesian plane with no units assigned to its axes. To ensure SRID 0 behavior, create geometry values using SRID 0. SRID 0 is the default for new geometry values if no SRID is specified.

Geometry values produced by any spatial function inherit the SRID of the geometry arguments.

Spatial functions that take multiple geometry arguments require those arguments to have the same SRID value (that is, same value in the lower 32 bits). Assuming equal SRIDs, spatial functions do nothing with them after performing the equality check; geometry values are implicitly handled using Cartesian coordinates (SRID 0). If a spatial function returns ER_GIS_DIFFERENT_SRIDS, it means that the geometry arguments did not all have the same SRID. You must modify them to have the same SRID.

The Open Geospatial Consortium guidelines require that input polygons already be closed, so unclosed polygons are rejected as invalid rather than being closed.

Empty geometry-collection handling is as follows: An empty WKT input geometry collection may be specified as 'GEOMETRYCOLLECTION()'. This is also the output WKT resulting from a spatial operation that produces an empty geometry collection.

During parsing of a nested geometry collection, the collection is flattened and its basic components are used in various GIS operations to compute results. This provides additional flexibility to users because it is unnecessary to be concerned about the uniqueness of geometry data. Nested geometry collections may be produced from nested GIS function calls without having to be explicitly flattened first.

12.15.3 Functions That Create Geometry Values from WKT Values

These functions take as arguments a Well-Known Text (WKT) representation and, optionally, a spatial reference system identifier (SRID). They return the corresponding geometry. For a description of WKT format, see Well-Known Text (WKT) Format.

Functions in this section detect arguments in either Cartesian or geographic spatial reference systems (SRSs), and return results appropriate to the SRS.

ST_GeomFromText() accepts a WKT value of any geometry type as its first argument. Other functions provide type-specific construction functions for construction of geometry values of each geometry type.

Functions such as ST_MPointFromText() and ST_GeomFromText() that accept WKT-format representations of MultiPoint values permit individual points within values to be surrounded by parentheses. For example, both of the following function calls are valid:

ST_MPointFromText('MULTIPOINT (1 1, 2 2, 3 3)')
ST_MPointFromText('MULTIPOINT ((1 1), (2 2), (3 3))')

Functions such as ST_GeomFromText() that accept WKT geometry collection arguments understand both OpenGIS 'GEOMETRYCOLLECTION EMPTY' standard syntax and MySQL 'GEOMETRYCOLLECTION()' nonstandard syntax. Functions such as ST_AsWKT() that produce WKT values produce 'GEOMETRYCOLLECTION EMPTY' standard syntax:

mysql> SET @s1 = ST_GeomFromText('GEOMETRYCOLLECTION()');
mysql> SET @s2 = ST_GeomFromText('GEOMETRYCOLLECTION EMPTY');
mysql> SELECT ST_AsWKT(@s1), ST_AsWKT(@s2);
+--------------------------+--------------------------+
| ST_AsWKT(@s1)            | ST_AsWKT(@s2)            |
+--------------------------+--------------------------+
| GEOMETRYCOLLECTION EMPTY | GEOMETRYCOLLECTION EMPTY |
+--------------------------+--------------------------+

Unless otherwise specified, functions in this section handle their arguments as follows:

If any geometry argument is NULL or is not a syntactically well-formed geometry, or if the SRID argument is NULL, the return value is NULL.
By default, geographic coordinates (latitude, longitude) are interpreted as in the order specified by the spatial reference system of geometry arguments. An optional options argument may be given to override the default axis order. options consists of a list of comma-separated key=value. The onlypermitted key value is axis-order, with permitted values of lat-long, long-lat and srid-defined (the default).
If the options argument is NULL, the return value is NULL. If the options argument is invalid, an error occurs to indicate why.
If an SRID argument refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For geographic SRS geometry arguments, if any argument has a longitude or latitude that is out of range, an error occurs:
- If a longitude value is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
- If a latitude value is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.

These functions are available for creating geometries from WKT values:

ST_GeomCollFromText(wkt[, srid [, options]]), ST_GeometryCollectionFromText(wkt[, srid [, options]]), ST_GeomCollFromTxt(wkt[, srid [, options]])

Constructs a GeometryCollection value using its WKT representation and SRID.

These functions handle their arguments as described in the introduction to this section.

mysql> SET @g = "MULTILINESTRING((10 10, 11 11), (9 9, 10 10))";
mysql> SELECT ST_AsText(ST_GeomCollFromText(@g));
+--------------------------------------------+
| ST_AsText(ST_GeomCollFromText(@g))         |
+--------------------------------------------+
| MULTILINESTRING((10 10,11 11),(9 9,10 10)) |
+--------------------------------------------+

ST_GeomFromText(wkt[, srid [, options]]), ST_GeometryFromText(wkt[, srid [, options]])
Constructs a geometry value of any type using its WKT representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_LineFromText(wkt[, srid [, options]]), ST_LineStringFromText(wkt[, srid [, options]])
Constructs a LineString value using its WKT representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_MLineFromText(wkt[, srid [, options]]), ST_MultiLineStringFromText(wkt[, srid [, options]])
Constructs a MultiLineString value using its WKT representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_MPointFromText(wkt[, srid [, options]]), ST_MultiPointFromText(wkt[, srid [, options]])
Constructs a MultiPoint value using its WKT representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_MPolyFromText(wkt[, srid [, options]]), ST_MultiPolygonFromText(wkt[, srid [, options]])
Constructs a MultiPolygon value using its WKT representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_PointFromText(wkt[, srid [, options]])
Constructs a Point value using its WKT representation and SRID.
ST_PointFromText() handles its arguments as described in the introduction to this section.
ST_PolyFromText(wkt[, srid [, options]]), ST_PolygonFromText(wkt[, srid [, options]])
Constructs a Polygon value using its WKT representation and SRID.
These functions handle their arguments as described in the introduction to this section.

12.15.4 Functions That Create Geometry Values from WKB Values

These functions take as arguments a BLOB containing a Well-Known Binary (WKB) representation and, optionally, a spatial reference system identifier (SRID). They return the corresponding geometry. For a description of WKB format, see Well-Known Binary (WKB) Format.

Functions in this section detect arguments in either Cartesian or geographic spatial reference systems (SRSs), and return results appropriate to the SRS.

ST_GeomFromWKB() accepts a WKB value of any geometry type as its first argument. Other functions provide type-specific construction functions for construction of geometry values of each geometry type.

Prior to MySQL 8.0, these functions also accepted geometry objects as returned by the functions in Section 12.15.5, “MySQL-Specific Functions That Create Geometry Values”. Geometry arguments are no longer permitted and produce an error. To migrate calls from using geometry arguments to using WKB arguments, follow these guidelines:

Rewrite constructs such as ST_GeomFromWKB(Point(0, 0)) as Point(0, 0).
Rewrite constructs such as ST_GeomFromWKB(Point(0, 0), 4326) as ST_SRID(Point(0, 0), 4326) or ST_GeomFromWKB(ST_AsWKB(Point(0, 0)), 4326).

Unless otherwise specified, functions in this section handle their arguments as follows:

If the WKB or SRID argument is NULL, the return value is NULL.
By default, geographic coordinates (latitude, longitude) are interpreted as in the order specified by the spatial reference system of geometry arguments. An optional options argument may be given to override the default axis order. options consists of a list of comma-separated key=value. The onlypermitted key value is axis-order, with permitted values of lat-long, long-lat and srid-defined (the default).
If the options argument is NULL, the return value is NULL. If the options argument is invalid, an error occurs to indicate why.
If an SRID argument refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For geographic SRS geometry arguments, if any argument has a longitude or latitude that is out of range, an error occurs:
- If a longitude value is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
- If a latitude value is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.

These functions are available for creating geometries from WKB values:

ST_GeomCollFromWKB(wkb[, srid [, options]]), ST_GeometryCollectionFromWKB(wkb[, srid [, options]])
Constructs a GeometryCollection value using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_GeomFromWKB(wkb[, srid [, options]]), ST_GeometryFromWKB(wkb[, srid [, options]])
Constructs a geometry value of any type using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_LineFromWKB(wkb[, srid [, options]]), ST_LineStringFromWKB(wkb[, srid [, options]])
Constructs a LineString value using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_MLineFromWKB(wkb[, srid [, options]]), ST_MultiLineStringFromWKB(wkb[, srid [, options]])
Constructs a MultiLineString value using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_MPointFromWKB(wkb[, srid [, options]]), ST_MultiPointFromWKB(wkb[, srid [, options]])
Constructs a MultiPoint value using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_MPolyFromWKB(wkb[, srid [, options]]), ST_MultiPolygonFromWKB(wkb[, srid [, options]])
Constructs a MultiPolygon value using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.
ST_PointFromWKB(wkb[, srid [, options]])
Constructs a Point value using its WKB representation and SRID.
ST_PointFromWKB() handles its arguments as described in the introduction to this section.
ST_PolyFromWKB(wkb[, srid [, options]]), ST_PolygonFromWKB(wkb[, srid [, options]])
Constructs a Polygon value using its WKB representation and SRID.
These functions handle their arguments as described in the introduction to this section.

12.15.5 MySQL-Specific Functions That Create Geometry Values

MySQL provides a set of useful nonstandard functions for creating geometry values. The functions described in this section are MySQL extensions to the OpenGIS specification.

These functions produce geometry objects from either WKB values or geometry objects as arguments. If any argument is not a proper WKB or geometry representation of the proper object type, the return value is NULL.

For example, you can insert the geometry return value from Point() directly into a POINT column:

INSERT INTO t1 (pt_col) VALUES(Point(1,2));

GeomCollection(g [, g] ...)
Constructs a GeomCollection value from the geometry arguments.
GeomCollection() returns all the proper geometries contained in the arguments even if a nonsupported geometry is present.
GeomCollection() with no arguments is permitted as a way to create an empty geometry. Also, functions such as ST_GeomFromText() that accept WKT geometry collection arguments understand both OpenGIS 'GEOMETRYCOLLECTION EMPTY' standard syntax and MySQL 'GEOMETRYCOLLECTION()' nonstandard syntax.
GeomCollection() and GeometryCollection() are synonymous, with GeomCollection() the preferred function.
GeometryCollection(g [, g] ...)
Constructs a GeomCollection value from the geometry arguments.
GeometryCollection() returns all the proper geometries contained in the arguments even if a nonsupported geometry is present.
GeometryCollection() with no arguments is permitted as a way to create an empty geometry. Also, functions such as ST_GeomFromText() that accept WKT geometry collection arguments understand both OpenGIS 'GEOMETRYCOLLECTION EMPTY' standard syntax and MySQL 'GEOMETRYCOLLECTION()' nonstandard syntax.
GeomCollection() and GeometryCollection() are synonymous, with GeomCollection() the preferred function.
LineString(pt [, pt] ...)
Constructs a LineString value from a number of Point or WKB Point arguments. If the number of arguments is less than two, the return value is NULL.
MultiLineString(ls [, ls] ...)
Constructs a MultiLineString value using LineString or WKB LineString arguments.
MultiPoint(pt [, pt2] ...)
Constructs a MultiPoint value using Point or WKB Point arguments.
MultiPolygon(poly [, poly] ...)
Constructs a MultiPolygon value from a set of Polygon or WKB Polygon arguments.
Point(x, y)
Constructs a Point using its coordinates.
Polygon(ls [, ls] ...)
Constructs a Polygon value from a number of LineString or WKB LineString arguments. If any argument does not represent a LinearRing (that is, not a closed and simple LineString), the return value is NULL.

12.15.6 Geometry Format Conversion Functions

MySQL supports the functions listed in this section for converting geometry values from internal geometry format to WKT or WKB format, or for swapping the order of X and Y coordinates.

There are also functions to convert a string from WKT or WKB format to internal geometry format. See Section 12.15.3, “Functions That Create Geometry Values from WKT Values”, and Section 12.15.4, “Functions That Create Geometry Values from WKB Values”.

Functions such as ST_GeomFromText() that accept WKT geometry collection arguments understand both OpenGIS 'GEOMETRYCOLLECTION EMPTY' standard syntax and MySQL 'GEOMETRYCOLLECTION()' nonstandard syntax. Another way to produce an empty geometry collection is by calling GeometryCollection() with no arguments. Functions such as ST_AsWKT() that produce WKT values produce 'GEOMETRYCOLLECTION EMPTY' standard syntax:

mysql> SET @s1 = ST_GeomFromText('GEOMETRYCOLLECTION()');
mysql> SET @s2 = ST_GeomFromText('GEOMETRYCOLLECTION EMPTY');
mysql> SELECT ST_AsWKT(@s1), ST_AsWKT(@s2);
+--------------------------+--------------------------+
| ST_AsWKT(@s1)            | ST_AsWKT(@s2)            |
+--------------------------+--------------------------+
| GEOMETRYCOLLECTION EMPTY | GEOMETRYCOLLECTION EMPTY |
+--------------------------+--------------------------+
mysql> SELECT ST_AsWKT(GeomCollection());
+----------------------------+
| ST_AsWKT(GeomCollection()) |
+----------------------------+
| GEOMETRYCOLLECTION EMPTY   |
+----------------------------+

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument is in an undefined spatial reference system, the axes are output in the order they appear in the geometry and an ER_WARN_SRS_NOT_FOUND_AXIS_ORDER warning occurs.
By default, geographic coordinates (latitude, longitude) are interpreted as in the order specified by the spatial reference system of geometry arguments. An optional options argument may be given to override the default axis order. options consists of a list of comma-separated key=value. The onlypermitted key value is axis-order, with permitted values of lat-long, long-lat and srid-defined (the default).
If the options argument is NULL, the return value is NULL. If the options argument is invalid, an error occurs to indicate why.
Otherwise, the return value is non-NULL.

These functions are available for format conversions or coordinate swapping:

ST_AsBinary(g [, options]), ST_AsWKB(g [, options])

Converts a value in internal geometry format to its WKB representation and returns the binary result.

The function return value has geographic coordinates (latitude, longitude) in the order specified by the spatial reference system that applies to the geometry argument. An optional options argument may be given to override the default axis order.

ST_AsBinary() and ST_AsWKB() handle their arguments as described in the introduction to this section.

mysql> SET @g = ST_LineFromText('LINESTRING(0 5,5 10,10 15)', 4326);
mysql> SELECT ST_AsText(ST_GeomFromWKB(ST_AsWKB(@g)));
+-----------------------------------------+
| ST_AsText(ST_GeomFromWKB(ST_AsWKB(@g))) |
+-----------------------------------------+
| LINESTRING(5 0,10 5,15 10)              |
+-----------------------------------------+
mysql> SELECT ST_AsText(ST_GeomFromWKB(ST_AsWKB(@g, 'axis-order=long-lat')));
+----------------------------------------------------------------+
| ST_AsText(ST_GeomFromWKB(ST_AsWKB(@g, 'axis-order=long-lat'))) |
+----------------------------------------------------------------+
| LINESTRING(0 5,5 10,10 15)                                     |
+----------------------------------------------------------------+
mysql> SELECT ST_AsText(ST_GeomFromWKB(ST_AsWKB(@g, 'axis-order=lat-long')));
+----------------------------------------------------------------+
| ST_AsText(ST_GeomFromWKB(ST_AsWKB(@g, 'axis-order=lat-long'))) |
+----------------------------------------------------------------+
| LINESTRING(5 0,10 5,15 10)                                     |
+----------------------------------------------------------------+

ST_AsText(g [, options]), ST_AsWKT(g [, options])
Converts a value in internal geometry format to its WKT representation and returns the string result.
The function return value has geographic coordinates (latitude, longitude) in the order specified by the spatial reference system that applies to the geometry argument. An optional options argument may be given to override the default axis order.
ST_AsText() and ST_AsWKT() handle their arguments as described in the introduction to this section.
```
mysql> SET @g = 'LineString(1 1,2 2,3 3)';
mysql> SELECT ST_AsText(ST_GeomFromText(@g));
+--------------------------------+
| ST_AsText(ST_GeomFromText(@g)) |
+--------------------------------+
| LINESTRING(1 1,2 2,3 3)        |
+--------------------------------+
```
Output for MultiPoint values includes parentheses around each point. For example:
```
mysql> SELECT ST_AsText(ST_GeomFromText(@mp));
+---------------------------------+
| ST_AsText(ST_GeomFromText(@mp)) |
+---------------------------------+
| MULTIPOINT((1 1),(2 2),(3 3))   |
+---------------------------------+
```

ST_SwapXY(g)

Accepts an argument in internal geometry format, swaps the X and Y values of each coordinate pair within the geometry, and returns the result.

ST_SwapXY() handles its arguments as described in the introduction to this section.

mysql> SET @g = ST_LineFromText('LINESTRING(0 5,5 10,10 15)');
mysql> SELECT ST_AsText(@g);
+----------------------------+
| ST_AsText(@g)              |
+----------------------------+
| LINESTRING(0 5,5 10,10 15) |
+----------------------------+
mysql> SELECT ST_AsText(ST_SwapXY(@g));
+----------------------------+
| ST_AsText(ST_SwapXY(@g))   |
+----------------------------+
| LINESTRING(5 0,10 5,15 10) |
+----------------------------+

12.15.7 Geometry Property Functions

12.15.7.1 General Geometry Property Functions
12.15.7.2 Point Property Functions
12.15.7.3 LineString and MultiLineString Property Functions
12.15.7.4 Polygon and MultiPolygon Property Functions
12.15.7.5 GeometryCollection Property Functions

Each function that belongs to this group takes a geometry value as its argument and returns some quantitative or qualitative property of the geometry. Some functions restrict their argument type. Such functions return NULL if the argument is of an incorrect geometry type. For example, the ST_Area() polygon function returns NULL if the object type is neither Polygon nor MultiPolygon.

12.15.7.1 General Geometry Property Functions

The functions listed in this section do not restrict their argument and accept a geometry value of any type.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
If any SRID argument is not within the range of a 32-bit unsigned integer, an ER_DATA_OUT_OF_RANGE error occurs.
If any SRID argument refers to an undefined SRS, an ER_SRS_NOT_FOUND error occurs.
Otherwise, the return value is non-NULL.

These functions are available for obtaining geometry properties:

ST_Dimension(g)

Returns the inherent dimension of the geometry value g. The dimension can be −1, 0, 1, or 2. The meaning of these values is given in Section 11.5.2.2, “Geometry Class”.

ST_Dimension() handles its arguments as described in the introduction to this section.

mysql> SELECT ST_Dimension(ST_GeomFromText('LineString(1 1,2 2)'));
+------------------------------------------------------+
| ST_Dimension(ST_GeomFromText('LineString(1 1,2 2)')) |
+------------------------------------------------------+
|                                                    1 |
+------------------------------------------------------+

ST_Envelope(g)

Returns the minimum bounding rectangle (MBR) for the geometry value g. The result is returned as a Polygon value that is defined by the corner points of the bounding box:

POLYGON((MINX MINY, MAXX MINY, MAXX MAXY, MINX MAXY, MINX MINY))

mysql> SELECT ST_AsText(ST_Envelope(ST_GeomFromText('LineString(1 1,2 2)')));
+----------------------------------------------------------------+
| ST_AsText(ST_Envelope(ST_GeomFromText('LineString(1 1,2 2)'))) |
+----------------------------------------------------------------+
| POLYGON((1 1,2 1,2 2,1 2,1 1))                                 |
+----------------------------------------------------------------+

If the argument is a point or a vertical or horizontal line segment, ST_Envelope() returns the point or the line segment as its MBR rather than returning an invalid polygon:

mysql> SELECT ST_AsText(ST_Envelope(ST_GeomFromText('LineString(1 1,1 2)')));
+----------------------------------------------------------------+
| ST_AsText(ST_Envelope(ST_GeomFromText('LineString(1 1,1 2)'))) |
+----------------------------------------------------------------+
| LINESTRING(1 1,1 2)                                            |
+----------------------------------------------------------------+

ST_Envelope() handles its arguments as described in the introduction to this section, with this exception:

If the geometry has an SRID value for a geographic spatial reference system (SRS), an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.

ST_GeometryType(g)

Returns a binary string indicating the name of the geometry type of which the geometry instance g is a member. The name corresponds to one of the instantiable Geometry subclasses.

ST_GeometryType() handles its arguments as described in the introduction to this section.

mysql> SELECT ST_GeometryType(ST_GeomFromText('POINT(1 1)'));
+------------------------------------------------+
| ST_GeometryType(ST_GeomFromText('POINT(1 1)')) |
+------------------------------------------------+
| POINT                                          |
+------------------------------------------------+

ST_IsEmpty(g)
This function is a placeholder that returns 1 for an empty geometry collection value or 0 otherwise.
The only valid empty geometry is represented in the form of an empty geometry collection value. MySQL does not support GIS EMPTY values such as POINT EMPTY.
ST_IsEmpty() handles its arguments as described in the introduction to this section.
ST_IsSimple(g)
Returns 1 if the geometry value g is simple according to the ISO SQL/MM Part 3: Spatial standard. ST_IsSimple() returns 0 if the argument is not simple.
The descriptions of the instantiable geometric classes given under Section 11.5.2, “The OpenGIS Geometry Model” include the specific conditions that cause class instances to be classified as not simple.
ST_IsSimple() handles its arguments as described in the introduction to this section, with this exception:
- If the geometry has a geographic SRS with a longitude or latitude that is out of range, an error occurs:
  - If any longitude argument is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
  - If any latitude argument is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
  Ranges shown are in degrees. The exact range limits deviate slightly due to floating-point arithmetic.
ST_SRID(g[, srid])
With a single argument representing a valid geometry object g, ST_SRID() returns an integer indicating the ID of the spatial reference system (SRS) associated with g.
With the optional second argument representing a valid SRID value, ST_SRID() returns an object with the same type as its first argument with an SRID value equal to the second argument. This only sets the SRID value of the object; it does not perform any transformation of coordinate values.
ST_SRID() handles its arguments as described in the introduction to this section, with this exception:
- For the single-argument syntax, ST_SRID() returns the geometry SRID even if it refers to an undefined SRS. An ER_SRS_NOT_FOUND error does not occur.
```
mysql> SET @g = ST_GeomFromText('LineString(1 1,2 2)', 0);
mysql> SELECT ST_SRID(@g);
+-------------+
| ST_SRID(@g) |
+-------------+
|           0 |
+-------------+
mysql> SET @g = ST_SRID(@g, 4326);
mysql> SELECT ST_SRID(@g);
+-------------+
| ST_SRID(@g) |
+-------------+
|        4326 |
+-------------+
```
It is possible to create a geometry in a particular SRID by passing to ST_SRID() the result of one of the MySQL-specific functions for creating spatial values, along with an SRID value. For example:
```
SET @g1 = ST_SRID(Point(1, 1), 4326);
```
However, that method creates the geometry in SRID 0, then casts it to SRID 4326 (WGS 84). A preferable alternative is to create the geometry with the correct spatial reference system to begin with. For example:
```
SET @g1 = ST_PointFromText('POINT(1 1)', 4326);
SET @g1 = ST_GeomFromText('POINT(1 1)', 4326);
```
The two-argument form of ST_SRID() is useful for tasks such as correcting or changing the SRS of geometries that have an incorrect SRID.

12.15.7.2 Point Property Functions

A Point consists of X and Y coordinates, which may be obtained using the ST_X() and ST_Y() functions, respectively. These functions also permit an optional second argument that specifies an X or Y coordinate value, in which case the function result is the Point object from the first argument with the appropriate coordinate modified to be equal to the second argument.

For Point objects that have a geographic spatial reference system (SRS), the longitude and latitude may be obtained using the ST_Longitude() and ST_Latitude() functions, respectively. These functions also permit an optional second argument that specifies a longitude or latitude value, in which case the function result is the Point object from the first argument with the longitude or latitude modified to be equal to the second argument.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL, the return value is NULL.
If any geometry argument is a valid geometry but not a Point object, an ER_UNEXPECTED_GEOMETRY_TYPE error occurs.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
If an X or Y coordinate argument is provided and the value is -inf, +inf, or NaN, an ER_DATA_OUT_OF_RANGE error occurs.
If a longitude or latitude argument is out of range, an error occurs:
- If any longitude argument is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
- If any latitude argument is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
Ranges shown are in degrees. The exact range limits deviate slightly due to floating-point arithmetic.
Otherwise, the return value is non-NULL.

These functions are available for obtaining point properties:

ST_Latitude(p [, new_latitude_val])
With a single argument representing a valid Point object p that has a geographic spatial reference system (SRS), ST_Latitude() returns the latitude value of p as a double-precision number.
With the optional second argument representing a valid latitude value, ST_Latitude() returns a Point object like the first argument with its latitude equal to the second argument.
ST_Latitude() handles its arguments as described in the introduction to this section, with the addition that if the Point object is valid but does not have a geographic SRS, an ER_SRS_NOT_GEOGRAPHIC error occurs.
```
mysql> SET @pt = ST_GeomFromText('POINT(45 90)', 4326);
mysql> SELECT ST_Latitude(@pt);
+------------------+
| ST_Latitude(@pt) |
+------------------+
|               45 |
+------------------+
mysql> SELECT ST_AsText(ST_Latitude(@pt, 10));
+---------------------------------+
| ST_AsText(ST_Latitude(@pt, 10)) |
+---------------------------------+
| POINT(10 90)                    |
+---------------------------------+
```
This function was added in MySQL 8.0.12.
ST_Longitude(p [, new_longitude_val])
With a single argument representing a valid Point object p that has a geographic spatial reference system (SRS), ST_Longitude() returns the longitude value of p as a double-precision number.
With the optional second argument representing a valid longitude value, ST_Longitude() returns a Point object like the first argument with its longitude equal to the second argument.
ST_Longitude() handles its arguments as described in the introduction to this section, with the addition that if the Point object is valid but does not have a geographic SRS, an ER_SRS_NOT_GEOGRAPHIC error occurs.
```
mysql> SET @pt = ST_GeomFromText('POINT(45 90)', 4326);
mysql> SELECT ST_Longitude(@pt);
+-------------------+
| ST_Longitude(@pt) |
+-------------------+
|                90 |
+-------------------+
mysql> SELECT ST_AsText(ST_Longitude(@pt, 10));
+----------------------------------+
| ST_AsText(ST_Longitude(@pt, 10)) |
+----------------------------------+
| POINT(45 10)                     |
+----------------------------------+
```
This function was added in MySQL 8.0.12.
ST_X(p[, new_x_val])
With a single argument representing a valid Point object p, ST_X() returns the X-coordinate value of p as a double-precision number. As of MySQL 8.0.12, the X coordinate is considered to refer to the axis that appears first in the Point spatial reference system (SRS) definition.
With the optional second argument, ST_X() returns a Point object like the first argument with its X coordinate equal to the second argument. As of MySQL 8.0.12, if the Point object has a geographic SRS, the second argument must be in the proper range for longitude or latitude values.
ST_X() handles its arguments as described in the introduction to this section.
```
mysql> SELECT ST_X(Point(56.7, 53.34));
+--------------------------+
| ST_X(Point(56.7, 53.34)) |
+--------------------------+
|                     56.7 |
+--------------------------+
mysql> SELECT ST_AsText(ST_X(Point(56.7, 53.34), 10.5));
+-------------------------------------------+
| ST_AsText(ST_X(Point(56.7, 53.34), 10.5)) |
+-------------------------------------------+
| POINT(10.5 53.34)                         |
+-------------------------------------------+
```
ST_Y(p[, new_y_val])
With a single argument representing a valid Point object p, ST_Y() returns the Y-coordinate value of p as a double-precision number. As of MySQL 8.0.12, the Y coordinate is considered to refer to the axis that appears second in the Point spatial reference system (SRS) definition.
With the optional second argument, ST_Y() returns a Point object like the first argument with its Y coordinate equal to the second argument. As of MySQL 8.0.12, if the Point object has a geographic SRS, the second argument must be in the proper range for longitude or latitude values.
ST_Y() handles its arguments as described in the introduction to this section.
```
mysql> SELECT ST_Y(Point(56.7, 53.34));
+--------------------------+
| ST_Y(Point(56.7, 53.34)) |
+--------------------------+
|                    53.34 |
+--------------------------+
mysql> SELECT ST_AsText(ST_Y(Point(56.7, 53.34), 10.5));
+-------------------------------------------+
| ST_AsText(ST_Y(Point(56.7, 53.34), 10.5)) |
+-------------------------------------------+
| POINT(56.7 10.5)                          |
+-------------------------------------------+
```

12.15.7.3 LineString and MultiLineString Property Functions

A LineString consists of Point values. You can extract particular points of a LineString, count the number of points that it contains, or obtain its length.

Some functions in this section also work for MultiLineString values.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL or any geometry argument is an empty geometry, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
Otherwise, the return value is non-NULL.

These functions are available for obtaining linestring properties:

ST_EndPoint(ls)

Returns the Point that is the endpoint of the LineString value ls.

ST_EndPoint() handles its arguments as described in the introduction to this section.

mysql> SET @ls = 'LineString(1 1,2 2,3 3)';
mysql> SELECT ST_AsText(ST_EndPoint(ST_GeomFromText(@ls)));
+----------------------------------------------+
| ST_AsText(ST_EndPoint(ST_GeomFromText(@ls))) |
+----------------------------------------------+
| POINT(3 3)                                   |
+----------------------------------------------+

ST_IsClosed(ls)

For a LineString value ls, ST_IsClosed() returns 1 if ls is closed (that is, its ST_StartPoint() and ST_EndPoint() values are the same).

For a MultiLineString value ls, ST_IsClosed() returns 1 if ls is closed (that is, the ST_StartPoint() and ST_EndPoint() values are the same for each LineString in ls).

ST_IsClosed() returns 0 if ls is not closed, and NULL if ls is NULL.

ST_IsClosed() handles its arguments as described in the introduction to this section, with this exception:

If the geometry has an SRID value for a geographic spatial reference system (SRS), an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.

mysql> SET @ls1 = 'LineString(1 1,2 2,3 3,2 2)';
mysql> SET @ls2 = 'LineString(1 1,2 2,3 3,1 1)';

mysql> SELECT ST_IsClosed(ST_GeomFromText(@ls1));
+------------------------------------+
| ST_IsClosed(ST_GeomFromText(@ls1)) |
+------------------------------------+
|                                  0 |
+------------------------------------+

mysql> SELECT ST_IsClosed(ST_GeomFromText(@ls2));
+------------------------------------+
| ST_IsClosed(ST_GeomFromText(@ls2)) |
+------------------------------------+
|                                  1 |
+------------------------------------+

mysql> SET @ls3 = 'MultiLineString((1 1,2 2,3 3),(4 4,5 5))';

mysql> SELECT ST_IsClosed(ST_GeomFromText(@ls3));
+------------------------------------+
| ST_IsClosed(ST_GeomFromText(@ls3)) |
+------------------------------------+
|                                  0 |
+------------------------------------+

ST_Length(ls)
Returns a double-precision number indicating the length of the LineString or MultiLineString value ls in its associated spatial reference. The length of a MultiLineString value is equal to the sum of the lengths of its elements.
ST_Length() computes a result as follows:
- If the geometry is a valid LineString in a Cartesian SRS, the return value is the Cartesian length of the geometry.
- If the geometry is a valid MultiLineString in a Cartesian SRS, the return value is the sum of the Cartesian lengths of its elements.
- If the geometry is a valid LineString in a geographic SRS, the return value is the geodetic length of the geometry in that SRS, in meters.
- If the geometry is a valid MultiLineString in a geographic SRS, the return value is the sum of the geodetic lengths of its elements in that SRS, in meters.
ST_Length() handles its arguments as described in the introduction to this section, with these exceptions:
- If the geometry is not a LineString or MultiLineString, the return value is NULL.
- If the geometry is geometrically invalid, either the result is an undefined length (that is, it can be any number), or an error occurs.
- If the length computation result is +inf, an ER_DATA_OUT_OF_RANGE error occurs.
- If the geometry has a geographic SRS with a longitude or latitude that is out of range, an error occurs:
  - If any longitude argument is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
  - If any latitude argument is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
  Ranges shown are in degrees. The exact range limits deviate slightly due to floating-point arithmetic.
```
mysql> SET @ls = 'LineString(1 1,2 2,3 3)';
mysql> SELECT ST_Length(ST_GeomFromText(@ls));
+---------------------------------+
| ST_Length(ST_GeomFromText(@ls)) |
+---------------------------------+
|              2.8284271247461903 |
+---------------------------------+

mysql> SET @mls = 'MultiLineString((1 1,2 2,3 3),(4 4,5 5))';
mysql> SELECT ST_Length(ST_GeomFromText(@mls));
+----------------------------------+
| ST_Length(ST_GeomFromText(@mls)) |
+----------------------------------+
|                4.242640687119286 |
+----------------------------------+
```

ST_NumPoints(ls)

Returns the number of Point objects in the LineString value ls.

ST_NumPoints() handles its arguments as described in the introduction to this section.

mysql> SET @ls = 'LineString(1 1,2 2,3 3)';
mysql> SELECT ST_NumPoints(ST_GeomFromText(@ls));
+------------------------------------+
| ST_NumPoints(ST_GeomFromText(@ls)) |
+------------------------------------+
|                                  3 |
+------------------------------------+

ST_PointN(ls, N)

Returns the N-th Point in the Linestring value ls. Points are numbered beginning with 1.

ST_PointN() handles its arguments as described in the introduction to this section.

mysql> SET @ls = 'LineString(1 1,2 2,3 3)';
mysql> SELECT ST_AsText(ST_PointN(ST_GeomFromText(@ls),2));
+----------------------------------------------+
| ST_AsText(ST_PointN(ST_GeomFromText(@ls),2)) |
+----------------------------------------------+
| POINT(2 2)                                   |
+----------------------------------------------+

ST_StartPoint(ls)

Returns the Point that is the start point of the LineString value ls.

ST_StartPoint() handles its arguments as described in the introduction to this section.

mysql> SET @ls = 'LineString(1 1,2 2,3 3)';
mysql> SELECT ST_AsText(ST_StartPoint(ST_GeomFromText(@ls)));
+------------------------------------------------+
| ST_AsText(ST_StartPoint(ST_GeomFromText(@ls))) |
+------------------------------------------------+
| POINT(1 1)                                     |
+------------------------------------------------+

12.15.7.4 Polygon and MultiPolygon Property Functions

Functions in this section return properties of Polygon or MultiPolygon values.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL or any geometry argument is an empty geometry, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For functions that take multiple geometry arguments, if those arguments do not have the same SRID, an ER_GIS_DIFFERENT_SRIDS error occurs.
Otherwise, the return value is non-NULL.

These functions are available for obtaining polygon properties:

ST_Area(poly)
Returns a double-precision number indicating the area of the argument, as measured in its spatial reference system. For arguments of dimension 0 or 1, the result is 0.
The result is the sum of the area values of all components for a geometry collection. If a geometry collection is empty, its area is returned as 0.
ST_Area() handles its arguments as described in the introduction to this section, with these exceptions:
- If a geometry is empty, the return value is 0 rather than NULL.
- If the geometry has an SRID value for a geographic spatial reference system (SRS), an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.
```
mysql> SET @poly =
       'Polygon((0 0,0 3,3 0,0 0),(1 1,1 2,2 1,1 1))';
mysql> SELECT ST_Area(ST_GeomFromText(@poly));
+---------------------------------+
| ST_Area(ST_GeomFromText(@poly)) |
+---------------------------------+
|                               4 |
+---------------------------------+

mysql> SET @mpoly =
    -> 'MultiPolygon(((0 0,0 3,3 3,3 0,0 0),(1 1,1 2,2 2,2 1,1 1)))';
mysql> SELECT ST_Area(ST_GeomFromText(@mpoly));
+----------------------------------+
| ST_Area(ST_GeomFromText(@mpoly)) |
+----------------------------------+
|                                8 |
+----------------------------------+
```
ST_Centroid(mpoly)
Returns the mathematical centroid for the MultiPolygon value mpoly as a Point. The result is not guaranteed to be on the MultiPolygon.
This function processes geometry collections by computing the centroid point for components of highest dimension in the collection. Such components are extracted and made into a single MultiPolygon, MultiLineString, or MultiPoint for centroid computation.
ST_Centroid() handles its arguments as described in the introduction to this section, with these exceptions:
- The return value is NULL for the additional condition that the argument is an empty geometry collection.
- If the geometry has an SRID value for a geographic spatial reference system (SRS), an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.
```
mysql> SET @poly =
    -> ST_GeomFromText('POLYGON((0 0,10 0,10 10,0 10,0 0),(5 5,7 5,7 7,5 7,5 5))');
mysql> SELECT ST_GeometryType(@poly),ST_AsText(ST_Centroid(@poly));
+------------------------+--------------------------------------------+
| ST_GeometryType(@poly) | ST_AsText(ST_Centroid(@poly))              |
+------------------------+--------------------------------------------+
| POLYGON                | POINT(4.958333333333333 4.958333333333333) |
+------------------------+--------------------------------------------+
```

ST_ExteriorRing(poly)

Returns the exterior ring of the Polygon value poly as a LineString.

ST_ExteriorRing() handles its arguments as described in the introduction to this section.

mysql> SET @poly =
    -> 'Polygon((0 0,0 3,3 3,3 0,0 0),(1 1,1 2,2 2,2 1,1 1))';
mysql> SELECT ST_AsText(ST_ExteriorRing(ST_GeomFromText(@poly)));
+----------------------------------------------------+
| ST_AsText(ST_ExteriorRing(ST_GeomFromText(@poly))) |
+----------------------------------------------------+
| LINESTRING(0 0,0 3,3 3,3 0,0 0)                    |
+----------------------------------------------------+

ST_InteriorRingN(poly, N)

Returns the N-th interior ring for the Polygon value poly as a LineString. Rings are numbered beginning with 1.

ST_InteriorRingN() handles its arguments as described in the introduction to this section.

mysql> SET @poly =
    -> 'Polygon((0 0,0 3,3 3,3 0,0 0),(1 1,1 2,2 2,2 1,1 1))';
mysql> SELECT ST_AsText(ST_InteriorRingN(ST_GeomFromText(@poly),1));
+-------------------------------------------------------+
| ST_AsText(ST_InteriorRingN(ST_GeomFromText(@poly),1)) |
+-------------------------------------------------------+
| LINESTRING(1 1,1 2,2 2,2 1,1 1)                       |
+-------------------------------------------------------+

ST_NumInteriorRing(poly), ST_NumInteriorRings(poly)

Returns the number of interior rings in the Polygon value poly.

ST_NumInteriorRing() and ST_NuminteriorRings() handle their arguments as described in the introduction to this section.

mysql> SET @poly =
    -> 'Polygon((0 0,0 3,3 3,3 0,0 0),(1 1,1 2,2 2,2 1,1 1))';
mysql> SELECT ST_NumInteriorRings(ST_GeomFromText(@poly));
+---------------------------------------------+
| ST_NumInteriorRings(ST_GeomFromText(@poly)) |
+---------------------------------------------+
|                                           1 |
+---------------------------------------------+

12.15.7.5 GeometryCollection Property Functions

These functions return properties of GeometryCollection values.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL or any geometry argument is an empty geometry, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
Otherwise, the return value is non-NULL.

These functions are available for obtaining geometry collection properties:

ST_GeometryN(gc, N)

Returns the N-th geometry in the GeometryCollection value gc. Geometries are numbered beginning with 1.

ST_GeometryN() handles its arguments as described in the introduction to this section.

mysql> SET @gc = 'GeometryCollection(Point(1 1),LineString(2 2, 3 3))';
mysql> SELECT ST_AsText(ST_GeometryN(ST_GeomFromText(@gc),1));
+-------------------------------------------------+
| ST_AsText(ST_GeometryN(ST_GeomFromText(@gc),1)) |
+-------------------------------------------------+
| POINT(1 1)                                      |
+-------------------------------------------------+

ST_NumGeometries(gc)

Returns the number of geometries in the GeometryCollection value gc.

ST_NumGeometries() handles its arguments as described in the introduction to this section.

mysql> SET @gc = 'GeometryCollection(Point(1 1),LineString(2 2, 3 3))';
mysql> SELECT ST_NumGeometries(ST_GeomFromText(@gc));
+----------------------------------------+
| ST_NumGeometries(ST_GeomFromText(@gc)) |
+----------------------------------------+
|                                      2 |
+----------------------------------------+

12.15.8 Spatial Operator Functions

OpenGIS proposes a number of functions that can produce geometries. They are designed to implement spatial operators.

These functions support all argument type combinations except those that are inapplicable according to the Open Geospatial Consortium specification.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For functions that take multiple geometry arguments, if those arguments do not have the same SRID, an ER_GIS_DIFFERENT_SRIDS error occurs.
If any geometry argument has an SRID value for a geographic SRS, an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.
Otherwise, the return value is non-NULL.

These spatial operator functions are available:

ST_Buffer(g, d[, strategy1[, strategy2[, strategy3]]])
Returns a geometry that represents all points whose distance from the geometry value g is less than or equal to a distance of d.
If the geometry argument is empty, ST_Buffer() returns an empty geometry.
If the distance is 0, ST_Buffer() returns the geometry argument unchanged:
```
mysql> SET @pt = ST_GeomFromText('POINT(0 0)');
mysql> SELECT ST_AsText(ST_Buffer(@pt, 0));
+------------------------------+
| ST_AsText(ST_Buffer(@pt, 0)) |
+------------------------------+
| POINT(0 0)                   |
+------------------------------+
```
ST_Buffer() supports negative distances for Polygon and MultiPolygon values, and for geometry collections containing Polygon or MultiPolygon values. The result may be an empty geometry.
ST_Buffer() permits up to three optional strategy arguments following the distance argument. Strategies influence buffer computation. These arguments are byte string values produced by the ST_Buffer_Strategy() function, to be used for point, join, and end strategies:
- Point strategies apply to Point and MultiPoint geometries. If no point strategy is specified, the default is ST_Buffer_Strategy('point_circle', 32).
- Join strategies apply to LineString, MultiLineString, Polygon, and MultiPolygon geometries. If no join strategy is specified, the default is ST_Buffer_Strategy('join_round', 32).
- End strategies apply to LineString and MultiLineString geometries. If no end strategy is specified, the default is ST_Buffer_Strategy('end_round', 32).
Up to one strategy of each type may be specified, and they may be given in any order.
ST_Buffer() handles its arguments as described in the introduction to this section, with these exceptions:
- For a negative distance for Point, MultiPoint, LineString, and MultiLineString values, and for geometry collections not containing any Polygon or MultiPolygon values, an ER_WRONG_ARGUMENTS error occurs.
- If multiple strategies of a given type are specified, an ER_WRONG_ARGUMENTS error occurs.
```
mysql> SET @pt = ST_GeomFromText('POINT(0 0)');
mysql> SET @pt_strategy = ST_Buffer_Strategy('point_square');
mysql> SELECT ST_AsText(ST_Buffer(@pt, 2, @pt_strategy));
+--------------------------------------------+
| ST_AsText(ST_Buffer(@pt, 2, @pt_strategy)) |
+--------------------------------------------+
| POLYGON((-2 -2,2 -2,2 2,-2 2,-2 -2))       |
+--------------------------------------------+
```
```
mysql> SET @ls = ST_GeomFromText('LINESTRING(0 0,0 5,5 5)');
mysql> SET @end_strategy = ST_Buffer_Strategy('end_flat');
mysql> SET @join_strategy = ST_Buffer_Strategy('join_round', 10);
mysql> SELECT ST_AsText(ST_Buffer(@ls, 5, @end_strategy, @join_strategy))
+---------------------------------------------------------------+
| ST_AsText(ST_Buffer(@ls, 5, @end_strategy, @join_strategy))   |
+---------------------------------------------------------------+
| POLYGON((5 5,5 10,0 10,-3.5355339059327373 8.535533905932738, |
| -5 5,-5 0,0 0,5 0,5 5))                                       |
+---------------------------------------------------------------+
```
ST_Buffer_Strategy(strategy[, points_per_circle])
This function returns a strategy byte string for use with ST_Buffer() to influence buffer computation.
Information about strategies is available at Boost.org.
The first argument must be a string indicating a strategy option:
- For point strategies, permitted values are 'point_circle' and 'point_square'.
- For join strategies, permitted values are 'join_round' and 'join_miter'.
- For end strategies, permitted values are 'end_round' and 'end_flat'.
If the first argument is 'point_circle', 'join_round', 'join_miter', or 'end_round', the points_per_circle argument must be given as a positive numeric value. The maximum points_per_circle value is the value of the max_points_in_geometry system variable.
For examples, see the description of ST_Buffer().
ST_Buffer_Strategy() handles its arguments as described in the introduction to this section, with these exceptions:
- If any argument is invalid, an ER_WRONG_ARGUMENTS error occurs.
- If the first argument is 'point_square' or 'end_flat', the points_per_circle argument must not be given or an ER_WRONG_ARGUMENTS error occurs.
ST_ConvexHull(g)
Returns a geometry that represents the convex hull of the geometry value g.
This function computes a geometry's convex hull by first checking whether its vertex points are colinear. The function returns a linear hull if so, a polygon hull otherwise. This function processes geometry collections by extracting all vertex points of all components of the collection, creating a MultiPoint value from them, and computing its convex hull.
ST_ConvexHull() handles its arguments as described in the introduction to this section, with this exception:
- The return value is NULL for the additional condition that the argument is an empty geometry collection.
```
mysql> SET @g = 'MULTIPOINT(5 0,25 0,15 10,15 25)';
mysql> SELECT ST_AsText(ST_ConvexHull(ST_GeomFromText(@g)));
+-----------------------------------------------+
| ST_AsText(ST_ConvexHull(ST_GeomFromText(@g))) |
+-----------------------------------------------+
| POLYGON((5 0,25 0,15 25,5 0))                 |
+-----------------------------------------------+
```

ST_Difference(g1, g2)

Returns a geometry that represents the point set difference of the geometry values g1 and g2.

ST_Difference() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = Point(1,1), @g2 = Point(2,2);
mysql> SELECT ST_AsText(ST_Difference(@g1, @g2));
+------------------------------------+
| ST_AsText(ST_Difference(@g1, @g2)) |
+------------------------------------+
| POINT(1 1)                         |
+------------------------------------+

ST_Intersection(g1, g2)

Returns a geometry that represents the point set intersection of the geometry values g1 and g2.

ST_Intersection() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = ST_GeomFromText('LineString(1 1, 3 3)');
mysql> SET @g2 = ST_GeomFromText('LineString(1 3, 3 1)');
mysql> SELECT ST_AsText(ST_Intersection(@g1, @g2));
+--------------------------------------+
| ST_AsText(ST_Intersection(@g1, @g2)) |
+--------------------------------------+
| POINT(2 2)                           |
+--------------------------------------+

ST_SymDifference(g1, g2)

Returns a geometry that represents the point set symmetric difference of the geometry values g1 and g2, which is defined as:

g1 symdifference g2 := (g1 union g2) difference (g1 intersection g2)

Or, in function call notation:

ST_SymDifference(g1, g2) = ST_Difference(ST_Union(g1, g2), ST_Intersection(g1, g2))

ST_SymDifference() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = Point(1,1), @g2 = Point(2,2);
mysql> SELECT ST_AsText(ST_SymDifference(@g1, @g2));
+---------------------------------------+
| ST_AsText(ST_SymDifference(@g1, @g2)) |
+---------------------------------------+
| MULTIPOINT((1 1),(2 2))               |
+---------------------------------------+

ST_Union(g1, g2)

Returns a geometry that represents the point set union of the geometry values g1 and g2.

ST_Union() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = ST_GeomFromText('LineString(1 1, 3 3)');
mysql> SET @g2 = ST_GeomFromText('LineString(1 3, 3 1)');
mysql> SELECT ST_AsText(ST_Union(@g1, @g2));
+--------------------------------------+
| ST_AsText(ST_Union(@g1, @g2))        |
+--------------------------------------+
| MULTILINESTRING((1 1,3 3),(1 3,3 1)) |
+--------------------------------------+

In addition, Section 12.15.7, “Geometry Property Functions”, discusses several functions that construct new geometries from existing ones. See that section for descriptions of these functions:

12.15.9 Functions That Test Spatial Relations Between Geometry Objects

12.15.9.1 Spatial Relation Functions That Use Object Shapes
12.15.9.2 Spatial Relation Functions That Use Minimum Bounding Rectangles

The functions described in this section take two geometries as arguments and return a qualitative or quantitative relation between them.

MySQL implements two sets of functions using function names defined by the OpenGIS specification. One set tests the relationship between two geometry values using precise object shapes, the other set uses object minimum bounding rectangles (MBRs).

12.15.9.1 Spatial Relation Functions That Use Object Shapes

The OpenGIS specification defines the following functions to test the relationship between two geometry values g1 and g2, using precise object shapes. Except for ST_Distance(), the return values 1 and 0 indicate true and false, respectively. ST_Distance() returns distance values.

Functions in this section detect arguments in either Cartesian or geographic spatial reference systems (SRSs), and return results appropriate to the SRS.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL or any geometry argument is an empty geometry, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For functions that take multiple geometry arguments, if those arguments do not have the same SRID, an ER_GIS_DIFFERENT_SRIDS error occurs.
If any geometry argument is geometrically invalid, either the result is true or false (it is undefined which), or an error occurs.
For geographic SRS geometry arguments, if any argument has a longitude or latitude that is out of range, an error occurs:
- If a longitude value is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
- If a latitude value is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.
Otherwise, the return value is non-NULL.

These object-shape functions are available for testing geometry relationships:

ST_Contains(g1, g2)
Returns 1 or 0 to indicate whether g1 completely contains g2. This tests the opposite relationship as ST_Within().
ST_Contains() handles its arguments as described in the introduction to this section.
ST_Crosses(g1, g2)
Two geometries spatially cross if their spatial relation has the following properties:
- Unless g1 and and g2 are both of dimension 1: g1 crosses g2 if the interior of g2 has points in common with the interior of g1, but g2 does not cover the entire interior of g1.
- If both g1 and g2 are of dimension 1: If the lines cross each other in a finite number of points (that is, no common line segments, only single points in common).
This function returns 1 or 0 to indicate whether g1 spatially crosses g2.
ST_Crosses() handles its arguments as described in the introduction to this section except that the return value is NULL for these additional conditions:
- g1 is of dimension 2 (Polygon or MultiPolygon).
- g2 is of dimension 1 (Point or MultiPoint).
ST_Disjoint(g1, g2)
Returns 1 or 0 to indicate whether g1 is spatially disjoint from (does not intersect) g2.
ST_Disjoint() handles its arguments as described in the introduction to this section.
ST_Distance(g1, g2)
Returns the distance between g1 and g2, measured in the length unit of the spatial reference system (SRS).
This function processes geometry collections by returning the shortest distance among all combinations of the components of the two geometry arguments.
ST_Distance() handles its arguments as described in the introduction to this section, with these exceptions:
- ST_Distance() detects arguments in a geographic (ellipsoidal) spatial reference system and returns the geodetic distance on the ellipsoid. The only permitted geographic argument types are Point and Point, or Point and MultiPoint (in any argument order). If called with other geometry type argument combinations in a geographic SRS, an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.
- If any argument is geometrically invalid, either the result is an undefined distance (that is, it can be any number), or an error occurs.
- If an intermediate or final result produces NaN or a negative number, an ER_GIS_INVALID_DATA error occurs.
```
mysql> SET @g1 = Point(1,1);
mysql> SET @g2 = Point(2,2);
mysql> SELECT ST_Distance(@g1, @g2);
+-----------------------+
| ST_Distance(@g1, @g2) |
+-----------------------+
|    1.4142135623730951 |
+-----------------------+

mysql> SET @g1 = ST_GeomFromText('POINT(1 1)', 4326);
mysql> SET @g2 = ST_GeomFromText('POINT(2 2)', 4326);
mysql> SELECT ST_Distance(@g1, @g2);
+-----------------------+
| ST_Distance(@g1, @g2) |
+-----------------------+
|     156874.3859490455 |
+-----------------------+
```
For the special case of distance calculations on a sphere, see the ST_Distance_Sphere() function.

ST_Equals(g1, g2)

Returns 1 or 0 to indicate whether g1 is spatially equal to g2.

ST_Equals() handles its arguments as described in the introduction to this section, except that it does not return NULL for empty geometry arguments.

mysql> SET @g1 = Point(1,1), @g2 = Point(2,2);
mysql> SELECT ST_Equals(@g1, @g1), ST_Equals(@g1, @g2);
+---------------------+---------------------+
| ST_Equals(@g1, @g1) | ST_Equals(@g1, @g2) |
+---------------------+---------------------+
|                   1 |                   0 |
+---------------------+---------------------+

ST_Intersects(g1, g2)
Returns 1 or 0 to indicate whether g1 spatially intersects g2.
ST_Intersects() handles its arguments as described in the introduction to this section.
ST_Overlaps(g1, g2)
Two geometries spatially overlap if they intersect and their intersection results in a geometry of the same dimension but not equal to either of the given geometries.
This function returns 1 or 0 to indicate whether g1 spatially overlaps g2.
ST_Overlaps() handles its arguments as described in the introduction to this section except that the return value is NULL for the additional condition that the dimensions of the two geometries are not equal.
ST_Touches(g1, g2)
Two geometries spatially touch if their interiors do not intersect, but the boundary of one of the geometries intersects either the boundary or the interior of the other.
This function returns 1 or 0 to indicate whether g1 spatially touches g2.
ST_Touches() handles its arguments as described in the introduction to this section except that the return value is NULL for the additional condition that both geometries are of dimension 0 (Point or MultiPoint).
ST_Within(g1, g2)
Returns 1 or 0 to indicate whether g1 is spatially within g2. This tests the opposite relationship as ST_Contains().
ST_Within() handles its arguments as described in the introduction to this section.

12.15.9.2 Spatial Relation Functions That Use Minimum Bounding Rectangles

MySQL provides several MySQL-specific functions that test the relationship between minimum bounding rectangles (MBRs) of two geometries g1 and g2. The return values 1 and 0 indicate true and false, respectively.

The bounding box of a point is interpreted as a point that is both boundary and interior.

The bounding box of a straight horizontal or vertical line is interpreted as a line where the interior of the line is also boundary. The endpoints are boundary points.

If any of the parameters are geometry collections, the interior, boundary, and exterior of those parameters are those of the union of all elements in the collection.

Functions in this section detect arguments in either Cartesian or geographic spatial reference systems (SRSs), and return results appropriate to the SRS.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL or an empty geometry, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For functions that take multiple geometry arguments, if those arguments do not have the same SRID, an ER_GIS_DIFFERENT_SRIDS error occurs.
If any argument is geometrically invalid, either the result is true or false (it is undefined which), or an error occurs.
For geographic SRS geometry arguments, if any argument has a longitude or latitude that is out of range, an error occurs:
- If a longitude value is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
- If a latitude value is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.
Otherwise, the return value is non-NULL.

These MBR functions are available for testing geometry relationships:

MBRContains(g1, g2)

Returns 1 or 0 to indicate whether the minimum bounding rectangle of g1 contains the minimum bounding rectangle of g2. This tests the opposite relationship as MBRWithin().

MBRContains() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = ST_GeomFromText('Polygon((0 0,0 3,3 3,3 0,0 0))');
mysql> SET @g2 = ST_GeomFromText('Point(1 1)');
mysql> SELECT MBRContains(@g1,@g2), MBRWithin(@g2,@g1);
+----------------------+--------------------+
| MBRContains(@g1,@g2) | MBRWithin(@g2,@g1) |
+----------------------+--------------------+
|                    1 |                  1 |
+----------------------+--------------------+

MBRCoveredBy(g1, g2)

Returns 1 or 0 to indicate whether the minimum bounding rectangle of g1 is covered by the minimum bounding rectangle of g2. This tests the opposite relationship as MBRCovers().

MBRCoveredBy() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = ST_GeomFromText('Polygon((0 0,0 3,3 3,3 0,0 0))');
mysql> SET @g2 = ST_GeomFromText('Point(1 1)');
mysql> SELECT MBRCovers(@g1,@g2), MBRCoveredby(@g1,@g2);
+--------------------+-----------------------+
| MBRCovers(@g1,@g2) | MBRCoveredby(@g1,@g2) |
+--------------------+-----------------------+
|                  1 |                     0 |
+--------------------+-----------------------+
mysql> SELECT MBRCovers(@g2,@g1), MBRCoveredby(@g2,@g1);
+--------------------+-----------------------+
| MBRCovers(@g2,@g1) | MBRCoveredby(@g2,@g1) |
+--------------------+-----------------------+
|                  0 |                     1 |
+--------------------+-----------------------+

MBRCovers(g1, g2)
Returns 1 or 0 to indicate whether the minimum bounding rectangle of g1 covers the minimum bounding rectangle of g2. This tests the opposite relationship as MBRCoveredBy(). See the description of MBRCoveredBy() for examples.
MBRCovers() handles its arguments as described in the introduction to this section.
MBRDisjoint(g1, g2)
Returns 1 or 0 to indicate whether the minimum bounding rectangles of the two geometries g1 and g2 are disjoint (do not intersect).
MBRDisjoint() handles its arguments as described in the introduction to this section.
MBREquals(g1, g2)
Returns 1 or 0 to indicate whether the minimum bounding rectangles of the two geometries g1 and g2 are the same.
MBREquals() handles its arguments as described in the introduction to this section, except that it does not return NULL for empty geometry arguments.
MBRIntersects(g1, g2)
Returns 1 or 0 to indicate whether the minimum bounding rectangles of the two geometries g1 and g2 intersect.
MBRIntersects() handles its arguments as described in the introduction to this section.
MBROverlaps(g1, g2)
Two geometries spatially overlap if they intersect and their intersection results in a geometry of the same dimension but not equal to either of the given geometries.
This function returns 1 or 0 to indicate whether the minimum bounding rectangles of the two geometries g1 and g2 overlap.
MBROverlaps() handles its arguments as described in the introduction to this section.
MBRTouches(g1, g2)
Two geometries spatially touch if their interiors do not intersect, but the boundary of one of the geometries intersects either the boundary or the interior of the other.
This function returns 1 or 0 to indicate whether the minimum bounding rectangles of the two geometries g1 and g2 touch.
MBRTouches() handles its arguments as described in the introduction to this section.

MBRWithin(g1, g2)

Returns 1 or 0 to indicate whether the minimum bounding rectangle of g1 is within the minimum bounding rectangle of g2. This tests the opposite relationship as MBRContains().

MBRWithin() handles its arguments as described in the introduction to this section.

mysql> SET @g1 = ST_GeomFromText('Polygon((0 0,0 3,3 3,3 0,0 0))');
mysql> SET @g2 = ST_GeomFromText('Polygon((0 0,0 5,5 5,5 0,0 0))');
mysql> SELECT MBRWithin(@g1,@g2), MBRWithin(@g2,@g1);
+--------------------+--------------------+
| MBRWithin(@g1,@g2) | MBRWithin(@g2,@g1) |
+--------------------+--------------------+
|                  1 |                  0 |
+--------------------+--------------------+

12.15.10 Spatial Geohash Functions

Geohash is a system for encoding latitude and longitude coordinates of arbitrary precision into a text string. Geohash values are strings that contain only characters chosen from "0123456789bcdefghjkmnpqrstuvwxyz".

The functions in this section enable manipulation of geohash values, which provides applications the capabilities of importing and exporting geohash data, and of indexing and searching geohash values.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL, the return value is NULL.
If any argument is invalid, an error occurs.
If any argument has a longitude or latitude that is out of range, an error occurs:
- If any longitude argument is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
- If any latitude argument is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
Ranges shown are in degrees. The exact range limits deviate slightly due to floating-point arithmetic.
If any point argument does not have SRID 0 or 4326, an ER_SRS_NOT_FOUND error occurs. point argument SRID validity is not checked.
If any SRID argument refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
If any SRID argument is not within the range of a 32-bit unsigned integer, an ER_DATA_OUT_OF_RANGE error occurs.
Otherwise, the return value is non-NULL.

These geohash functions are available:

ST_GeoHash(longitude, latitude, max_length), ST_GeoHash(point, max_length)
Returns a geohash string in the connection character set and collation.
For the first syntax, the longitude must be a number in the range [−180, 180], and the latitude must be a number in the range [−90, 90]. For the second syntax, a POINT value is required, where the X and Y coordinates are in the valid ranges for longitude and latitude, respectively.
The resulting string is no longer than max_length characters, which has an upper limit of 100. The string might be shorter than max_length characters because the algorithm that creates the geohash value continues until it has created a string that is either an exact representation of the location or max_length characters, whichever comes first.
ST_GeoHash() handles its arguments as described in the introduction to this section.
```
mysql> SELECT ST_GeoHash(180,0,10), ST_GeoHash(-180,-90,15);
+----------------------+-------------------------+
| ST_GeoHash(180,0,10) | ST_GeoHash(-180,-90,15) |
+----------------------+-------------------------+
| xbpbpbpbpb           | 000000000000000         |
+----------------------+-------------------------+
```
ST_LatFromGeoHash(geohash_str)
Returns the latitude from a geohash string value, as a double-precision number in the range [−90, 90].
The ST_LatFromGeoHash() decoding function reads no more than 433 characters from the geohash_str argument. That represents the upper limit on information in the internal representation of coordinate values. Characters past the 433rd are ignored, even if they are otherwise illegal and produce an error.
ST_LatFromGeoHash() handles its arguments as described in the introduction to this section.
```
mysql> SELECT ST_LatFromGeoHash(ST_GeoHash(45,-20,10));
+------------------------------------------+
| ST_LatFromGeoHash(ST_GeoHash(45,-20,10)) |
+------------------------------------------+
|                                      -20 |
+------------------------------------------+
```
ST_LongFromGeoHash(geohash_str)
Returns the longitude from a geohash string value, as a double-precision number in the range [−180, 180].
The remarks in the description of ST_LatFromGeoHash() regarding the maximum number of characters processed from the geohash_str argument also apply to ST_LongFromGeoHash().
ST_LongFromGeoHash() handles its arguments as described in the introduction to this section.
```
mysql> SELECT ST_LongFromGeoHash(ST_GeoHash(45,-20,10));
+-------------------------------------------+
| ST_LongFromGeoHash(ST_GeoHash(45,-20,10)) |
+-------------------------------------------+
|                                        45 |
+-------------------------------------------+
```
ST_PointFromGeoHash(geohash_str, srid)
Returns a POINT value containing the decoded geohash value, given a geohash string value.
The X and Y coordinates of the point are the longitude in the range [−180, 180] and the latitude in the range [−90, 90], respectively.
The srid argument is an 32-bit unsigned integer.
The remarks in the description of ST_LatFromGeoHash() regarding the maximum number of characters processed from the geohash_str argument also apply to ST_PointFromGeoHash().
ST_PointFromGeoHash() handles its arguments as described in the introduction to this section.
```
mysql> SET @gh = ST_GeoHash(45,-20,10);
mysql> SELECT ST_AsText(ST_PointFromGeoHash(@gh,0));
+---------------------------------------+
| ST_AsText(ST_PointFromGeoHash(@gh,0)) |
+---------------------------------------+
| POINT(45 -20)                         |
+---------------------------------------+
```

12.15.11 Spatial GeoJSON Functions

This section describes functions for converting between GeoJSON documents and spatial values. GeoJSON is an open standard for encoding geometric/geographical features. For more information, see http://geojson.org. The functions discussed here follow GeoJSON specification revision 1.0.

GeoJSON supports the same geometric/geographic data types that MySQL supports. Feature and FeatureCollection objects are not supported, except that geometry objects are extracted from them. CRS support is limited to values that identify an SRID.

MySQL also supports a native JSON data type and a set of SQL functions to enable operations on JSON values. For more information, see Section 11.6, “The JSON Data Type”, and Section 12.16, “JSON Functions”.

ST_AsGeoJSON(g [, max_dec_digits [, options]])

Generates a GeoJSON object from the geometry g. The object string has the connection character set and collation.

If any argument is NULL, the return value is NULL. If any non-NULL argument is invalid, an error occurs.

max_dec_digits, if specified, limits the number of decimal digits for coordinates and causes rounding of output. If not specified, this argument defaults to its maximum value of 2³² − 1. The minimum is 0.

options, if specified, is a bitmask. The following table shows the permitted flag values. If the geometry argument has an SRID of 0, no CRS object is produced even for those flag values that request one.

Flag Value	Meaning
0	No options. This is the default if `options` is not specified.
1	Add a bounding box to the output.
2	Add a short-format CRS URN to the output. The default format is a short format (`EPSG:srid`).
4	Add a long-format CRS URN (`urn:ogc:def:crs:EPSG::srid`). This flag overrides flag 2. For example, option values of 5 and 7 mean the same (add a bounding box and a long-format CRS URN).

mysql> SELECT ST_AsGeoJSON(ST_GeomFromText('POINT(11.11111 12.22222)'),2);
+-------------------------------------------------------------+
| ST_AsGeoJSON(ST_GeomFromText('POINT(11.11111 12.22222)'),2) |
+-------------------------------------------------------------+
| {"type": "Point", "coordinates": [11.11, 12.22]}            |
+-------------------------------------------------------------+

ST_GeomFromGeoJSON(str [, options [, srid]])

Parses a string str representing a GeoJSON object and returns a geometry.

If any argument is NULL, the return value is NULL. If any non-NULL argument is invalid, an error occurs.

options, if given, describes how to handle GeoJSON documents that contain geometries with coordinate dimensions higher than 2. The following table shows the permitted options values.

Option Value	Meaning
1	Reject the document and produce an error. This is the default if `options` is not specified.
2, 3, 4	Accept the document and strip off the coordinates for higher coordinate dimensions.

options values of 2, 3, and 4 currently produce the same effect. If geometries with coordinate dimensions higher than 2 are supported in the future, these values will produce different effects.

The srid argument, if given, must be a 32-bit unsigned integer. If not given, the geometry return value has an SRID of 4326.

If srid refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.

For geographic SRS geometry arguments, if any argument has a longitude or latitude that is out of range, an error occurs:

If a longitude value is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
If a latitude value is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.

Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.

GeoJSON geometry, feature, and feature collection objects may have a crs property. The parsing function parses named CRS URNs in the urn:ogc:def:crs:EPSG::srid and EPSG:srid namespaces, but not CRSs given as link objects. Also, urn:ogc:def:crs:OGC:1.3:CRS84 is recognized as SRID 4326. If an object has a CRS that is not understood, an error occurs, with the exception that if the optional srid argument is given, any CRS is ignored even if it is invalid.

If a crs member that specifies an SRID different from the top-level object SRID is found at a lower level of the GeoJSON document, an ER_INVALID_GEOJSON_CRS_NOT_TOP_LEVEL error occurs.

As specified in the GeoJSON specification, parsing is case sensitive for the type member of the GeoJSON input (Point, LineString, and so forth). The specification is silent regarding case sensitivity for other parsing, which in MySQL is not case-sensitive.

This example shows the parsing result for a simple GeoJSON object:

mysql> SET @json = '{ "type": "Point", "coordinates": [102.0, 0.0]}';
mysql> SELECT ST_AsText(ST_GeomFromGeoJSON(@json));
+--------------------------------------+
| ST_AsText(ST_GeomFromGeoJSON(@json)) |
+--------------------------------------+
| POINT(102 0)                         |
+--------------------------------------+

12.15.12 Spatial Convenience Functions

The functions in this section provide convenience operations on geometry values.

Unless otherwise specified, functions in this section handle their arguments as follows:

If any argument is NULL, the return value is NULL.
If any geometry argument is not a syntactically well-formed geometry, an ER_GIS_INVALID_DATA error occurs.
If any geometry argument has an SRID value that refers to an undefined spatial reference system (SRS), an ER_SRS_NOT_FOUND error occurs.
For functions that take multiple geometry arguments, if those arguments do not have the same SRID, an ER_GIS_DIFFERENT_SRIDS error occurs.
Otherwise, the return value is non-NULL.

These convenience functions are available:

ST_Distance_Sphere(g1, g2 [, radius])
Returns the mimimum spherical distance between Point or MultiPoint arguments on a sphere, in meters. (For general-purpose distance calculations, see the ST_Distance() function.) The optional radius argument should be given in meters.
If both geometry parameters are valid Cartesian Point or MultiPoint values in SRID 0, the return value is shortest distance between the two geometries on a sphere with the provided radius. If omitted, the default radius is 6,370,986 meters, Point X and Y coordinates are interpreted as longitude and latitude, respectively, in degrees.
If both geometry parameters are valid Point or MultiPoint values in a geographic spatial reference system (SRS), the return value is the shortest distance between the two geometries on a sphere with the provided radius. If omitted, the default radius is equal to the mean radius, defined as (2a+b)/3, where a is the semi-major axis and b is the semi-minor axis of the SRS.
ST_Distance_Sphere() handles its arguments as described in the introduction to this section, with these exceptions:
- Supported geometry argument combinations are Point and Point, or Point and MultiPoint (in any argument order). If at least one of the geometries is neither Point nor MultiPoint, and its SRID is 0, an ER_NOT_IMPLEMENTED_FOR_CARTESIAN_SRS error occurs. If at least one of the geometries is neither Point nor MultiPoint, and its SRID refers to a geographic SRS, an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs. If any geometry refers to a projected SRS, an ER_NOT_IMPLEMENTED_FOR_PROJECTED_SRS error occurs.
- If any argument has a longitude or latitude that is out of range, an error occurs:
  - If any longitude argument is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
  - If any latitude argument is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
  Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.
- If the radius argument is present but not positive, an ER_NONPOSITIVE_RADIUS error occurs.
- If the distance exceeds the range of a double-precision number, an ER_STD_OVERFLOW_ERROR error occurs.
```
mysql> SET @pt1 = ST_GeomFromText('POINT(0 0)');
mysql> SET @pt2 = ST_GeomFromText('POINT(180 0)');
mysql> SELECT ST_Distance_Sphere(@pt1, @pt2);
+--------------------------------+
| ST_Distance_Sphere(@pt1, @pt2) |
+--------------------------------+
|             20015042.813723423 |
+--------------------------------+
```
ST_IsValid(g)
Returns 1 if the argument is geometrically valid, 0 if the argument is not geometrically valid. Geometry validity is defined by the OGC specification.
The only valid empty geometry is represented in the form of an empty geometry collection value. ST_IsValid() returns 1 in this case. MySQL does not support GIS EMPTY values such as POINT EMPTY.
ST_IsValid() handles its arguments as described in the introduction to this section, with this exception:
- If the geometry has a geographic SRS with a longitude or latitude that is out of range, an error occurs:
  - If any longitude argument is not in the range (−180, 180], an ER_LONGITUDE_OUT_OF_RANGE error occurs.
  - If any latitude argument is not in the range [−90, 90], an ER_LATITUDE_OUT_OF_RANGE error occurs.
  Ranges shown are in degrees. If an SRS uses another unit, the range uses the corresponding values in its unit. The exact range limits deviate slightly due to floating-point arithmetic.
```
mysql> SET @ls1 = ST_GeomFromText('LINESTRING(0 0,-0.00 0,0.0 0)');
mysql> SET @ls2 = ST_GeomFromText('LINESTRING(0 0, 1 1)');
mysql> SELECT ST_IsValid(@ls1);
+------------------+
| ST_IsValid(@ls1) |
+------------------+
|                0 |
+------------------+
mysql> SELECT ST_IsValid(@ls2);
+------------------+
| ST_IsValid(@ls2) |
+------------------+
|                1 |
+------------------+
```
ST_MakeEnvelope(pt1, pt2)
Returns the rectangle that forms the envelope around two points, as a Point, LineString, or Polygon.
Calculations are done using the Cartesian coordinate system rather than on a sphere, spheroid, or on earth.
Given two points pt1 and pt2, ST_MakeEnvelope() creates the result geometry on an abstract plane like this:
- If pt1 and pt2 are equal, the result is the point pt1.
- Otherwise, if (pt1, pt2) is a vertical or horizontal line segment, the result is the line segment (pt1, pt2).
- Otherwise, the result is a polygon using pt1 and pt2 as diagonal points.
The result geometry has an SRID of 0.
ST_MakeEnvelope() handles its arguments as described in the introduction to this section, with these exceptions:
- If the arguments are not Point values, an ER_WRONG_ARGUMENTS error occurs.
- An ER_GIS_INVALID_DATA error occurs for the additional condition that any coordinate value of the two points is infinite (that is, NaN),
- If any geometry has an SRID value for a geographic spatial reference system (SRS), an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.
```
mysql> SET @pt1 = ST_GeomFromText('POINT(0 0)');
mysql> SET @pt2 = ST_GeomFromText('POINT(1 1)');
mysql> SELECT ST_AsText(ST_MakeEnvelope(@pt1, @pt2));
+----------------------------------------+
| ST_AsText(ST_MakeEnvelope(@pt1, @pt2)) |
+----------------------------------------+
| POLYGON((0 0,1 0,1 1,0 1,0 0))         |
+----------------------------------------+
```
ST_Simplify(g, max_distance)
Simplifies a geometry using the Douglas-Peucker algorithm and returns a simplified value of the same type.
The geometry may be any geometry type, although the Douglas-Peucker algorithm may not actually process every type. A geometry collection is processed by giving its components one by one to the simplification algorithm, and the returned geometries are put into a geometry collection as result.
The max_distance argument is the distance (in units of the input coordinates) of a vertex to other segments to be removed. Vertices within this distance of the simplified linestring are removed.
According to Boost.Geometry, geometries might become invalid as a result of the simplification process, and the process might create self-intersections. To check the validity of the result, pass it to ST_IsValid().
ST_Simplify() handles its arguments as described in the introduction to this section, with this exception:
- If the max_distance argument is not positive, or is NaN, an ER_WRONG_ARGUMENTS error occurs.
```
mysql> SET @g = ST_GeomFromText('LINESTRING(0 0,0 1,1 1,1 2,2 2,2 3,3 3)');
mysql> SELECT ST_AsText(ST_Simplify(@g, 0.5));
+---------------------------------+
| ST_AsText(ST_Simplify(@g, 0.5)) |
+---------------------------------+
| LINESTRING(0 0,0 1,1 1,2 3,3 3) |
+---------------------------------+
mysql> SELECT ST_AsText(ST_Simplify(@g, 1.0));
+---------------------------------+
| ST_AsText(ST_Simplify(@g, 1.0)) |
+---------------------------------+
| LINESTRING(0 0,3 3)             |
+---------------------------------+
```
ST_Validate(g)
Validates a geometry according to the OGC specification. A geometry can be syntactically well-formed (WKB value plus SRID) but geometrically invalid. For example, this polygon is geometrically invalid: POLYGON((0 0, 0 0, 0 0, 0 0, 0 0))
ST_Validate() returns the geometry if it is syntactically well-formed and is geometrically valid, NULL if the argument is not syntactically well-formed or is not geometrically valid or is NULL.
ST_Validate() can be used to filter out invalid geometry data, although at a cost. For applications that require more precise results not tainted by invalid data, this penalty may be worthwhile.
If the geometry argument is valid, it is returned as is, except that if an input Polygon or MultiPolygon has clockwise rings, those rings are reversed before checking for validity. If the geometry is valid, the value with the reversed rings is returned.
The only valid empty geometry is represented in the form of an empty geometry collection value. ST_Validate() returns it directly without further checks in this case.
ST_Validate() handles its arguments as described in the introduction to this section, with these exceptions:
- If the geometry is not syntactically well-formed, the return value is NULL. An ER_GIS_INVALID_DATA error does not occur.
- If the geometry has an SRID value for a geographic spatial reference system (SRS), an ER_NOT_IMPLEMENTED_FOR_GEOGRAPHIC_SRS error occurs.
```
mysql> SET @ls1 = ST_GeomFromText('LINESTRING(0 0)');
mysql> SET @ls2 = ST_GeomFromText('LINESTRING(0 0, 1 1)');
mysql> SELECT ST_AsText(ST_Validate(@ls1));
+------------------------------+
| ST_AsText(ST_Validate(@ls1)) |
+------------------------------+
| NULL                         |
+------------------------------+
mysql> SELECT ST_AsText(ST_Validate(@ls2));
+------------------------------+
| ST_AsText(ST_Validate(@ls2)) |
+------------------------------+
| LINESTRING(0 0,1 1)          |
+------------------------------+
```

12.16 JSON Functions

12.16.1 JSON Function Reference
12.16.2 Functions That Create JSON Values
12.16.3 Functions That Search JSON Values
12.16.4 Functions That Modify JSON Values
12.16.5 Functions That Return JSON Value Attributes
12.16.6 JSON Table Functions
12.16.7 JSON Utility Functions
12.16.8 JSON Path Syntax

The functions described in this section perform operations on JSON values. For discussion of the JSON data type and additional examples showing how to use these functions, see Section 11.6, “The JSON Data Type”.

For functions that take a JSON argument, an error occurs if the argument is not a valid JSON value. Arguments parsed as JSON are indicated by json_doc; arguments indicated by val are not parsed.

A set of spatial functions for operating on GeoJSON values is also available. See Section 12.15.11, “Spatial GeoJSON Functions”.

12.16.1 JSON Function Reference

Table 12.20 JSON Functions

Name	Description
`JSON_ARRAY()`	Create JSON array
`JSON_ARRAY_APPEND()`	Append data to JSON document
`JSON_ARRAY_INSERT()`	Insert into JSON array
`->`	Return value from JSON column after evaluating path; equivalent to JSON_EXTRACT().
`JSON_CONTAINS()`	Whether JSON document contains specific object at path
`JSON_CONTAINS_PATH()`	Whether JSON document contains any data at path
`JSON_DEPTH()`	Maximum depth of JSON document
`JSON_EXTRACT()`	Return data from JSON document
`->>`	Return value from JSON column after evaluating path and unquoting the result; equivalent to JSON_UNQUOTE(JSON_EXTRACT()).
`JSON_INSERT()`	Insert data into JSON document
`JSON_KEYS()`	Array of keys from JSON document
`JSON_LENGTH()`	Number of elements in JSON document
`JSON_MERGE()` (deprecated 8.0.3)	Merge JSON documents, preserving duplicate keys. Deprecated synonym for JSON_MERGE_PRESERVE()
`JSON_MERGE_PATCH()`	Merge JSON documents, replacing values of duplicate keys
`JSON_MERGE_PRESERVE()`	Merge JSON documents, preserving duplicate keys
`JSON_OBJECT()`	Create JSON object
`JSON_PRETTY()`	Prints a JSON document in human-readable format, with each array element or object member printed on a new line, indented two spaces with respect to its parent.
`JSON_QUOTE()`	Quote JSON document
`JSON_REMOVE()`	Remove data from JSON document
`JSON_REPLACE()`	Replace values in JSON document
`JSON_SEARCH()`	Path to value within JSON document
`JSON_SET()`	Insert data into JSON document
`JSON_STORAGE_FREE()`	Freed space within binary representation of a JSON column value following a partial update
`JSON_STORAGE_SIZE()`	Space used for storage of binary representation of a JSON document; for a JSON column, the space used when the document was inserted, prior to any partial updates
`JSON_TABLE()`	Returns data from a JSON expression as a relational table
`JSON_TYPE()`	Type of JSON value
`JSON_UNQUOTE()`	Unquote JSON value
`JSON_VALID()`	Whether JSON value is valid

MySQL supports two aggregate JSON functions JSON_ARRAYAGG() and JSON_OBJECTAGG(). See Section 12.19, “Aggregate (GROUP BY) Functions”, for descriptions of these.

MySQL also supports “pretty-printing” of JSON values in an easy-to-read format, using the JSON_PRETTY() function. You can see how much storage space a given JSON value takes up, and how much space remains for additional storage, using JSON_STORAGE_SIZE() and JSON_STORAGE_FREE(), respectively. For complete descriptions of these functions, see Section 12.16.7, “JSON Utility Functions”.

12.16.2 Functions That Create JSON Values

The functions listed in this section compose JSON values from component elements.

JSON_ARRAY([val[, val] ...])

Evaluates a (possibly empty) list of values and returns a JSON array containing those values.

mysql> SELECT JSON_ARRAY(1, "abc", NULL, TRUE, CURTIME());
+---------------------------------------------+
| JSON_ARRAY(1, "abc", NULL, TRUE, CURTIME()) |
+---------------------------------------------+
| [1, "abc", null, true, "11:30:24.000000"]   |
+---------------------------------------------+

JSON_OBJECT([key, val[, key, val] ...])

Evaluates a (possibly empty) list of key-value pairs and returns a JSON object containing those pairs. An error occurs if any key name is NULL or the number of arguments is odd.

mysql> SELECT JSON_OBJECT('id', 87, 'name', 'carrot');
+-----------------------------------------+
| JSON_OBJECT('id', 87, 'name', 'carrot') |
+-----------------------------------------+
| {"id": 87, "name": "carrot"}            |
+-----------------------------------------+

JSON_QUOTE(string)
Quotes a string as a JSON value by wrapping it with double quote characters and escaping interior quote and other characters, then returning the result as a utf8mb4 string. Returns NULL if the argument is NULL.
This function is typically used to produce a valid JSON string literal for inclusion within a JSON document.
Certain special characters are escaped with backslashes per the escape sequences shown in Table 12.21, “JSON_UNQUOTE() Special Character Escape Sequences”.
```
mysql> SELECT JSON_QUOTE('null'), JSON_QUOTE('"null"');
+--------------------+----------------------+
| JSON_QUOTE('null') | JSON_QUOTE('"null"') |
+--------------------+----------------------+
| "null"             | "\"null\""           |
+--------------------+----------------------+
mysql> SELECT JSON_QUOTE('[1, 2, 3]');
+-------------------------+
| JSON_QUOTE('[1, 2, 3]') |
+-------------------------+
| "[1, 2, 3]"             |
+-------------------------+
```

You can also obtain JSON values by casting values of other types to the JSON type using CAST(value AS JSON); see Converting between JSON and non-JSON values, for more information.

Two aggregate functions generating JSON values are available. JSON_ARRAYAGG() returns a result set as a single JSON array, and JSON_OBJECTAGG() returns a result set as a single JSON object. For more information, see Section 12.19, “Aggregate (GROUP BY) Functions”.

12.16.3 Functions That Search JSON Values

The functions in this section perform search operations on JSON values to extract data from them, report whether data exists at a location within them, or report the path to data within them.

JSON_CONTAINS(target, candidate[, path])
Indicates by returning 1 or 0 whether a given candidate JSON document is contained within a target JSON document, or—if a path argument was supplied—whether the candidate is found at a specific path within the target. Returns NULL if any argument is NULL, or if the path argument does not identify a section of the target document. An error occurs if target or candidate is not a valid JSON document, or if the path argument is not a valid path expression or contains a * or ** wildcard.
To check only whether any data exists at the path, use JSON_CONTAINS_PATH() instead.
The following rules define containment:
- A candidate scalar is contained in a target scalar if and only if they are comparable and are equal. Two scalar values are comparable if they have the same JSON_TYPE() types, with the exception that values of types INTEGER and DECIMAL are also comparable to each other.
- A candidate array is contained in a target array if and only if every element in the candidate is contained in some element of the target.
- A candidate nonarray is contained in a target array if and only if the candidate is contained in some element of the target.
- A candidate object is contained in a target object if and only if for each key in the candidate there is a key with the same name in the target and the value associated with the candidate key is contained in the value associated with the target key.
Otherwise, the candidate value is not contained in the target document.
```
mysql> SET @j = '{"a": 1, "b": 2, "c": {"d": 4}}';
mysql> SET @j2 = '1';
mysql> SELECT JSON_CONTAINS(@j, @j2, '$.a');
+-------------------------------+
| JSON_CONTAINS(@j, @j2, '$.a') |
+-------------------------------+
|                             1 |
+-------------------------------+
mysql> SELECT JSON_CONTAINS(@j, @j2, '$.b');
+-------------------------------+
| JSON_CONTAINS(@j, @j2, '$.b') |
+-------------------------------+
|                             0 |
+-------------------------------+

mysql> SET @j2 = '{"d": 4}';
mysql> SELECT JSON_CONTAINS(@j, @j2, '$.a');
+-------------------------------+
| JSON_CONTAINS(@j, @j2, '$.a') |
+-------------------------------+
|                             0 |
+-------------------------------+
mysql> SELECT JSON_CONTAINS(@j, @j2, '$.c');
+-------------------------------+
| JSON_CONTAINS(@j, @j2, '$.c') |
+-------------------------------+
|                             1 |
+-------------------------------+
```

JSON_CONTAINS_PATH(json_doc, one_or_all, path[, path] ...)

Returns 0 or 1 to indicate whether a JSON document contains data at a given path or paths. Returns NULL if any argument is NULL. An error occurs if the json_doc argument is not a valid JSON document, any path argument is not a valid path expression, or one_or_all is not 'one' or 'all'.

To check for a specific value at a path, use JSON_CONTAINS() instead.

The return value is 0 if no specified path exists within the document. Otherwise, the return value depends on the one_or_all argument:

'one': 1 if at least one path exists within the document, 0 otherwise.
'all': 1 if all paths exist within the document, 0 otherwise.

mysql> SET @j = '{"a": 1, "b": 2, "c": {"d": 4}}';
mysql> SELECT JSON_CONTAINS_PATH(@j, 'one', '$.a', '$.e');
+---------------------------------------------+
| JSON_CONTAINS_PATH(@j, 'one', '$.a', '$.e') |
+---------------------------------------------+
|                                           1 |
+---------------------------------------------+
mysql> SELECT JSON_CONTAINS_PATH(@j, 'all', '$.a', '$.e');
+---------------------------------------------+
| JSON_CONTAINS_PATH(@j, 'all', '$.a', '$.e') |
+---------------------------------------------+
|                                           0 |
+---------------------------------------------+
mysql> SELECT JSON_CONTAINS_PATH(@j, 'one', '$.c.d');
+----------------------------------------+
| JSON_CONTAINS_PATH(@j, 'one', '$.c.d') |
+----------------------------------------+
|                                      1 |
+----------------------------------------+
mysql> SELECT JSON_CONTAINS_PATH(@j, 'one', '$.a.d');
+----------------------------------------+
| JSON_CONTAINS_PATH(@j, 'one', '$.a.d') |
+----------------------------------------+
|                                      0 |
+----------------------------------------+

JSON_EXTRACT(json_doc, path[, path] ...)
Returns data from a JSON document, selected from the parts of the document matched by the path arguments. Returns NULL if any argument is NULL or no paths locate a value in the document. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression.
The return value consists of all values matched by the path arguments. If it is possible that those arguments could return multiple values, the matched values are autowrapped as an array, in the order corresponding to the paths that produced them. Otherwise, the return value is the single matched value.
```
mysql> SELECT JSON_EXTRACT('[10, 20, [30, 40]]', '$[1]');
+--------------------------------------------+
| JSON_EXTRACT('[10, 20, [30, 40]]', '$[1]') |
+--------------------------------------------+
| 20                                         |
+--------------------------------------------+
mysql> SELECT JSON_EXTRACT('[10, 20, [30, 40]]', '$[1]', '$[0]');
+----------------------------------------------------+
| JSON_EXTRACT('[10, 20, [30, 40]]', '$[1]', '$[0]') |
+----------------------------------------------------+
| [20, 10]                                           |
+----------------------------------------------------+
mysql> SELECT JSON_EXTRACT('[10, 20, [30, 40]]', '$[2][*]');
+-----------------------------------------------+
| JSON_EXTRACT('[10, 20, [30, 40]]', '$[2][*]') |
+-----------------------------------------------+
| [30, 40]                                      |
+-----------------------------------------------+
```
MySQL supports the -> operator as shorthand for this function as used with 2 arguments where the left hand side is a JSON column identifier (not an expression) and the right hand side is the JSON path to be matched within the column.

column->path

The -> operator serves as an alias for the JSON_EXTRACT() function when used with two arguments, a column identifier on the left and a JSON path on the right that is evaluated against the JSON document (the column value). You can use such expressions in place of column identifiers wherever they occur in SQL statements.

The two SELECT statements shown here produce the same output:

mysql> SELECT c, JSON_EXTRACT(c, "$.id"), g
     > FROM jemp
     > WHERE JSON_EXTRACT(c, "$.id") > 1
     > ORDER BY JSON_EXTRACT(c, "$.name");
+-------------------------------+-----------+------+
| c                             | c->"$.id" | g    |
+-------------------------------+-----------+------+
| {"id": "3", "name": "Barney"} | "3"       |    3 |
| {"id": "4", "name": "Betty"}  | "4"       |    4 |
| {"id": "2", "name": "Wilma"}  | "2"       |    2 |
+-------------------------------+-----------+------+
3 rows in set (0.00 sec)

mysql> SELECT c, c->"$.id", g
     > FROM jemp
     > WHERE c->"$.id" > 1
     > ORDER BY c->"$.name";
+-------------------------------+-----------+------+
| c                             | c->"$.id" | g    |
+-------------------------------+-----------+------+
| {"id": "3", "name": "Barney"} | "3"       |    3 |
| {"id": "4", "name": "Betty"}  | "4"       |    4 |
| {"id": "2", "name": "Wilma"}  | "2"       |    2 |
+-------------------------------+-----------+------+
3 rows in set (0.00 sec)

This functionality is not limited to SELECT, as shown here:

mysql> ALTER TABLE jemp ADD COLUMN n INT;
Query OK, 0 rows affected (0.68 sec)
Records: 0  Duplicates: 0  Warnings: 0

mysql> UPDATE jemp SET n=1 WHERE c->"$.id" = "4";
Query OK, 1 row affected (0.04 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT c, c->"$.id", g, n
     > FROM jemp
     > WHERE JSON_EXTRACT(c, "$.id") > 1
     > ORDER BY c->"$.name";
+-------------------------------+-----------+------+------+
| c                             | c->"$.id" | g    | n    |
+-------------------------------+-----------+------+------+
| {"id": "3", "name": "Barney"} | "3"       |    3 | NULL |
| {"id": "4", "name": "Betty"}  | "4"       |    4 |    1 |
| {"id": "2", "name": "Wilma"}  | "2"       |    2 | NULL |
+-------------------------------+-----------+------+------+
3 rows in set (0.00 sec)

mysql> DELETE FROM jemp WHERE c->"$.id" = "4";
Query OK, 1 row affected (0.04 sec)

mysql> SELECT c, c->"$.id", g, n
     > FROM jemp
     > WHERE JSON_EXTRACT(c, "$.id") > 1
     > ORDER BY c->"$.name";
+-------------------------------+-----------+------+------+
| c                             | c->"$.id" | g    | n    |
+-------------------------------+-----------+------+------+
| {"id": "3", "name": "Barney"} | "3"       |    3 | NULL |
| {"id": "2", "name": "Wilma"}  | "2"       |    2 | NULL |
+-------------------------------+-----------+------+------+
2 rows in set (0.00 sec)

(See Indexing a Generated Column to Provide a JSON Column Index, for the statements used to create and populate the table just shown.)

This also works with JSON array values, as shown here:

mysql> CREATE TABLE tj10 (a JSON, b INT);
Query OK, 0 rows affected (0.26 sec)

mysql> INSERT INTO tj10
     > VALUES ("[3,10,5,17,44]", 33), ("[3,10,5,17,[22,44,66]]", 0);
Query OK, 1 row affected (0.04 sec)

mysql> SELECT a->"$[4]" FROM tj10;
+--------------+
| a->"$[4]"    |
+--------------+
| 44           |
| [22, 44, 66] |
+--------------+
2 rows in set (0.00 sec)

mysql> SELECT * FROM tj10 WHERE a->"$[0]" = 3;
+------------------------------+------+
| a                            | b    |
+------------------------------+------+
| [3, 10, 5, 17, 44]           |   33 |
| [3, 10, 5, 17, [22, 44, 66]] |    0 |
+------------------------------+------+
2 rows in set (0.00 sec)

Nested arrays are supported. An expression using -> evaluates as NULL if no matching key is found in the target JSON document, as shown here:

mysql> SELECT * FROM tj10 WHERE a->"$[4][1]" IS NOT NULL;
+------------------------------+------+
| a                            | b    |
+------------------------------+------+
| [3, 10, 5, 17, [22, 44, 66]] |    0 |
+------------------------------+------+

mysql> SELECT a->"$[4][1]" FROM tj10;
+--------------+
| a->"$[4][1]" |
+--------------+
| NULL         |
| 44           |
+--------------+
2 rows in set (0.00 sec)

This is the same behavior as seen in such cases when using JSON_EXTRACT():

mysql> SELECT JSON_EXTRACT(a, "$[4][1]") FROM tj10;
+----------------------------+
| JSON_EXTRACT(a, "$[4][1]") |
+----------------------------+
| NULL                       |
| 44                         |
+----------------------------+
2 rows in set (0.00 sec)

column->>path

This is an improved, unquoting extraction operator. Whereas the -> operator simply extracts a value, the ->> operator in addition unquotes the extracted result. In other words, given a JSON column value column and a path expression path, the following three expressions return the same value:

JSON_UNQUOTE( JSON_EXTRACT(column, path) )
JSON_UNQUOTE(column -> path)
column->>path

The ->> operator can be used wherever JSON_UNQUOTE(JSON_EXTRACT()) would be allowed. This includes (but is not limited to) SELECT lists, WHERE and HAVING clauses, and ORDER BY and GROUP BY clauses.

The next few statements demonstrate some ->> operator equivalences with other expressions in the mysql client:

mysql> SELECT * FROM jemp WHERE g > 2;
+-------------------------------+------+
| c                             | g    |
+-------------------------------+------+
| {"id": "3", "name": "Barney"} |    3 |
| {"id": "4", "name": "Betty"}  |    4 |
+-------------------------------+------+
2 rows in set (0.01 sec)

mysql> SELECT c->'$.name' AS name
    ->     FROM jemp WHERE g > 2;
+----------+
| name     |
+----------+
| "Barney" |
| "Betty"  |
+----------+
2 rows in set (0.00 sec)

mysql> SELECT JSON_UNQUOTE(c->'$.name') AS name
    ->     FROM jemp WHERE g > 2;
+--------+
| name   |
+--------+
| Barney |
| Betty  |
+--------+
2 rows in set (0.00 sec)

mysql> SELECT c->>'$.name' AS name
    ->     FROM jemp WHERE g > 2;
+--------+
| name   |
+--------+
| Barney |
| Betty  |
+--------+
2 rows in set (0.00 sec)

See Indexing a Generated Column to Provide a JSON Column Index, for the SQL statements used to create and populate the jemp table in the set of examples just shown.

This operator can also be used with JSON arrays, as shown here:

mysql> CREATE TABLE tj10 (a JSON, b INT);
Query OK, 0 rows affected (0.26 sec)

mysql> INSERT INTO tj10 VALUES
    ->     ('[3,10,5,"x",44]', 33),
    ->     ('[3,10,5,17,[22,"y",66]]', 0);
Query OK, 2 rows affected (0.04 sec)
Records: 2  Duplicates: 0  Warnings: 0

mysql> SELECT a->"$[3]", a->"$[4][1]" FROM tj10;
+-----------+--------------+
| a->"$[3]" | a->"$[4][1]" |
+-----------+--------------+
| "x"       | NULL         |
| 17        | "y"          |
+-----------+--------------+
2 rows in set (0.00 sec)

mysql> SELECT a->>"$[3]", a->>"$[4][1]" FROM tj10;
+------------+---------------+
| a->>"$[3]" | a->>"$[4][1]" |
+------------+---------------+
| x          | NULL          |
| 17         | y             |
+------------+---------------+
2 rows in set (0.00 sec)

As with ->, the ->> operator is always expanded in the output of EXPLAIN, as the following example demonstrates:

mysql> EXPLAIN SELECT c->>'$.name' AS name
    ->     FROM jemp WHERE g > 2\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: jemp
   partitions: NULL
         type: range
possible_keys: i
          key: i
      key_len: 5
          ref: NULL
         rows: 2
     filtered: 100.00
        Extra: Using where
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS\G
*************************** 1. row ***************************
  Level: Note
   Code: 1003
Message: /* select#1 */ select
json_unquote(json_extract(`jtest`.`jemp`.`c`,'$.name')) AS `name` from
`jtest`.`jemp` where (`jtest`.`jemp`.`g` > 2)
1 row in set (0.00 sec)

This is similar to how MySQL expands the -> operator in the same circumstances.

JSON_KEYS(json_doc[, path])
Returns the keys from the top-level value of a JSON object as a JSON array, or, if a path argument is given, the top-level keys from the selected path. Returns NULL if any argument is NULL, the json_doc argument is not an object, or path, if given, does not locate an object. An error occurs if the json_doc argument is not a valid JSON document or the path argument is not a valid path expression or contains a * or ** wildcard.
The result array is empty if the selected object is empty. If the top-level value has nested subobjects, the return value does not include keys from those subobjects.
```
mysql> SELECT JSON_KEYS('{"a": 1, "b": {"c": 30}}');
+---------------------------------------+
| JSON_KEYS('{"a": 1, "b": {"c": 30}}') |
+---------------------------------------+
| ["a", "b"]                            |
+---------------------------------------+
mysql> SELECT JSON_KEYS('{"a": 1, "b": {"c": 30}}', '$.b');
+----------------------------------------------+
| JSON_KEYS('{"a": 1, "b": {"c": 30}}', '$.b') |
+----------------------------------------------+
| ["c"]                                        |
+----------------------------------------------+
```

JSON_SEARCH(json_doc, one_or_all, search_str[, escape_char[, path] ...])

Returns the path to the given string within a JSON document. Returns NULL if any of the json_doc, search_str, or path arguments are NULL; no path exists within the document; or search_str is not found. An error occurs if the json_doc argument is not a valid JSON document, any path argument is not a valid path expression, one_or_all is not 'one' or 'all', or escape_char is not a constant expression.

The one_or_all argument affects the search as follows:

'one': The search terminates after the first match and returns one path string. It is undefined which match is considered first.
'all': The search returns all matching path strings such that no duplicate paths are included. If there are multiple strings, they are autowrapped as an array. The order of the array elements is undefined.

Within the search_str search string argument, the % and _ characters work as for the LIKE operator: % matches any number of characters (including zero characters), and _ matches exactly one character.

To specify a literal % or _ character in the search string, precede it by the escape character. The default is \ if the escape_char argument is missing or NULL. Otherwise, escape_char must be a constant that is empty or one character.

For more information about matching and escape character behavior, see the description of LIKE in Section 12.5.1, “String Comparison Functions”. For escape character handling, a difference from the LIKE behavior is that the escape character for JSON_SEARCH() must evaluate to a constant at compile time, not just at execution time. For example, if JSON_SEARCH() is used in a prepared statement and the escape_char argument is supplied using a ? parameter, the parameter value might be constant at execution time, but is not at compile time.

mysql> SET @j = '["abc", [{"k": "10"}, "def"], {"x":"abc"}, {"y":"bcd"}]';

mysql> SELECT JSON_SEARCH(@j, 'one', 'abc');
+-------------------------------+
| JSON_SEARCH(@j, 'one', 'abc') |
+-------------------------------+
| "$[0]"                        |
+-------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', 'abc');
+-------------------------------+
| JSON_SEARCH(@j, 'all', 'abc') |
+-------------------------------+
| ["$[0]", "$[2].x"]            |
+-------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', 'ghi');
+-------------------------------+
| JSON_SEARCH(@j, 'all', 'ghi') |
+-------------------------------+
| NULL                          |
+-------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10');
+------------------------------+
| JSON_SEARCH(@j, 'all', '10') |
+------------------------------+
| "$[1][0].k"                  |
+------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10', NULL, '$');
+-----------------------------------------+
| JSON_SEARCH(@j, 'all', '10', NULL, '$') |
+-----------------------------------------+
| "$[1][0].k"                             |
+-----------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10', NULL, '$[*]');
+--------------------------------------------+
| JSON_SEARCH(@j, 'all', '10', NULL, '$[*]') |
+--------------------------------------------+
| "$[1][0].k"                                |
+--------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10', NULL, '$**.k');
+---------------------------------------------+
| JSON_SEARCH(@j, 'all', '10', NULL, '$**.k') |
+---------------------------------------------+
| "$[1][0].k"                                 |
+---------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10', NULL, '$[*][0].k');
+-------------------------------------------------+
| JSON_SEARCH(@j, 'all', '10', NULL, '$[*][0].k') |
+-------------------------------------------------+
| "$[1][0].k"                                     |
+-------------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10', NULL, '$[1]');
+--------------------------------------------+
| JSON_SEARCH(@j, 'all', '10', NULL, '$[1]') |
+--------------------------------------------+
| "$[1][0].k"                                |
+--------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '10', NULL, '$[1][0]');
+-----------------------------------------------+
| JSON_SEARCH(@j, 'all', '10', NULL, '$[1][0]') |
+-----------------------------------------------+
| "$[1][0].k"                                   |
+-----------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', 'abc', NULL, '$[2]');
+---------------------------------------------+
| JSON_SEARCH(@j, 'all', 'abc', NULL, '$[2]') |
+---------------------------------------------+
| "$[2].x"                                    |
+---------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%a%');
+-------------------------------+
| JSON_SEARCH(@j, 'all', '%a%') |
+-------------------------------+
| ["$[0]", "$[2].x"]            |
+-------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%b%');
+-------------------------------+
| JSON_SEARCH(@j, 'all', '%b%') |
+-------------------------------+
| ["$[0]", "$[2].x", "$[3].y"]  |
+-------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%b%', NULL, '$[0]');
+---------------------------------------------+
| JSON_SEARCH(@j, 'all', '%b%', NULL, '$[0]') |
+---------------------------------------------+
| "$[0]"                                      |
+---------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%b%', NULL, '$[2]');
+---------------------------------------------+
| JSON_SEARCH(@j, 'all', '%b%', NULL, '$[2]') |
+---------------------------------------------+
| "$[2].x"                                    |
+---------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%b%', NULL, '$[1]');
+---------------------------------------------+
| JSON_SEARCH(@j, 'all', '%b%', NULL, '$[1]') |
+---------------------------------------------+
| NULL                                        |
+---------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%b%', '', '$[1]');
+-------------------------------------------+
| JSON_SEARCH(@j, 'all', '%b%', '', '$[1]') |
+-------------------------------------------+
| NULL                                      |
+-------------------------------------------+

mysql> SELECT JSON_SEARCH(@j, 'all', '%b%', '', '$[3]');
+-------------------------------------------+
| JSON_SEARCH(@j, 'all', '%b%', '', '$[3]') |
+-------------------------------------------+
| "$[3].y"                                  |
+-------------------------------------------+

For more information about the JSON path syntax supported by MySQL, including rules governing the wildcard operators * and **, see Section 12.16.8, “JSON Path Syntax”.

12.16.4 Functions That Modify JSON Values

The functions in this section modify JSON values and return the result.

JSON_ARRAY_APPEND(json_doc, path, val[, path, val] ...)

Appends values to the end of the indicated arrays within a JSON document and returns the result. Returns NULL if any argument is NULL. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression or contains a * or ** wildcard.

The path-value pairs are evaluated left to right. The document produced by evaluating one pair becomes the new value against which the next pair is evaluated.

If a path selects a scalar or object value, that value is autowrapped within an array and the new value is added to that array. Pairs for which the path does not identify any value in the JSON document are ignored.

mysql> SET @j = '["a", ["b", "c"], "d"]';
mysql> SELECT JSON_ARRAY_APPEND(@j, '$[1]', 1);
+----------------------------------+
| JSON_ARRAY_APPEND(@j, '$[1]', 1) |
+----------------------------------+
| ["a", ["b", "c", 1], "d"]        |
+----------------------------------+
mysql> SELECT JSON_ARRAY_APPEND(@j, '$[0]', 2);
+----------------------------------+
| JSON_ARRAY_APPEND(@j, '$[0]', 2) |
+----------------------------------+
| [["a", 2], ["b", "c"], "d"]      |
+----------------------------------+
mysql> SELECT JSON_ARRAY_APPEND(@j, '$[1][0]', 3);
+-------------------------------------+
| JSON_ARRAY_APPEND(@j, '$[1][0]', 3) |
+-------------------------------------+
| ["a", [["b", 3], "c"], "d"]         |
+-------------------------------------+

mysql> SET @j = '{"a": 1, "b": [2, 3], "c": 4}';
mysql> SELECT JSON_ARRAY_APPEND(@j, '$.b', 'x');
+------------------------------------+
| JSON_ARRAY_APPEND(@j, '$.b', 'x')  |
+------------------------------------+
| {"a": 1, "b": [2, 3, "x"], "c": 4} |
+------------------------------------+
mysql> SELECT JSON_ARRAY_APPEND(@j, '$.c', 'y');
+--------------------------------------+
| JSON_ARRAY_APPEND(@j, '$.c', 'y')    |
+--------------------------------------+
| {"a": 1, "b": [2, 3], "c": [4, "y"]} |
+--------------------------------------+

mysql> SET @j = '{"a": 1}';
mysql> SELECT JSON_ARRAY_APPEND(@j, '$', 'z');
+---------------------------------+
| JSON_ARRAY_APPEND(@j, '$', 'z') |
+---------------------------------+
| [{"a": 1}, "z"]                 |
+---------------------------------+

In MySQL 5.7, this function was named JSON_APPEND(). That name is no longer supported in MySQL 8.0.

JSON_ARRAY_INSERT(json_doc, path, val[, path, val] ...)

Updates a JSON document, inserting into an array within the document and returning the modified document. Returns NULL if any argument is NULL. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression or contains a * or ** wildcard or does not end with an array element identifier.

The path-value pairs are evaluated left to right. The document produced by evaluating one pair becomes the new value against which the next pair is evaluated.

Pairs for which the path does not identify any array in the JSON document are ignored. If a path identifies an array element, the corresponding value is inserted at that element position, shifting any following values to the right. If a path identifies an array position past the end of an array, the value is inserted at the end of the array.

mysql> SET @j = '["a", {"b": [1, 2]}, [3, 4]]';
mysql> SELECT JSON_ARRAY_INSERT(@j, '$[1]', 'x');
+------------------------------------+
| JSON_ARRAY_INSERT(@j, '$[1]', 'x') |
+------------------------------------+
| ["a", "x", {"b": [1, 2]}, [3, 4]]  |
+------------------------------------+
mysql> SELECT JSON_ARRAY_INSERT(@j, '$[100]', 'x');
+--------------------------------------+
| JSON_ARRAY_INSERT(@j, '$[100]', 'x') |
+--------------------------------------+
| ["a", {"b": [1, 2]}, [3, 4], "x"]    |
+--------------------------------------+
mysql> SELECT JSON_ARRAY_INSERT(@j, '$[1].b[0]', 'x');
+-----------------------------------------+
| JSON_ARRAY_INSERT(@j, '$[1].b[0]', 'x') |
+-----------------------------------------+
| ["a", {"b": ["x", 1, 2]}, [3, 4]]       |
+-----------------------------------------+
mysql> SELECT JSON_ARRAY_INSERT(@j, '$[2][1]', 'y');
+---------------------------------------+
| JSON_ARRAY_INSERT(@j, '$[2][1]', 'y') |
+---------------------------------------+
| ["a", {"b": [1, 2]}, [3, "y", 4]]     |
+---------------------------------------+
mysql> SELECT JSON_ARRAY_INSERT(@j, '$[0]', 'x', '$[2][1]', 'y');
+----------------------------------------------------+
| JSON_ARRAY_INSERT(@j, '$[0]', 'x', '$[2][1]', 'y') |
+----------------------------------------------------+
| ["x", "a", {"b": [1, 2]}, [3, 4]]                  |
+----------------------------------------------------+

Earlier modifications affect the positions of the following elements in the array, so subsequent paths in the same JSON_ARRAY_INSERT() call should take this into account. In the final example, the second path inserts nothing because the path no longer matches anything after the first insert.

JSON_INSERT(json_doc, path, val[, path, val] ...)
Inserts data into a JSON document and returns the result. Returns NULL if any argument is NULL. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression or contains a * or ** wildcard.
The path-value pairs are evaluated left to right. The document produced by evaluating one pair becomes the new value against which the next pair is evaluated.
A path-value pair for an existing path in the document is ignored and does not overwrite the existing document value. A path-value pair for a nonexisting path in the document adds the value to the document if the path identifies one of these types of values:
- A member not present in an existing object. The member is added to the object and associated with the new value.
- A position past the end of an existing array. The array is extended with the new value. If the existing value is not an array, it is autowrapped as an array, then extended with the new value.
Otherwise, a path-value pair for a nonexisting path in the document is ignored and has no effect.
For a comparison of JSON_INSERT(), JSON_REPLACE(), and JSON_SET(), see the discussion of JSON_SET().
```
mysql> SET @j = '{ "a": 1, "b": [2, 3]}';
mysql> SELECT JSON_INSERT(@j, '$.a', 10, '$.c', '[true, false]');
+----------------------------------------------------+
| JSON_INSERT(@j, '$.a', 10, '$.c', '[true, false]') |
+----------------------------------------------------+
| {"a": 1, "b": [2, 3], "c": "[true, false]"}        |
+----------------------------------------------------+
```
The third and final value listed in the result is a quoted string and not an array like the second one (which is not quoted in the output); no casting of values to the JSON type is performed. To insert the array as an array, you must perform such casts explicitly, as shown here:
```
mysql> SELECT JSON_INSERT(@j, '$.a', 10, '$.c', CAST('[true, false]' AS JSON));
+------------------------------------------------------------------+
| JSON_INSERT(@j, '$.a', 10, '$.c', CAST('[true, false]' AS JSON)) |
+------------------------------------------------------------------+
| {"a": 1, "b": [2, 3], "c": [true, false]}                        |
+------------------------------------------------------------------+
1 row in set (0.00 sec)
```

JSON_MERGE(json_doc, json_doc[, json_doc] ...)

Merges two or more JSON documents. Synonym for JSON_MERGE_PRESERVE(); deprecated in MySQL 8.0.3 and subject to removal in a future release.

mysql> SELECT JSON_MERGE('[1, 2]', '[true, false]');
+---------------------------------------+
| JSON_MERGE('[1, 2]', '[true, false]') |
+---------------------------------------+
| [1, 2, true, false]                   |
+---------------------------------------+
1 row in set, 1 warning (0.00 sec)

mysql> SHOW WARNINGS\G
*************************** 1. row ***************************
  Level: Warning
   Code: 1287
Message: 'JSON_MERGE' is deprecated and will be removed in a future release. \
 Please use JSON_MERGE_PRESERVE/JSON_MERGE_PATCH instead
1 row in set (0.00 sec)

For additional examples, see the entry for JSON_MERGE_PRESERVE().

JSON_MERGE_PATCH(json_doc, json_doc[, json_doc] ...)

Performs an RFC 7396 compliant merge of two or more JSON documents and returns the merged result, without preserving members having duplicate keys. Raises an error if at least one of the documents passed as arguments to this function is not valid.

Note

For an explanation and example of the differences between this function and JSON_MERGE_PRESERVE(), see JSON_MERGE_PATCH() compared with JSON_MERGE_PRESERVE().

JSON_MERGE_PATCH() performs a merge as follows:

If the first argument is not an object, the result of the merge is the same as if an empty object had been merged with the second argument.
If the second argument is not an object, the result of the merge is the second argument.
If both arguments are objects, the result of the merge is an object with the following members:
- All members of the first object which do not have a corresponding member with the same key in the second object.
- All members of the second object which do not have a corresponding key in the first object, and whose value is not the JSON null literal.
- All members with a key that exists in both the first and the second object, and whose value in the second object is not the JSON null literal. The values of these members are the results of recursively merging the value in the first object with the value in the second object.

For additional information, see Normalization, Merging, and Autowrapping of JSON Values.

mysql> SELECT JSON_MERGE_PATCH('[1, 2]', '[true, false]');
+---------------------------------------------+
| JSON_MERGE_PATCH('[1, 2]', '[true, false]') |
+---------------------------------------------+
| [true, false]                               |
+---------------------------------------------+

mysql> SELECT JSON_MERGE_PATCH('{"name": "x"}', '{"id": 47}');
+-------------------------------------------------+
| JSON_MERGE_PATCH('{"name": "x"}', '{"id": 47}') |
+-------------------------------------------------+
| {"id": 47, "name": "x"}                         |
+-------------------------------------------------+

mysql> SELECT JSON_MERGE_PATCH('1', 'true');
+-------------------------------+
| JSON_MERGE_PATCH('1', 'true') |
+-------------------------------+
| true                          |
+-------------------------------+

mysql> SELECT JSON_MERGE_PATCH('[1, 2]', '{"id": 47}');
+------------------------------------------+
| JSON_MERGE_PATCH('[1, 2]', '{"id": 47}') |
+------------------------------------------+
| {"id": 47}                               |
+------------------------------------------+

mysql> SELECT JSON_MERGE_PATCH('{ "a": 1, "b":2 }',
     >     '{ "a": 3, "c":4 }');
+-----------------------------------------------------------+
| JSON_MERGE_PATCH('{ "a": 1, "b":2 }','{ "a": 3, "c":4 }') |
+-----------------------------------------------------------+
| {"a": 3, "b": 2, "c": 4}                                  |
+-----------------------------------------------------------+

mysql> SELECT JSON_MERGE_PATCH('{ "a": 1, "b":2 }','{ "a": 3, "c":4 }',
     >     '{ "a": 5, "d":6 }');
+-------------------------------------------------------------------------------+
| JSON_MERGE_PATCH('{ "a": 1, "b":2 }','{ "a": 3, "c":4 }','{ "a": 5, "d":6 }') |
+-------------------------------------------------------------------------------+
| {"a": 5, "b": 2, "c": 4, "d": 6}                                              |
+-------------------------------------------------------------------------------+

You can use this function to remove a member by specifying null as the value of the same member in the seond argument, as shown here:

mysql> SELECT JSON_MERGE_PATCH('{"a":1, "b":2}', '{"b":null}');
+--------------------------------------------------+
| JSON_MERGE_PATCH('{"a":1, "b":2}', '{"b":null}') |
+--------------------------------------------------+
| {"a": 1}                                         |
+--------------------------------------------------+

This example shows that the function operates in a recursive fashion; that is, values of members are not limited to scalars, but rather can themselves be JSON documents:

mysql> SELECT JSON_MERGE_PATCH('{"a":{"x":1}}', '{"a":{"y":2}}');
+----------------------------------------------------+
| JSON_MERGE_PATCH('{"a":{"x":1}}', '{"a":{"y":2}}') |
+----------------------------------------------------+
| {"a": {"x": 1, "y": 2}}                            |
+----------------------------------------------------+

JSON_MERGE_PATCH() is supported in MySQL 8.0.3 and later.

JSON_MERGE_PATCH() compared with JSON_MERGE_PRESERVE(). The behavior of JSON_MERGE_PATCH() is the same as that of JSON_MERGE_PRESERVE(), with the following two exceptions:

JSON_MERGE_PATCH() removes any member in the first object with a matching key in the second object, provided that the value associated with the key in the second object is not JSON null.
If the second object has a member with a key matching a member in the first object, JSON_MERGE_PATCH() replaces the value in the first object with the value in the second object, whereas JSON_MERGE_PRESERVE() appends the second value to the first value.

This example compares the results of merging the same 3 JSON objects, each having a matching key "a", with each of these two functions:

mysql> SET @x = '{ "a": 1, "b": 2 }',
     >     @y = '{ "a": 3, "c": 4 }',
     >     @z = '{ "a": 5, "d": 6 }';

mysql> SELECT  JSON_MERGE_PATCH(@x, @y, @z)    AS Patch,
    ->         JSON_MERGE_PRESERVE(@x, @y, @z) AS Preserve\G
*************************** 1. row ***************************
   Patch: {"a": 5, "b": 2, "c": 4, "d": 6}
Preserve: {"a": [1, 3, 5], "b": 2, "c": 4, "d": 6}

JSON_MERGE_PRESERVE(json_doc, json_doc[, json_doc] ...)

Merges two or more JSON documents and returns the merged result. Returns NULL if any argument is NULL. An error occurs if any argument is not a valid JSON document.

Merging takes place according to the following rules. For additional information, see Normalization, Merging, and Autowrapping of JSON Values.

Adjacent arrays are merged to a single array.
Adjacent objects are merged to a single object.
A scalar value is autowrapped as an array and merged as an array.
An adjacent array and object are merged by autowrapping the object as an array and merging the two arrays.

mysql> SELECT JSON_MERGE_PRESERVE('[1, 2]', '[true, false]');
+------------------------------------------------+
| JSON_MERGE_PRESERVE('[1, 2]', '[true, false]') |
+------------------------------------------------+
| [1, 2, true, false]                            |
+------------------------------------------------+

mysql> SELECT JSON_MERGE_PRESERVE('{"name": "x"}', '{"id": 47}');
+----------------------------------------------------+
| JSON_MERGE_PRESERVE('{"name": "x"}', '{"id": 47}') |
+----------------------------------------------------+
| {"id": 47, "name": "x"}                            |
+----------------------------------------------------+

mysql> SELECT JSON_MERGE_PRESERVE('1', 'true');
+----------------------------------+
| JSON_MERGE_PRESERVE('1', 'true') |
+----------------------------------+
| [1, true]                        |
+----------------------------------+

mysql> SELECT JSON_MERGE_PRESERVE('[1, 2]', '{"id": 47}');
+---------------------------------------------+
| JSON_MERGE_PRESERVE('[1, 2]', '{"id": 47}') |
+---------------------------------------------+
| [1, 2, {"id": 47}]                          |
+---------------------------------------------+

mysql> SELECT JSON_MERGE_PRESERVE('{ "a": 1, "b": 2 }',
     >    '{ "a": 3, "c": 4 }');
+--------------------------------------------------------------+
| JSON_MERGE_PRESERVE('{ "a": 1, "b": 2 }','{ "a": 3, "c":4 }') |
+--------------------------------------------------------------+
| {"a": [1, 3], "b": 2, "c": 4}                                |
+--------------------------------------------------------------+

mysql> SELECT JSON_MERGE_PRESERVE('{ "a": 1, "b": 2 }','{ "a": 3, "c": 4 }',
     >    '{ "a": 5, "d": 6 }');
+----------------------------------------------------------------------------------+
| JSON_MERGE_PRESERVE('{ "a": 1, "b": 2 }','{ "a": 3, "c": 4 }','{ "a": 5, "d": 6 }') |
+----------------------------------------------------------------------------------+
| {"a": [1, 3, 5], "b": 2, "c": 4, "d": 6}                                         |
+----------------------------------------------------------------------------------+

This function was added in MySQL 8.0.3 as a synonym for JSON_MERGE(). The JSON_MERGE() function is now deprecated, and is subject to removal in a future release of MySQL.

This function is similar to but differs from JSON_MERGE_PATCH() in significant respects; see JSON_MERGE_PATCH() compared with JSON_MERGE_PRESERVE(), for more information.

JSON_REMOVE(json_doc, path[, path] ...)
Removes data from a JSON document and returns the result. Returns NULL if any argument is NULL. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression or is $ or contains a * or ** wildcard.
The path arguments are evaluated left to right. The document produced by evaluating one path becomes the new value against which the next path is evaluated.
It is not an error if the element to be removed does not exist in the document; in that case, the path does not affect the document.
```
mysql> SET @j = '["a", ["b", "c"], "d"]';
mysql> SELECT JSON_REMOVE(@j, '$[1]');
+-------------------------+
| JSON_REMOVE(@j, '$[1]') |
+-------------------------+
| ["a", "d"]              |
+-------------------------+
```
JSON_REPLACE(json_doc, path, val[, path, val] ...)
Replaces existing values in a JSON document and returns the result. Returns NULL if any argument is NULL. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression or contains a * or ** wildcard.
The path-value pairs are evaluated left to right. The document produced by evaluating one pair becomes the new value against which the next pair is evaluated.
A path-value pair for an existing path in the document overwrites the existing document value with the new value. A path-value pair for a nonexisting path in the document is ignored and has no effect.
In MySQL 8.0.4, the optimizer can perform a partial, in-place update of a JSON column instead of removing the old document and writing the new document in its entirety to the column. This optimization can be performed for an update statement that uses the JSON_REPLACE() function and meets the conditions outlined in Partial Updates of JSON Values.
For a comparison of JSON_INSERT(), JSON_REPLACE(), and JSON_SET(), see the discussion of JSON_SET().
```
mysql> SET @j = '{ "a": 1, "b": [2, 3]}';
mysql> SELECT JSON_REPLACE(@j, '$.a', 10, '$.c', '[true, false]');
+-----------------------------------------------------+
| JSON_REPLACE(@j, '$.a', 10, '$.c', '[true, false]') |
+-----------------------------------------------------+
| {"a": 10, "b": [2, 3]}                              |
+-----------------------------------------------------+
```
JSON_SET(json_doc, path, val[, path, val] ...)
Inserts or updates data in a JSON document and returns the result. Returns NULL if any argument is NULL or path, if given, does not locate an object. An error occurs if the json_doc argument is not a valid JSON document or any path argument is not a valid path expression or contains a * or ** wildcard.
The path-value pairs are evaluated left to right. The document produced by evaluating one pair becomes the new value against which the next pair is evaluated.
A path-value pair for an existing path in the document overwrites the existing document value with the new value. A path-value pair for a nonexisting path in the document adds the value to the document if the path identifies one of these types of values:
- A member not present in an existing object. The member is added to the object and associated with the new value.
- A position past the end of an existing array. The array is extended with the new value. If the existing value is not an array, it is autowrapped as an array, then extended with the new value.
Otherwise, a path-value pair for a nonexisting path in the document is ignored and has no effect.
In MySQL 8.0.4, the optimizer can perform a partial, in-place update of a JSON column instead of removing the old document and writing the new document in its entirety to the column. This optimization can be performed for an update statement that uses the JSON_SET() function and meets the conditions outlined in Partial Updates of JSON Values.
The JSON_SET(), JSON_INSERT(), and JSON_REPLACE() functions are related:
- JSON_SET() replaces existing values and adds nonexisting values.
- JSON_INSERT() inserts values without replacing existing values.
- JSON_REPLACE() replaces only existing values.
The following examples illustrate these differences, using one path that does exist in the document ($.a) and another that does not exist ($.c):
```
mysql> SET @j = '{ "a": 1, "b": [2, 3]}';
mysql> SELECT JSON_SET(@j, '$.a', 10, '$.c', '[true, false]');
+-------------------------------------------------+
| JSON_SET(@j, '$.a', 10, '$.c', '[true, false]') |
+-------------------------------------------------+
| {"a": 10, "b": [2, 3], "c": "[true, false]"}    |
+-------------------------------------------------+
mysql> SELECT JSON_INSERT(@j, '$.a', 10, '$.c', '[true, false]');
+----------------------------------------------------+
| JSON_INSERT(@j, '$.a', 10, '$.c', '[true, false]') |
+----------------------------------------------------+
| {"a": 1, "b": [2, 3], "c": "[true, false]"}        |
+----------------------------------------------------+
mysql> SELECT JSON_REPLACE(@j, '$.a', 10, '$.c', '[true, false]');
+-----------------------------------------------------+
| JSON_REPLACE(@j, '$.a', 10, '$.c', '[true, false]') |
+-----------------------------------------------------+
| {"a": 10, "b": [2, 3]}                              |
+-----------------------------------------------------+
```

JSON_UNQUOTE(json_val)

Unquotes JSON value and returns the result as a utf8mb4 string. Returns NULL if the argument is NULL. An error occurs if the value starts and ends with double quotes but is not a valid JSON string literal.

Within a string, certain sequences have special meaning unless the NO_BACKSLASH_ESCAPES SQL mode is enabled. Each of these sequences begins with a backslash (\), known as the escape character. MySQL recognizes the escape sequences shown in Table 12.21, “JSON_UNQUOTE() Special Character Escape Sequences”. For all other escape sequences, backslash is ignored. That is, the escaped character is interpreted as if it was not escaped. For example, \x is just x. These sequences are case-sensitive. For example, \b is interpreted as a backspace, but \B is interpreted as B.

Table 12.21 JSON_UNQUOTE() Special Character Escape Sequences

Escape Sequence	Character Represented by Sequence
`\"`	A double quote (`"`) character
`\b`	A backspace character
`\f`	A formfeed character
`\n`	A newline (linefeed) character
`\r`	A carriage return character
`\t`	A tab character
`\\`	A backslash (`\`) character
`\uXXXX`	UTF-8 bytes for Unicode value `XXXX`

Two simple examples of the use of this function are shown here:

mysql> SET @j = '"abc"';
mysql> SELECT @j, JSON_UNQUOTE(@j);
+-------+------------------+
| @j    | JSON_UNQUOTE(@j) |
+-------+------------------+
| "abc" | abc              |
+-------+------------------+
mysql> SET @j = '[1, 2, 3]';
mysql> SELECT @j, JSON_UNQUOTE(@j);
+-----------+------------------+
| @j        | JSON_UNQUOTE(@j) |
+-----------+------------------+
| [1, 2, 3] | [1, 2, 3]        |
+-----------+------------------+

The following set of examples shows how JSON_UNQUOTE handles escapes with NO_BACKSLASH_ESCAPES disabled and enabled:

mysql> SELECT @@sql_mode;
+------------+
| @@sql_mode |
+------------+
|            |
+------------+

mysql> SELECT JSON_UNQUOTE('"\\t\\u0032"');
+------------------------------+
| JSON_UNQUOTE('"\\t\\u0032"') |
+------------------------------+
|       2                           |
+------------------------------+

mysql> SET @@sql_mode = 'NO_BACKSLASH_ESCAPES';
mysql> SELECT JSON_UNQUOTE('"\\t\\u0032"');
+------------------------------+
| JSON_UNQUOTE('"\\t\\u0032"') |
+------------------------------+
| \t\u0032                     |
+------------------------------+

mysql> SELECT JSON_UNQUOTE('"\t\u0032"');
+----------------------------+
| JSON_UNQUOTE('"\t\u0032"') |
+----------------------------+
|       2                         |
+----------------------------+

12.16.5 Functions That Return JSON Value Attributes

The functions in this section return attributes of JSON values.

JSON_DEPTH(json_doc)

Returns the maximum depth of a JSON document. Returns NULL if the argument is NULL. An error occurs if the argument is not a valid JSON document.

An empty array, empty object, or scalar value has depth 1. A nonempty array containing only elements of depth 1 or nonempty object containing only member values of depth 1 has depth 2. Otherwise, a JSON document has depth greater than 2.

mysql> SELECT JSON_DEPTH('{}'), JSON_DEPTH('[]'), JSON_DEPTH('true');
+------------------+------------------+--------------------+
| JSON_DEPTH('{}') | JSON_DEPTH('[]') | JSON_DEPTH('true') |
+------------------+------------------+--------------------+
|                1 |                1 |                  1 |
+------------------+------------------+--------------------+
mysql> SELECT JSON_DEPTH('[10, 20]'), JSON_DEPTH('[[], {}]');
+------------------------+------------------------+
| JSON_DEPTH('[10, 20]') | JSON_DEPTH('[[], {}]') |
+------------------------+------------------------+
|                      2 |                      2 |
+------------------------+------------------------+
mysql> SELECT JSON_DEPTH('[10, {"a": 20}]');
+-------------------------------+
| JSON_DEPTH('[10, {"a": 20}]') |
+-------------------------------+
|                             3 |
+-------------------------------+

JSON_LENGTH(json_doc[, path])

Returns the length of a JSON document, or, if a path argument is given, the length of the value within the document identified by the path. Returns NULL if any argument is NULL or the path argument does not identify a value in the document. An error occurs if the json_doc argument is not a valid JSON document or the path argument is not a valid path expression or contains a * or ** wildcard.

The length of a document is determined as follows:

The length of a scalar is 1.
The length of an array is the number of array elements.
The length of an object is the number of object members.
The length does not count the length of nested arrays or objects.

mysql> SELECT JSON_LENGTH('[1, 2, {"a": 3}]');
+---------------------------------+
| JSON_LENGTH('[1, 2, {"a": 3}]') |
+---------------------------------+
|                               3 |
+---------------------------------+
mysql> SELECT JSON_LENGTH('{"a": 1, "b": {"c": 30}}');
+-----------------------------------------+
| JSON_LENGTH('{"a": 1, "b": {"c": 30}}') |
+-----------------------------------------+
|                                       2 |
+-----------------------------------------+
mysql> SELECT JSON_LENGTH('{"a": 1, "b": {"c": 30}}', '$.b');
+------------------------------------------------+
| JSON_LENGTH('{"a": 1, "b": {"c": 30}}', '$.b') |
+------------------------------------------------+
|                                              1 |
+------------------------------------------------+

JSON_TYPE(json_val)

Returns a utf8mb4 string indicating the type of a JSON value. This can be an object, an array, or a scalar type, as shown here:

mysql> SET @j = '{"a": [10, true]}';
mysql> SELECT JSON_TYPE(@j);
+---------------+
| JSON_TYPE(@j) |
+---------------+
| OBJECT        |
+---------------+
mysql> SELECT JSON_TYPE(JSON_EXTRACT(@j, '$.a'));
+------------------------------------+
| JSON_TYPE(JSON_EXTRACT(@j, '$.a')) |
+------------------------------------+
| ARRAY                              |
+------------------------------------+
mysql> SELECT JSON_TYPE(JSON_EXTRACT(@j, '$.a[0]'));
+---------------------------------------+
| JSON_TYPE(JSON_EXTRACT(@j, '$.a[0]')) |
+---------------------------------------+
| INTEGER                               |
+---------------------------------------+
mysql> SELECT JSON_TYPE(JSON_EXTRACT(@j, '$.a[1]'));
+---------------------------------------+
| JSON_TYPE(JSON_EXTRACT(@j, '$.a[1]')) |
+---------------------------------------+
| BOOLEAN                               |
+---------------------------------------+

JSON_TYPE() returns NULL if the argument is NULL:

mysql> SELECT JSON_TYPE(NULL);
+-----------------+
| JSON_TYPE(NULL) |
+-----------------+
| NULL            |
+-----------------+

An error occurs if the argument is not a valid JSON value:

mysql> SELECT JSON_TYPE(1);
ERROR 3146 (22032): Invalid data type for JSON data in argument 1
to function json_type; a JSON string or JSON type is required.

For a non-NULL, non-error result, the following list describes the possible JSON_TYPE() return values:

Purely JSON types:
- OBJECT: JSON objects
- ARRAY: JSON arrays
- BOOLEAN: The JSON true and false literals
- NULL: The JSON null literal
Numeric types:
- INTEGER: MySQL TINYINT, SMALLINT, MEDIUMINT and INT and BIGINT scalars
- DOUBLE: MySQL DOUBLE FLOAT scalars
- DECIMAL: MySQL DECIMAL and NUMERIC scalars
Temporal types:
- DATETIME: MySQL DATETIME and TIMESTAMP scalars
- DATE: MySQL DATE scalars
- TIME: MySQL TIME scalars
String types:
- STRING: MySQL utf8 character type scalars: CHAR, VARCHAR, TEXT, ENUM, and SET
Binary types:
- BLOB: MySQL binary type scalars including BINARY, VARBINARY, BLOB, and BIT
All other types:
- OPAQUE (raw bits)

JSON_VALID(val)

Returns 0 or 1 to indicate whether a value is valid JSON. Returns NULL if the argument is NULL.

mysql> SELECT JSON_VALID('{"a": 1}');
+------------------------+
| JSON_VALID('{"a": 1}') |
+------------------------+
|                      1 |
+------------------------+
mysql> SELECT JSON_VALID('hello'), JSON_VALID('"hello"');
+---------------------+-----------------------+
| JSON_VALID('hello') | JSON_VALID('"hello"') |
+---------------------+-----------------------+
|                   0 |                     1 |
+---------------------+-----------------------+

12.16.6 JSON Table Functions

This section contains information about JSON functions that convert JSON data to tabular data. In MySQL 8.0.4 and later, one such function—JSON_TABLE()—is supported.

JSON_TABLE(expr, path COLUMNS (column_list) [AS] alias)
Extracts data from a JSON document and returns it as a relational table having the specified columns. The complete syntax for this function is shown here:
```
JSON_TABLE(
    expr,
    path COLUMNS (column_list)
    [AS] alias
)

column_list:
    column[, column][, ...]

column:
    name FOR ORDINALITY
    |  name type PATH string path [on_error] [on_empty]
    |  name type EXISTS PATH string path
    |  NESTED [PATH] path COLUMNS (column_list)

on_error:
    {NULL | ERROR | DEFAULT json_string} ON ERROR

on_empty:
    {NULL | ERROR | DEFAULT json_string} ON EMPTY
```
expr: This is an expression that returns JSON data. This can be a constant ('{"a":1}'), a column (t1.json_data, given table t1 specified prior to JSON_TABLE() in the FROM clause), or a function call (JSON_EXTRACT(t1,jsn_data,'$.post.comments')).
path: A JSON path expression, which is applied to the data source. We refer to the JSON value matching the path as the row source; this is used to generate a row of relational data. The COLUMNS clause evaluates the row source, finds specific JSON values within the row source, and returns those JSON values as SQL values in individual columns of a row of relational data.
The alias is required. The usual rules for table aliases apply (see Section 9.2, “Schema Object Names”).
JSON_TABLE() supports four types of columns, described in the following list:
1. name FOR ORDINALITY: This type enumerates rows in the COLUMNS clause; the column named name is a counter whose type is UNSIGNED INT, and whose initial value is 1. This is equivalent to specifying a column as AUTO_INCREMENT in a CREATE TABLE statement, and can be used to distinguish parent rows with the same value for multiple rows generated by a NESTED [PATH] clause.
2. name type PATH string_path [on_error] [on_empty]: Columns of this type are used to extract scalar values specified by string_path. type is a MySQL data type. JSON_TABLE() extracts data as JSON then coerces it to the column type, using the regular automatic type conversion applying to JSON data in MySQL. The exact behavior depends on the column type: If the column type is an SQL type, then only a scalar value can be saved in the column. Saving an object or array triggers the on error clause; this also occurs when an error takes place during coercion from the value saved as JSON to the table column, such as trying to save the string 'asd' to an integer column. A missing value triggers the on_empty clause.
  The optional on_error clause determines what JSON_TABLE() does when saving an object or array:
  - NULL ON ERROR: The column is set to NULL; this is the default behavior. If an error occurs during type coercion, a warning is thrown.
  - ERROR ON ERROR: An error is thrown.
  - DEFAULT json string ON ERROR: The json_string is parsed as JSON (provided that it is valid) and stored instead of the object or array. A warning is thrown if the error is caused by type coercion. Column type rules also apply to the default value.
  When a value saved to a column is truncated, such as saving 3.14159 in a DECIMAL(10,1) column, a warning is issued independently of any ON ERROR option. When multiple values are truncated in a single statement, the warning is issued only once.
  The optional on empty clause determines what JSON_TABLE() does in the event that data is missing (depending on type). This clause is also triggered on a column in a NESTED PATH clause when the latter has no match and a NULL complemented row is produced for it. on empty takes one of the following values:
  - NULL ON EMPTY: The column is set to NULL; this is the default behavior.
  - ERROR ON EMPTY: An error is thrown.
  - DEFAULT json_string ON EMPTY: the provided json_string is parsed as JSON, as long as it is valid, and stored instead of the missing value. Column type rules also apply to the default value.
  This query demonstrates the use of the ON ERROR and ON EMPTY options. The row corresponding to {"b":1} is empty for the path "$.a", and attempting to save [1,2] as a scalar produces an error; these rows are highlighted in the output shown.
```
mysql> SELECT *
    -> FROM
    ->   JSON_TABLE(
    ->     '[{"a":"3"},{"a":2},{"b":1},{"a":0},{"a":[1,2]}]',
    ->     "$[*]"
    ->     COLUMNS(
    ->       rowid FOR ORDINALITY,
    ->       ac VARCHAR(100) PATH "$.a" DEFAULT '999' ON ERROR DEFAULT '111' ON EMPTY,
    ->       aj JSON PATH "$.a" DEFAULT '{"x": 333}' ON EMPTY,
    ->       bx INT EXISTS PATH "$.b"
    ->     )
    ->   ) AS tt;

+-------+------+------------+------+
| rowid | ac   | aj         | bx   |
+-------+------+------------+------+
|     1 | 3    | "3"        |    0 |
|     2 | 2    | 2          |    0 |
|     3 | 111  | {"x": 333} |    1 |
|     4 | 0    | 0          |    0 |
|     5 | 999  | [1, 2]     |    0 |
+-------+------+------------+------+
5 rows in set (0.00 sec)
```
3. name type EXISTS PATH path: This column returns 1 if any data is present at the location specified by path, and 0 otherwise. type can be any valid MySQL data type, but should normally be specified as some variety of INT.
4. NESTED [PATH] path COLUMNS (column_list): This flattens nested objects or arrays in JSON data into a single row along with the JSON values from the parent object or array. Using multiple PATH options allows projection of JSON values from multiple levels of nesting into a single row.
  The path is relative to the parent path row path of JSON_TABLE(), or the path of the parent NESTED [PATH] clause in the event of nested paths.
Column names are subject to the usual rules and limitations governing table column names. See Section 9.2, “Schema Object Names”.
All JSON and JSON path expressions are checked for validity; an invalid expression of either type causes an error.
Each match for the path preceding the COLUMNS keyword maps to an individual row in the result table. For example, the following query gives the result shown here:
```
mysql> SELECT *
    -> FROM
    ->   JSON_TABLE(
    ->     '[{"x":2,"y":"8"},{"x":"3","y":"7"},{"x":"4","y":6}]',
    ->     "$[*]" COLUMNS(
    ->       xval VARCHAR(100) PATH "$.x",
    ->       yval VARCHAR(100) PATH "$.y"
    ->     )
    ->   ) AS  jt1;

+------+------+
| xval | yval |
+------+------+
| 2    | 8    |
| 3    | 7    |
| 4    | 6    |
+------+------+
```
The expression "$[*]" matches each element of the array. You can filter the rows in the result by modifying the path; for example, using "$[1]" limits extraction to the second element of the JSON array used as the source, as shown here:
```
mysql> SELECT *
    -> FROM
    ->   JSON_TABLE(
    ->     '[{"x":2,"y":"8"},{"x":"3","y":"7"},{"x":"4","y":6}]',
    ->     "$[1]" COLUMNS(
    ->       xval VARCHAR(100) PATH "$.x",
    ->       yval VARCHAR(100) PATH "$.y"
    ->     )
    ->   ) AS  jt1;

+------+------+
| xval | yval |
+------+------+
| 3    | 7    |
+------+------+
```
Within a column definition, "$" passes the entire match to the column; "$.x" and "$.y" pass only the values corresponding to the keys x and y, respectively, within that match. For more information, see Section 12.16.8, “JSON Path Syntax”.
NESTED PATH (or simply NESTED; PATH is optional) produces a set of records for each match in the COLUMNS clause to which it belongs. If there is no match, all columns of the nested path are set to NULL. This implements an outer join between the topmost clause and NESTED [PATH]. An inner join can be emulated by applying a suitable condition in the WHERE clause, as shown here:
```
mysql> SELECT *
    -> FROM
    ->   JSON_TABLE(
    ->     '[ {"a": 1, "b": [11,111]}, {"a": 2, "b": [22,222]}, {"a":3}]',
    ->     '$[*]' COLUMNS(
    ->             a INT PATH '$.a',
    ->             NESTED PATH '$.b[*]' COLUMNS (b INT PATH '$')
    ->            )
    ->    ) AS jt
    -> WHERE b IS NOT NULL;

+------+------+
| a    | b    |
+------+------+
|    1 |   11 |
|    1 |  111 |
|    2 |   22 |
|    2 |  222 |
+------+------+
```
Sibling nested paths—that is, two or more instances of NESTED [PATH] in the same COLUMNS clause—are processed one after another, one at a time. While one nested path is producing records, columns of any sibling nested path expressions are set to NULL. This means that the total number of records for a single match within a single containing COLUMNS clause is the sum and not the product of all records produced by NESTED [PATH] modifiers, as shown here:
```
mysql> SELECT *
    -> FROM
    ->   JSON_TABLE(
    ->     '[{"a": 1, "b": [11,111]}, {"a": 2, "b": [22,222]}]',
    ->     '$[*]' COLUMNS(
    ->         a INT PATH '$.a',
    ->         NESTED PATH '$.b[*]' COLUMNS (b1 INT PATH '$'),
    ->         NESTED PATH '$.b[*]' COLUMNS (b2 INT PATH '$')
    ->     )
    -> ) AS jt;

+------+------+------+
| a    | b1   | b2   |
+------+------+------+
|    1 |   11 | NULL |
|    1 |  111 | NULL |
|    1 | NULL |   11 |
|    1 | NULL |  111 |
|    2 |   22 | NULL |
|    2 |  222 | NULL |
|    2 | NULL |   22 |
|    2 | NULL |  222 |
+------+------+------+
```
A FOR ORDINALITY column enumerates records produced by the COLUMNS clause, and can be used to distinguish parent records of a nested path, especially if values in parent records are the same, as can be seen here:
```
mysql> SELECT *
    -> FROM
    ->   JSON_TABLE(
    ->     '[{"a": "a_val",
    '>       "b": [{"c": "c_val", "l": [1,2]}]},
    '>     {"a": "a_val",
    '>       "b": [{"c": "c_val","l": [11]}, {"c": "c_val", "l": [22]}]}]',
    ->     '$[*]' COLUMNS(
    ->       top_ord FOR ORDINALITY,
    ->       apath VARCHAR(10) PATH '$.a',
    ->       NESTED PATH '$.b[*]' COLUMNS (
    ->         bpath VARCHAR(10) PATH '$.c',
    ->         ord FOR ORDINALITY,
    ->         NESTED PATH '$.l[*]' COLUMNS (lpath varchar(10) PATH '$')
    ->         )
    ->     )
    -> ) as jt;

+---------+---------+---------+------+-------+
| top_ord | apath   | bpath   | ord  | lpath |
+---------+---------+---------+------+-------+
|       1 |  a_val  |  c_val  |    1 | 1     |
|       1 |  a_val  |  c_val  |    1 | 2     |
|       2 |  a_val  |  c_val  |    1 | 11    |
|       2 |  a_val  |  c_val  |    2 | 22    |
+---------+---------+---------+------+-------+
```
The source document contains an array of two elements; each of these elements produces two rows. The values of apath and bpath are the same over the entire result set; this means that they cannot be used to determine whether lpath values came from the same or different parents. The value of the ord column remains the same as the set of records having top_ord equal to 1, so these two values are from a single object. The remaining two values are from different objects, since they have different values in the ord column.

12.16.7 JSON Utility Functions

This section documents utility functions that act on JSON values, or strings that can be parsed as JSON values. JSON_PRETTY() prints out a JSON value in a format that is easy to read. JSON_STORAGE_SIZE() and JSON_STORAGE_FREE() show, respectively, the amount of storage space used by a given JSON value and the amount of space remaining in a JSON column following a partial update.

JSON_PRETTY(json_val)
Provides pretty-printing of JSON values similar to that implemented in PHP and by other languages and database systems. The value supplied must be a JSON value or a valid string representation of a JSON value. Extraneous whitespaces and newlines present in this value have no effect on the output. For a NULL value, the function returns NULL. If the value is not a JSON document, or if it cannot cannot be parsed as one, the function fails with an error.
Formatting of the output from this function adheres to the following rules:
- Each array element or object member appears on a separate line, indented by one additional level as compared to its parent.
- Each level of indentation adds two leading spaces.
- A comma separating individual array elements or object members is printed before the newline that separates the two elements or members.
- The key and the value of an object member are separated by a colon followed by a space (': ').
- An empty object or array is printed on a single line. No space is printed between the opening and closing brace.
- Special characters in string scalars and key names are escaped employing the same rules used by the JSON_QUOTE() function.
```
mysql> SELECT JSON_PRETTY('123'); # scalar
+--------------------+
| JSON_PRETTY('123') |
+--------------------+
| 123                |
+--------------------+

mysql> SELECT JSON_PRETTY("[1,3,5]"); # array
+------------------------+
| JSON_PRETTY("[1,3,5]") |
+------------------------+
| [
  1,
  3,
  5
]      |
+------------------------+

mysql> SELECT JSON_PRETTY('{"a":"10","b":"15","x":"25"}'); # object
+---------------------------------------------+
| JSON_PRETTY('{"a":"10","b":"15","x":"25"}') |
+---------------------------------------------+
| {
  "a": "10",
  "b": "15",
  "x": "25"
}   |
+---------------------------------------------+

mysql> SELECT JSON_PRETTY('["a",1,{"key1":
     >    "value1"},"5",     "77" ,
     >       {"key2":["value3","valueX",
     > "valueY"]},"j", "2"   ]')\G  # nested arrays and objects
*************************** 1. row ***************************
JSON_PRETTY('["a",1,{"key1":
             "value1"},"5",     "77" ,
                {"key2":["value3","valuex",
          "valuey"]},"j", "2"   ]'): [
  "a",
  1,
  {
    "key1": "value1"
  },
  "5",
  "77",
  {
    "key2": [
      "value3",
      "valuex",
      "valuey"
    ]
  },
  "j",
  "2"
]
```

JSON_STORAGE_FREE(json_val)

For a JSON column value, this function shows how much storage space was freed in its binary representation after it was updated in place using JSON_SET(), JSON_REPLACE(), or JSON_REMOVE(). The argument can also be a valid JSON document or a string which can be parsed as one—either as a literal value or as the value of a user variable—in which case the function returns 0. It returns a positive, nonzero value if the argument is a JSON column value which has been updated as described previously, such that its binary representation takes up less space than it did prior to the update. For a JSON column which has been updated such that its binary representation is the same as or larger than before, or if the update was not able to take advantage of a partial update, it returns 0; it returns NULL if the argument is NULL.

If json_val is not NULL, and neither is a valid JSON document nor can be successfully parsed as one, an error results.

In this example, we create a table containing a JSON column, then insert a row containing a JSON object:

mysql> CREATE TABLE jtable (jcol JSON);
Query OK, 0 rows affected (0.38 sec)

mysql> INSERT INTO jtable VALUES
    ->     ('{"a": 10, "b": "wxyz", "c": "[true, false]"}');
Query OK, 1 row affected (0.04 sec)

mysql> SELECT * FROM jtable;
+----------------------------------------------+
| jcol                                         |
+----------------------------------------------+
| {"a": 10, "b": "wxyz", "c": "[true, false]"} |
+----------------------------------------------+
1 row in set (0.00 sec)

Now we update the column value using JSON_SET() such that a partial update can be performed; in this case, we replace the value pointed to by the c key (the array [true, false]) with one that takes up less space (the integer 1):

mysql> UPDATE jtable
    ->     SET jcol = JSON_SET(jcol, "$.a", 10, "$.b", "wxyz", "$.c", 1);
Query OK, 1 row affected (0.03 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT * FROM jtable;
+--------------------------------+
| jcol                           |
+--------------------------------+
| {"a": 10, "b": "wxyz", "c": 1} |
+--------------------------------+
1 row in set (0.00 sec)

mysql> SELECT JSON_STORAGE_FREE(jcol) FROM jtable;
+-------------------------+
| JSON_STORAGE_FREE(jcol) |
+-------------------------+
|                      14 |
+-------------------------+
1 row in set (0.00 sec)

The effects of successive partial updates on this free space are cumulative, as shown in this example using JSON_SET() to reduce the space taken up by the value having key b (and making no other changes):

mysql> UPDATE jtable
    ->     SET jcol = JSON_SET(jcol, "$.a", 10, "$.b", "wx", "$.c", 1);
Query OK, 1 row affected (0.03 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT JSON_STORAGE_FREE(jcol) FROM jtable;
+-------------------------+
| JSON_STORAGE_FREE(jcol) |
+-------------------------+
|                      16 |
+-------------------------+
1 row in set (0.00 sec)

Updating the column without using JSON_SET(), JSON_REPLACE(), or JSON_REMOVE() means that the optimizer cannot perform the update in place; in this case, JSON_STORAGE_FREE() returns 0, as shown here:

mysql> UPDATE jtable SET jcol = '{"a": 10, "b": 1}';
Query OK, 1 row affected (0.05 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT JSON_STORAGE_FREE(jcol) FROM jtable;
+-------------------------+
| JSON_STORAGE_FREE(jcol) |
+-------------------------+
|                       0 |
+-------------------------+
1 row in set (0.00 sec)

Partial updates of JSON documents can be performed only on column values. For a user variable that stores a JSON value, the value is always completely replaced, even when the update is performed using JSON_SET():

mysql> SET @j = '{"a": 10, "b": "wxyz", "c": "[true, false]"}';
Query OK, 0 rows affected (0.00 sec)

mysql> SET @j = JSON_SET(@j, '$.a', 10, '$.b', 'wxyz', '$.c', '1');
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT @j, JSON_STORAGE_FREE(@j) AS Free;
+----------------------------------+------+
| @j                               | Free |
+----------------------------------+------+
| {"a": 10, "b": "wxyz", "c": "1"} |    0 |
+----------------------------------+------+
1 row in set (0.00 sec)

For a JSON literal, this function always returns 0:

mysql> SELECT JSON_STORAGE_FREE('{"a": 10, "b": "wxyz", "c": "1"}') AS Free;
+------+
| Free |
+------+
|    0 |
+------+
1 row in set (0.00 sec)

JSON_STORAGE_SIZE(json_val)

This function returns the number of bytes used to store the binary representation of a JSON document. When the argument is a JSON column, this is the space used to store the JSON document as it was inserted into the column, prior to any partial updates that may have been performed on it afterwards. json_val must be a valid JSON document or a string which can be parsed as one. In the case where it is string, the function returns the amount of storage space in the JSON binary representation that is created by parsing the string as JSON and converting it to binary. It returns NULL if the argument is NULL.

An error results when json_val is not NULL, and is not—or cannot be successfully parsed as—a JSON document.

To illustrate this function's behavior when used with a JSON column as its argument, we create a table named jtable containing a JSON column jcol, insert a JSON value into the table, then obtain the storage space used by this column with JSON_STORAGE_SIZE(), as shown here:

mysql> CREATE TABLE jtable (jcol JSON);
Query OK, 0 rows affected (0.42 sec)

mysql> INSERT INTO jtable VALUES
    ->     ('{"a": 1000, "b": "wxyz", "c": "[1, 3, 5, 7]"}');
Query OK, 1 row affected (0.04 sec)

mysql> SELECT
    ->     jcol,
    ->     JSON_STORAGE_SIZE(jcol) AS Size,
    ->     JSON_STORAGE_FREE(jcol) AS Free
    -> FROM jtable;
+-----------------------------------------------+------+------+
| jcol                                          | Size | Free |
+-----------------------------------------------+------+------+
| {"a": 1000, "b": "wxyz", "c": "[1, 3, 5, 7]"} |   47 |    0 |
+-----------------------------------------------+------+------+
1 row in set (0.00 sec)

According to the output of JSON_STORAGE_SIZE(), the JSON document inserted into the column takes up 47 bytes. We also checked the amount of space freed by any previous partial updates of the column using JSON_STORAGE_FREE(); since no updates have yet been performed, this is 0, as expected.

Next we perform an UPDATE on the table that should result in a partial update of the document stored in jcol, and then test the result as shown here:

mysql> UPDATE jtable SET jcol = 
    ->     JSON_SET(jcol, "$.b", "a");
Query OK, 1 row affected (0.04 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT
    ->     jcol,
    ->     JSON_STORAGE_SIZE(jcol) AS Size,
    ->     JSON_STORAGE_FREE(jcol) AS Free
    -> FROM jtable;
+--------------------------------------------+------+------+
| jcol                                       | Size | Free |
+--------------------------------------------+------+------+
| {"a": 1000, "b": "a", "c": "[1, 3, 5, 7]"} |   47 |    3 |
+--------------------------------------------+------+------+
1 row in set (0.00 sec)

The value returned by JSON_STORAGE_FREE() in the previous query indicates that a partial update of the JSON document was performed, and that this freed 3 bytes of space used to store it. The result returned by JSON_STORAGE_SIZE() is unchanged by the partial update.

Partial updates are supported for updates using JSON_SET(), JSON_REPLACE(), or JSON_REMOVE(). The direct assignment of a value to a JSON column cannot be partially updated; following such an update, JSON_STORAGE_SIZE() always shows the storage used for the newly-set value:

mysql> UPDATE jtable
mysql>     SET jcol = '{"a": 4.55, "b": "wxyz", "c": "[true, false]"}';
Query OK, 1 row affected (0.04 sec)
Rows matched: 1  Changed: 1  Warnings: 0

mysql> SELECT
    ->     jcol,
    ->     JSON_STORAGE_SIZE(jcol) AS Size,
    ->     JSON_STORAGE_FREE(jcol) AS Free
    -> FROM jtable;
+------------------------------------------------+------+------+
| jcol                                           | Size | Free |
+------------------------------------------------+------+------+
| {"a": 4.55, "b": "wxyz", "c": "[true, false]"} |   56 |    0 |
+------------------------------------------------+------+------+
1 row in set (0.00 sec)

A JSON user variable cannot be partially updated. This means that this function always shows the space currently used to store a JSON document in a user variable:

mysql> SET @j = '[100, "sakila", [1, 3, 5], 425.05]';
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT @j, JSON_STORAGE_SIZE(@j) AS Size;
+------------------------------------+------+
| @j                                 | Size |
+------------------------------------+------+
| [100, "sakila", [1, 3, 5], 425.05] |   45 |
+------------------------------------+------+
1 row in set (0.00 sec)

mysql> SET @j = JSON_SET(@j, '$[1]', "json");
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT @j, JSON_STORAGE_SIZE(@j) AS Size;
+----------------------------------+------+
| @j                               | Size |
+----------------------------------+------+
| [100, "json", [1, 3, 5], 425.05] |   43 |
+----------------------------------+------+
1 row in set (0.00 sec)

mysql> SET @j = JSON_SET(@j, '$[2][0]', JSON_ARRAY(10, 20, 30));
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT @j, JSON_STORAGE_SIZE(@j) AS Size;
+---------------------------------------------+------+
| @j                                          | Size |
+---------------------------------------------+------+
| [100, "json", [[10, 20, 30], 3, 5], 425.05] |   56 |
+---------------------------------------------+------+
1 row in set (0.00 sec)

For a JSON literal, this function always returns the current storage space used:

mysql> SELECT
    ->     JSON_STORAGE_SIZE('[100, "sakila", [1, 3, 5], 425.05]') AS A,
    ->     JSON_STORAGE_SIZE('{"a": 1000, "b": "a", "c": "[1, 3, 5, 7]"}') AS B,
    ->     JSON_STORAGE_SIZE('{"a": 1000, "b": "wxyz", "c": "[1, 3, 5, 7]"}') AS C,
    ->     JSON_STORAGE_SIZE('[100, "json", [[10, 20, 30], 3, 5], 425.05]') AS D;
+----+----+----+----+
| A  | B  | C  | D  |
+----+----+----+----+
| 45 | 44 | 47 | 56 |
+----+----+----+----+
1 row in set (0.00 sec)

12.16.8 JSON Path Syntax

Many of the functions described in previous sections require a path expression in order to identify a specific element in a JSON document. A path consists of the path's scope followed by one or more path legs. For paths used in MySQL JSON functions, the scope is always the document being searched or otherwise operated on, represented by a leading $ character. Path legs are separated by period characters (.). Cells in arrays are represented by [N], where N is a non-negative integer. Names of keys must be double-quoted strings or valid ECMAScript identifiers (see http://www.ecma-international.org/ecma-262/5.1/#sec-7.6). Path expressions, like JSON text, should be encoded using the ascii, utf8, or utf8mb4 character set. Other character encodings are implicitly coerced to utf8mb4. The complete syntax is shown here:

pathExpression:
    scope[(pathLeg)*]

pathLeg:
    member | arrayLocation | doubleAsterisk

member:
    period ( keyName | asterisk )

arrayLocation:
    leftBracket ( nonNegativeInteger | asterisk ) rightBracket

keyName:
    ESIdentifier | doubleQuotedString

doubleAsterisk:
    '**'

period:
    '.'

asterisk:
    '*'

leftBracket:
    '['

rightBracket:
    ']'

As noted previously, in MySQL, the scope of the path is always the document being operated on, represented as $. You can use '$' as a synonynm for the document in JSON path expressions.

Note

Some implementations support column references for scopes of JSON paths; currently, MySQL does not support these.

The wildcard * and ** tokens are used as follows:

.* represents the values of all members in the object.
[*] represents the values of all cells in the array.
[prefix]**suffix represents all paths beginning with prefix and ending with suffix. prefix is optional, while suffix is required; in other words, a path may not end in **.
In addition, a path may not contain the sequence ***.

For path syntax examples, see the descriptions of the various JSON fuinctions that take paths as arguments, such as JSON_CONTAINS_PATH(), JSON_SET(), and JSON_REPLACE(). For examples which include the use of the * and ** wildcards, see the description of the JSON_SEARCH() function.

12.17 Functions Used with Global Transaction IDs

The functions described in this section are used with GTID-based replication. It is important to keep in mind that all of these functions take string representations of GTID sets as arguments—as such, the GTID sets must always be quoted when used with them. See GTID Sets for more information.

The union of two GTID sets is simply their representations as strings, joined together with an interposed comma. In other words, you can define a very simple function for obtaining the union of two GTID sets, similar to that created here:

CREATE FUNCTION GTID_UNION(g1 TEXT, g2 TEXT)
    RETURNS TEXT DETERMINISTIC
    RETURN CONCAT(g1,',',g2);

For more information about GTIDs and how these GTID functions are used in practice, see Section 17.1.3, “Replication with Global Transaction Identifiers”.

Table 12.22 GTID Functions

Name	Description
`GTID_SUBSET()`	Return true if all GTIDs in subset are also in set; otherwise false.
`GTID_SUBTRACT()`	Return all GTIDs in set that are not in subset.
`WAIT_FOR_EXECUTED_GTID_SET()`	Wait until the given GTIDs have executed on slave.
`WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS()`	Wait until the given GTIDs have executed on slave.

GTID_SUBSET(subset,set)

Given two sets of global transaction IDs subset and set, returns true if all GTIDs in subset are also in set. Returns false otherwise.

The GTID sets used with this function are represented as strings, as shown in the following examples:

mysql> SELECT GTID_SUBSET('3E11FA47-71CA-11E1-9E33-C80AA9429562:23',
    ->     '3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57')\G
*************************** 1. row ***************************
GTID_SUBSET('3E11FA47-71CA-11E1-9E33-C80AA9429562:23',
    '3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57'): 1
1 row in set (0.00 sec)

mysql> SELECT GTID_SUBSET('3E11FA47-71CA-11E1-9E33-C80AA9429562:23-25',
    ->     '3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57')\G
*************************** 1. row ***************************
GTID_SUBSET('3E11FA47-71CA-11E1-9E33-C80AA9429562:23-25',
    '3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57'): 1
1 row in set (0.00 sec)

mysql> SELECT GTID_SUBSET('3E11FA47-71CA-11E1-9E33-C80AA9429562:20-25',
    ->     '3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57')\G
*************************** 1. row ***************************
GTID_SUBSET('3E11FA47-71CA-11E1-9E33-C80AA9429562:20-25',
    '3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57'): 0
1 row in set (0.00 sec)

GTID_SUBTRACT(set,subset)

Given two sets of global transaction IDs subset and set, returns only those GTIDs from set that are not in subset.

All GTID sets used with this function are represented as strings and must be quoted, as shown in these examples:

mysql> SELECT GTID_SUBTRACT('3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57',
    ->     '3E11FA47-71CA-11E1-9E33-C80AA9429562:21')\G
*************************** 1. row ***************************
GTID_SUBTRACT('3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57',
    '3E11FA47-71CA-11E1-9E33-C80AA9429562:21'): 3e11fa47-71ca-11e1-9e33-c80aa9429562:22-57
1 row in set (0.00 sec)

mysql> SELECT GTID_SUBTRACT('3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57',
    ->     '3E11FA47-71CA-11E1-9E33-C80AA9429562:20-25')\G
*************************** 1. row ***************************
GTID_SUBTRACT('3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57',
    '3E11FA47-71CA-11E1-9E33-C80AA9429562:20-25'): 3e11fa47-71ca-11e1-9e33-c80aa9429562:26-57
1 row in set (0.00 sec)

mysql> SELECT GTID_SUBTRACT('3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57',
    ->     '3E11FA47-71CA-11E1-9E33-C80AA9429562:23-24')\G
*************************** 1. row ***************************
GTID_SUBTRACT('3E11FA47-71CA-11E1-9E33-C80AA9429562:21-57',
    '3E11FA47-71CA-11E1-9E33-C80AA9429562:23-24'): 3e11fa47-71ca-11e1-9e33-c80aa9429562:21-22:25-57
1 row in set (0.01 sec)

WAIT_FOR_EXECUTED_GTID_SET(gtid_set[, timeout])
Wait until the server has applied all of the transactions whose global transaction identifiers are contained in gtid_set; that is, until the condition GTID_SUBSET(gtid_subset, @@global.gtid_executed) holds. See Section 17.1.3.1, “GTID Format and Storage” for a definition of GTID sets.
If a timeout is specified, and timeout seconds elapse before all of the transactions in the GTID set have been applied, the function stops waiting. timeout is optional, and the default timeout is 0 seconds, in which case the function always waits until all of the transactions in the GTID set have been applied.
WAIT_FOR_EXECUTED_GTID_SET() monitors all the GTIDs that are applied on the server, including transactions that arrive from all replication channels and user clients. It does not take into account whether replication channels have been started or stopped.
For more information, see Section 17.1.3, “Replication with Global Transaction Identifiers”.
GTID sets used with this function are represented as strings and so must be quoted as shown in the following example:
```
mysql> SELECT WAIT_FOR_EXECUTED_GTID_SET('3E11FA47-71CA-11E1-9E33-C80AA9429562:1-5');
        -> 0
```
For a syntax description for GTID sets, see Section 17.1.3.1, “GTID Format and Storage”.
For WAIT_FOR_EXECUTED_GTID_SET(), the return value is the state of the query, where 0 represents success, and 1 represents timeout. Any other failures generate an error.
gtid_mode cannot be changed to OFF while any client is using this function to wait for GTIDs to be applied.
WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS(gtid_set[, timeout][,channel])
WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS() is similar to WAIT_FOR_EXECUTED_GTID_SET() in that it waits until all of the transactions whose global transaction identifiers are contained in gtid_set have been applied, or until timeout seconds have elapsed, whichever occurs first. However, WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS() applies to a specific replication channel, and stops only after the transactions have been applied on the specified channel, for which the applier must be running. In contrast, WAIT_FOR_EXECUTED_GTID_SET() stops after the transactions have been applied, regardless of where they were applied (on any replication channel or any user client), and whether or not any replication channels are running.
The channel option names which replication channel the function applies to. If no channel is named and no channels other than the default replication channel exist, the function applies to the default replication channel. If multiple replication channels exist, you must specify a channel as otherwise it is not known which replication channel the function applies to. See Section 17.2.3, “Replication Channels” for more information on replication channels.

Note

Because WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS() applies to a specific replication channel, if an expected transaction arrives on a different replication channel or from a user client, for example in a failover or manual recovery situation, the function can hang indefinitely if no timeout is set. Use WAIT_FOR_EXECUTED_GTID_SET() instead to ensure correct handling of transactions in these situations.

GTID sets used with WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS() are represented as strings and must be quoted in the same way as for WAIT_FOR_EXECUTED_GTID_SET(). For WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS(), the return value for the function is an arbitrary positive number. If GTID-based replication is not active (that is, if the value of the gtid_mode variable is OFF), then this value is undefined and WAIT_UNTIL_SQL_THREAD_AFTER_GTIDS() returns NULL. If the slave is not running then the function also returns NULL.
gtid_mode cannot be changed to OFF while any client is using this function to wait for GTIDs to be applied.

12.18 MySQL Enterprise Encryption Functions

12.18.1 Enterprise Encryption Installation
12.18.2 Enterprise Encryption Usage and Examples
12.18.3 Enterprise Encryption Function Reference
12.18.4 Enterprise Encryption Function Descriptions

Note

MySQL Enterprise Encryption is an extension included in MySQL Enterprise Edition, a commercial product. To learn more about commercial products, http://www.mysql.com/products/.

MySQL Enterprise Edition includes a set of encryption functions based on the OpenSSL library that expose OpenSSL capabilities at the SQL level. These functions enable Enterprise applications to perform the following operations:

Implement added data protection using public-key asymmetric cryptography
Create public and private keys and digital signatures
Perform asymmetric encryption and decryption
Use cryptographic hashing for digital signing and data verification and validation

Enterprise Encryption supports the RSA, DSA, and DH cryptographic algorithms.

Enterprise Encryption is supplied as a user-defined function (UDF) library, from which individual functions can be installed individually.

12.18.1 Enterprise Encryption Installation

Enterprise Encryption functions are located in a user-defined function (UDF) library file installed in the plugin directory (the directory named by the plugin_dir system variable). The UDF library base name is openssl_udf and the suffix is platform dependent. For example, the file name on Linux or Windows is openssl_udf.so or openssl_udf.dll, respectively.

To install functions from the library file, use the CREATE FUNCTION statement. To load all functions from the library, use this set of statements (adjust the file name suffix as necessary):

CREATE FUNCTION asymmetric_decrypt RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION asymmetric_derive RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION asymmetric_encrypt RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION asymmetric_sign RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION asymmetric_verify RETURNS INTEGER
  SONAME 'openssl_udf.so';
CREATE FUNCTION create_asymmetric_priv_key RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION create_asymmetric_pub_key RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION create_dh_parameters RETURNS STRING
  SONAME 'openssl_udf.so';
CREATE FUNCTION create_digest RETURNS STRING
  SONAME 'openssl_udf.so';

Once installed, UDFs remain installed across server restarts. To unload UDFs, use the DROP FUNCTION statement. For example, to unload the key-generation functions, do this:

DROP FUNCTION create_asymmetric_priv_key;
DROP FUNCTION create_asymmetric_pub_key;

In the CREATE FUNCTION and DROP FUNCTION statements, the function names must be specified in lowercase. This differs from their use at function invocation time, for which you can use any lettercase.

The CREATE FUNCTION and DROP FUNCTION statements require the INSERT and DROP privilege, respectively, for the mysql database.

12.18.2 Enterprise Encryption Usage and Examples

To use Enterprise Encryption in applications, invoke the functions that are appropriate for the operations you wish to perform. This section demonstrates how to carry out some representative tasks:

Create a private/public key pair using RSA encryption

-- Encryption algorithm; can be 'DSA' or 'DH' instead
SET @algo = 'RSA';
-- Key length in bits; make larger for stronger keys
SET @key_len = 1024;

-- Create private key
SET @priv = CREATE_ASYMMETRIC_PRIV_KEY(@algo, @key_len);
-- Derive corresponding public key from private key, using same algorithm
SET @pub = CREATE_ASYMMETRIC_PUB_KEY(@algo, @priv);

Now you can use the key pair to encrypt and decrypt data, sign and verify data, or generate symmetric keys.

Use the private key to encrypt data and the public key to decrypt it

This requires that the members of the key pair be RSA keys.

SET @ciphertext = ASYMMETRIC_ENCRYPT(@algo, 'My secret text', @priv);
SET @cleartext = ASYMMETRIC_DECRYPT(@algo, @ciphertext, @pub);

Conversely, you can encrypt using the public key and decrypt using the private key.

SET @ciphertext = ASYMMETRIC_ENCRYPT(@algo, 'My secret text', @pub);
SET @cleartext = ASYMMETRIC_DECRYPT(@algo, @ciphertext, @priv);

In either case, the algorithm specified for the encryption and decryption functions must match that used to generate the keys.

Generate a digest from a string

-- Digest type; can be 'SHA256', 'SHA384', or 'SHA512' instead
SET @dig_type = 'SHA224';

-- Generate digest string
SET @dig = CREATE_DIGEST(@dig_type, 'My text to digest');

Use the digest with a key pair

The key pair can be used to sign data, then verify that the signature matches the digest.

-- Encryption algorithm; could be 'DSA' instead; keys must
-- have been created using same algorithm
SET @algo = 'RSA';

-- Generate signature for digest and verify signature against digest
SET @sig = ASYMMETRIC_SIGN(@algo, @dig, @priv, @dig_type);
-- Verify signature against digest
SET @verf = ASYMMETRIC_VERIFY(@algo, @dig, @sig, @pub, @dig_type);

Create a symmetric key

This requires DH private/public keys as inputs, created using a shared symmetric secret. Create the secret by passing the key length to CREATE_DH_PARAMETERS(), then pass the secret as the “key length” to CREATE_ASYMMETRIC_PRIV_KEY().

-- Generate DH shared symmetric secret
SET @dhp = CREATE_DH_PARAMETERS(1024);
-- Generate DH key pairs
SET @algo = 'DH';
SET @priv1 = CREATE_ASYMMETRIC_PRIV_KEY(@algo, @dhp);
SET @pub1 = CREATE_ASYMMETRIC_PUB_KEY(@algo, @priv1);
SET @priv2 = CREATE_ASYMMETRIC_PRIV_KEY(@algo, @dhp);
SET @pub2 = CREATE_ASYMMETRIC_PUB_KEY(@algo, @priv2);

-- Generate symmetric key using public key of first party,
-- private key of second party
SET @sym1 = ASYMMETRIC_DERIVE(@pub1, @priv2);

-- Or use public key of second party, private key of first party
SET @sym2 = ASYMMETRIC_DERIVE(@pub2, @priv1);

Key string values can be created at runtime and stored into a variable or table using SET, SELECT, or INSERT:

SET @priv1 = CREATE_ASYMMETRIC_PRIV_KEY('RSA', 1024);
SELECT CREATE_ASYMMETRIC_PRIV_KEY('RSA', 1024) INTO @priv2;
INSERT INTO t (key_col) VALUES(CREATE_ASYMMETRIC_PRIV_KEY('RSA', 1024));

Key string values stored in files can be read using the LOAD_FILE() function by users who have the FILE privilege.

Digest and signature strings can be handled similarly.

Limit CPU usage by key-generation operations

The CREATE_ASYMMETRIC_PRIV_KEY() and CREATE_DH_PARAMETERS() encryption functions take a key-length parameter, and the amount of CPU resources required by these functions increases as the key length increases. For some installations, this might result in unacceptable CPU usage if applications frequently generate excessively long keys.

OpenSSL imposes a minimum key length of 1,024 bits for all keys. OpenSSL also imposes a maximum key length of 10,000 bits and 16,384 bits for DSA and RSA keys, respectively, for CREATE_ASYMMETRIC_PRIV_KEY(), and a maximum key length of 10,000 bits for CREATE_DH_PARAMETERS(). If those maximum values are too high, three environment variables are available to enable MySQL server administrators to set lower maximum lengths for key generation, and thereby to limit CPU usage:

MYSQL_OPENSSL_UDF_DSA_BITS_THRESHOLD: Maximum DSA key length in bits for CREATE_ASYMMETRIC_PRIV_KEY(). The minimum and maximum values for this variable are 1,024 and 10,000.
MYSQL_OPENSSL_UDF_RSA_BITS_THRESHOLD: Maximum RSA key length in bits for CREATE_ASYMMETRIC_PRIV_KEY(). The minimum and maximum values for this variable are 1,024 and 16,384.
MYSQL_OPENSSL_UDF_DH_BITS_THRESHOLD: Maximum key length in bits for CREATE_DH_PARAMETERS(). The minimum and maximum values for this variable are 1,024 and 10,000.

To use any of these environment variables, set them in the environment of the process that starts the server. If set, their values take precedence over the maximum key lengths imposed by OpenSSL. For example, to set a maximum key length of 4,096 bits for DSA and RSA keys for CREATE_ASYMMETRIC_PRIV_KEY(), set these variables:

export MYSQL_OPENSSL_UDF_DSA_BITS_THRESHOLD=4096
export MYSQL_OPENSSL_UDF_RSA_BITS_THRESHOLD=4096

The example uses Bourne shell syntax. The syntax for other shells may differ.

12.18.3 Enterprise Encryption Function Reference

Table 12.23 MySQL Enterprise Encryption Functions

Name	Description
`ASYMMETRIC_DECRYPT()`	Decrypt ciphertext using private or public key
`ASYMMETRIC_DERIVE()`	Derive symmetric key from asymmetric keys
`ASYMMETRIC_ENCRYPT()`	Encrypt cleartext using private or public key
`ASYMMETRIC_SIGN()`	Generate signature from digest
`ASYMMETRIC_VERIFY()`	Verify that signature matches digest
`CREATE_ASYMMETRIC_PRIV_KEY()`	Create private key
`CREATE_ASYMMETRIC_PUB_KEY()`	Create public key
`CREATE_DH_PARAMETERS()`	Generate shared DH secret
`CREATE_DIGEST()`	Generate digest from string

12.18.4 Enterprise Encryption Function Descriptions

Enterprise Encryption functions have these general characteristics:

For arguments of the wrong type or an incorrect number of arguments, each function returns an error.
If the arguments are not suitable to permit a function to perform the requested operation, it returns NULL or 0 as appropriate. This occurs, for example, if a function does not support a specified algorithm, a key length is too short or long, or a string expected to be a key string in PEM format is not a valid key. (OpenSSL imposes its own key-length limits, and server administrators can impose additional limits on maximum key length by setting environment variables. See Section 12.18.2, “Enterprise Encryption Usage and Examples”.)
The underlying SSL library takes care of randomness initialization.

Several of the functions take an encryption algorithm argument. The following table summarizes the supported algorithms by function.

Table 12.24 Supported Algorithms by Function

Function	Supported Algorithms
`ASYMMETRIC_DECRYPT()`	RSA
`ASYMMETRIC_DERIVE()`	DH
`ASYMMETRIC_ENCRYPT()`	RSA
`ASYMMETRIC_SIGN()`	RSA, DSA
`ASYMMETRIC_VERIFY()`	RSA, DSA
`CREATE_ASYMMETRIC_PRIV_KEY()`	RSA, DSA, DH
`CREATE_ASYMMETRIC_PUB_KEY()`	RSA, DSA, DH
`CREATE_DH_PARAMETERS()`	DH

Note

Although you can create keys using any of the RSA, DSA, or DH encryption algorithms, other functions that take key arguments might accept only certain types of keys. For example, ASYMMETRIC_ENCRYPT() and ASYMMETRIC_DECRYPT() accept only RSA keys.

The following descriptions describe the calling sequences for Enterprise Encryption functions. For additional examples and discussion, see Section 12.18.2, “Enterprise Encryption Usage and Examples”.

ASYMMETRIC_DECRYPT(algorithm, crypt_str, key_str)
Decrypts an encrypted string using the given algorithm and key string, and returns the resulting cleartext as a binary string. If decryption fails, the result is NULL.
key_str must be a valid key string in PEM format. For successful decryption, it must be the public or private key string corresponding to the private or public key string used with ASYMMETRIC_ENCRYPT() to produce the encrypted string. algorithm indicates the encryption algorithm used to create the key.
Supported algorithm values: 'RSA'
For a usage example, see the description of ASYMMETRIC_ENCRYPT().
ASYMMETRIC_DERIVE(pub_key_str, priv_key_str)
Derives a symmetric key using the private key of one party and the public key of another, and returns the resulting key as a binary string. If key derivation fails, the result is NULL.
pub_key_str and priv_key_str must be valid key strings in PEM format. They must be created using the DH algorithm.
Suppose that you have two pairs of public and private keys:
```
SET @dhp = CREATE_DH_PARAMETERS(1024);
SET @priv1 = CREATE_ASYMMETRIC_PRIV_KEY('DH', @dhp);
SET @pub1 = CREATE_ASYMMETRIC_PUB_KEY('DH', @priv1);
SET @priv2 = CREATE_ASYMMETRIC_PRIV_KEY('DH', @dhp);
SET @pub2 = CREATE_ASYMMETRIC_PUB_KEY('DH', @priv2);
```
Suppose further that you use the private key from one pair and the public key from the other pair to create a symmetric key string. Then this symmetric key identity relationship holds:
```
ASYMMETRIC_DERIVE(@pub1, @priv2) = ASYMMETRIC_DERIVE(@pub2, @priv1)
```
ASYMMETRIC_ENCRYPT(algorithm, str, key_str)
Encrypts a string using the given algorithm and key string, and returns the resulting ciphertext as a binary string. If encryption fails, the result is NULL.
The str length cannot be greater than the key_str length − 11, in bytes
key_str must be a valid key string in PEM format. algorithm indicates the encryption algorithm used to create the key.
Supported algorithm values: 'RSA'
To encrypt a string, pass a private or public key string to ASYMMETRIC_ENCRYPT(). To recover the original unencrypted string, pass the encrypted string to ASYMMETRIC_DECRYPT(), along with the public or private key string correponding to the private or public key string used for encryption.
```
-- Generate private/public key pair
SET @priv = CREATE_ASYMMETRIC_PRIV_KEY('RSA', 1024);
SET @pub = CREATE_ASYMMETRIC_PUB_KEY('RSA', @priv);

-- Encrypt using private key, decrypt using public key
SET @ciphertext = ASYMMETRIC_ENCRYPT('RSA', 'The quick brown fox', @priv);
SET @cleartext = ASYMMETRIC_DECRYPT('RSA', @ciphertext, @pub);

-- Encrypt using public key, decrypt using private key
SET @ciphertext = ASYMMETRIC_ENCRYPT('RSA', 'The quick brown fox', @pub);
SET @cleartext = ASYMMETRIC_DECRYPT('RSA', @ciphertext, @priv);
```
Suppose that:
```
SET @s = a string to be encrypted
SET @priv = a valid private RSA key string in PEM format
SET @pub = the corresponding public RSA key string in PEM format
```
Then these identity relationships hold:
```
ASYMMETRIC_DECRYPT('RSA', ASYMMETRIC_ENCRYPT('RSA', @s, @priv), @pub) = @s
ASYMMETRIC_DECRYPT('RSA', ASYMMETRIC_ENCRYPT('RSA', @s, @pub), @priv) = @s
```
ASYMMETRIC_SIGN(algorithm, digest_str, priv_key_str, digest_type)
Signs a digest string using a private key string, and returns the signature as a binary string. If signing fails, the result is NULL.
digest_str is the digest string. It can be generated by calling CREATE_DIGEST(). digest_type indicates the digest algorithm used to generate the digest string.
priv_key_str is the private key string to use for signing the digest string. It must be a valid key string in PEM format. algorithm indicates the encryption algorithm used to create the key.
Supported algorithm values: 'RSA', 'DSA'
Supported digest_type values: 'SHA224', 'SHA256', 'SHA384', 'SHA512'
For a usage example, see the description of ASYMMETRIC_VERIFY().
ASYMMETRIC_VERIFY(algorithm, digest_str, sig_str, pub_key_str, digest_type)
Verifies whether the signature string matches the digest string, and returns 1 or 0 to indicate whether verification succeeded or failed.
digest_str is the digest string. It can be generated by calling CREATE_DIGEST(). digest_type indicates the digest algorithm used to generate the digest string.
sig_str is the signature string. It can be generated by calling ASYMMETRIC_SIGN().
pub_key_str is the public key string of the signer. It corresponds to the private key passed to ASYMMETRIC_SIGN() to generate the signature string and must be a valid key string in PEM format. algorithm indicates the encryption algorithm used to create the key.
Supported algorithm values: 'RSA', 'DSA'
Supported digest_type values: 'SHA224', 'SHA256', 'SHA384', 'SHA512'
```
-- Set the encryption algorithm and digest type
SET @algo = 'RSA';
SET @dig_type = 'SHA224';

-- Create private/public key pair
SET @priv = CREATE_ASYMMETRIC_PRIV_KEY(@algo, 1024);
SET @pub = CREATE_ASYMMETRIC_PUB_KEY(@algo, @priv);

-- Generate digest from string
SET @dig = CREATE_DIGEST(@dig_type, 'The quick brown fox');

-- Generate signature for digest and verify signature against digest
SET @sig = ASYMMETRIC_SIGN(@algo, @dig, @priv, @dig_type);
SET @verf = ASYMMETRIC_VERIFY(@algo, @dig, @sig, @pub, @dig_type);
```
CREATE_ASYMMETRIC_PRIV_KEY(algorithm, {key_len|dh_secret})
Creates a private key using the given algorithm and key length or DH secret, and returns the key as a binary string in PEM format. If key generation fails, the result is NULL.
Supported algorithm values: 'RSA', 'DSA', 'DH'
Supported key_len values: The minimum key length in bits is 1,024. The maximum key length depends on the algorithm: 16,384 for RSA and 10,000 for DSA. These key-length limits are constraints imposed by OpenSSL. Server administrators can impose additional limits on maximum key length by setting environment variables. See Section 12.18.2, “Enterprise Encryption Usage and Examples”.
For DH keys, pass a shared DH secret instead of a key length. To create the secret, pass the key length to CREATE_DH_PARAMETERS().
This example creates a 2,048-bit DSA private key, then derives a public key from the private key:
```
SET @priv = CREATE_ASYMMETRIC_PRIV_KEY('DSA', 2048);
SET @pub = CREATE_ASYMMETRIC_PUB_KEY('DSA', @priv);
```
For an example showing DH key generation, see the description of ASYMMETRIC_DERIVE().
Some general considerations in choosing key lengths and encryption algorithms:
- The strength of encryption for private and public keys increases with the key size, but the time for key generation increases as well.
- Generation of DH keys takes much longer than RSA or RSA keys.
- Asymmetric encryption functions are slower than symmetric functions. If performance is an important factor and the functions are to be used very frequently, you are better off using symmetric encryption. For example, consider using AES_ENCRYPT() and AES_DECRYPT().
CREATE_ASYMMETRIC_PUB_KEY(algorithm, priv_key_str)
Derives a public key from the given private key using the given algorithm, and returns the key as a binary string in PEM format. If key derivation fails, the result is NULL.
priv_key_str must be a valid key string in PEM format. algorithm indicates the encryption algorithm used to create the key.
Supported algorithm values: 'RSA', 'DSA', 'DH'
For a usage example, see the description of CREATE_ASYMMETRIC_PRIV_KEY().
CREATE_DH_PARAMETERS(key_len)
Creates a shared secret for generating a DH private/public key pair and returns a binary string that can be passed to CREATE_ASYMMETRIC_PRIV_KEY(). If secret generation fails, the result is null.
Supported key_len values: The minimum and maximum key lengths in bits are 1,024 and 10,000. These key-length limits are constraints imposed by OpenSSL. Server administrators can impose additional limits on maximum key length by setting environment variables. See Section 12.18.2, “Enterprise Encryption Usage and Examples”.
For an example showing how to use the return value for generating symmetric keys, see the description of ASYMMETRIC_DERIVE().
```
SET @dhp = CREATE_DH_PARAMETERS(1024);
```
CREATE_DIGEST(digest_type, str)
Creates a digest from the given string using the given digest type, and returns the digest as a binary string. If digest generation fails, the result is NULL.
Supported digest_type values: 'SHA224', 'SHA256', 'SHA384', 'SHA512'
```
SET @dig = CREATE_DIGEST('SHA512', The quick brown fox');
```
The resulting digest string is suitable for use with ASYMMETRIC_SIGN() and ASYMMETRIC_VERIFY().

12.19 Aggregate (GROUP BY) Functions

12.19.1 Aggregate (GROUP BY) Function Descriptions
12.19.2 GROUP BY Modifiers
12.19.3 MySQL Handling of GROUP BY
12.19.4 Detection of Functional Dependence

12.19.1 Aggregate (GROUP BY) Function Descriptions

This section describes group (aggregate) functions that operate on sets of values.

Table 12.25 Aggregate (GROUP BY) Functions

Name	Description
`AVG()`	Return the average value of the argument
`BIT_AND()`	Return bitwise AND
`BIT_OR()`	Return bitwise OR
`BIT_XOR()`	Return bitwise XOR
`COUNT()`	Return a count of the number of rows returned
`COUNT(DISTINCT)`	Return the count of a number of different values
`GROUP_CONCAT()`	Return a concatenated string
`JSON_ARRAYAGG()`	Return result set as a single JSON array
`JSON_OBJECTAGG()`	Return result set as a single JSON object
`MAX()`	Return the maximum value
`MIN()`	Return the minimum value
`STD()`	Return the population standard deviation
`STDDEV()`	Return the population standard deviation
`STDDEV_POP()`	Return the population standard deviation
`STDDEV_SAMP()`	Return the sample standard deviation
`SUM()`	Return the sum
`VAR_POP()`	Return the population standard variance
`VAR_SAMP()`	Return the sample variance
`VARIANCE()`	Return the population standard variance

Unless otherwise stated, group functions ignore NULL values.

If you use a group function in a statement containing no GROUP BY clause, it is equivalent to grouping on all rows. For more information, see Section 12.19.3, “MySQL Handling of GROUP BY”.

Most aggregate functions can be used as window functions. Those that can be used this way are signified in their syntax description by [over_clause], representing an optional OVER clause. over_clause is described in Section 12.20.2, “Window Function Concepts and Syntax”, which also includes other information about window function usage.

For numeric arguments, the variance and standard deviation functions return a DOUBLE value. The SUM() and AVG() functions return a DECIMAL value for exact-value arguments (integer or DECIMAL), and a DOUBLE value for approximate-value arguments (FLOAT or DOUBLE).

The SUM() and AVG() aggregate functions do not work with temporal values. (They convert the values to numbers, losing everything after the first nonnumeric character.) To work around this problem, convert to numeric units, perform the aggregate operation, and convert back to a temporal value. Examples:

SELECT SEC_TO_TIME(SUM(TIME_TO_SEC(time_col))) FROM tbl_name;
SELECT FROM_DAYS(SUM(TO_DAYS(date_col))) FROM tbl_name;

Functions such as SUM() or AVG() that expect a numeric argument cast the argument to a number if necessary. For SET or ENUM values, the cast operation causes the underlying numeric value to be used.

The BIT_AND(), BIT_OR(), and BIT_XOR() aggregate functions perform bit operations. Prior to MySQL 8.0, bit functions and operators required BIGINT (64-bit integer) arguments and returned BIGINT values, so they had a maximum range of 64 bits. Non-BIGINT arguments were converted to BIGINT prior to performing the operation and truncation could occur.

In MySQL 8.0, bit functions and operators permit binary string type arguments (BINARY, VARBINARY, and the BLOB types) and return a value of like type, which enables them to take arguments and produce return values larger than 64 bits. For discussion about argument evaluation and result types for bit operations, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.

AVG([DISTINCT] expr) [over_clause]
Returns the average value of expr. The DISTINCT option can be used to return the average of the distinct values of expr.
If there are no matching rows, AVG() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with DISTINCT.
```
mysql> SELECT student_name, AVG(test_score)
       FROM student
       GROUP BY student_name;
```
BIT_AND(expr) [over_clause]
Returns the bitwise AND of all bits in expr.
The result type depends on whether the function argument values are evaluated as binary strings or numbers:
- Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.
- Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. If the argument size exceeds 511 bytes, an ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.
If there are no matching rows, BIT_AND() returns a neutral value (all bits set to 1) having the same length as the argument values.
NULL values do not affect the result unless all values are NULL. In that case, the result is a neutral value having the same length as the argument values.
For more information discussion about argument evaluation and result types, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.
As of MySQL 8.0.12, this function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
BIT_OR(expr) [over_clause]
Returns the bitwise OR of all bits in expr.
The result type depends on whether the function argument values are evaluated as binary strings or numbers:
- Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.
- Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. If the argument size exceeds 511 bytes, an ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.
If there are no matching rows, BIT_OR() returns a neutral value (all bits set to 0) having the same length as the argument values.
NULL values do not affect the result unless all values are NULL. In that case, the result is a neutral value having the same length as the argument values.
For more information discussion about argument evaluation and result types, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.
As of MySQL 8.0.12, this function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
BIT_XOR(expr) [over_clause]
Returns the bitwise XOR of all bits in expr.
The result type depends on whether the function argument values are evaluated as binary strings or numbers:
- Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or NULL literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.
- Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an ER_INVALID_BITWISE_OPERANDS_SIZE error occurs. If the argument size exceeds 511 bytes, an ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE error occurs. Numeric evaluation produces an unsigned 64-bit integer.
If there are no matching rows, BIT_XOR() returns a neutral value (all bits set to 0) having the same length as the argument values.
NULL values do not affect the result unless all values are NULL. In that case, the result is a neutral value having the same length as the argument values.
For more information discussion about argument evaluation and result types, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.
As of MySQL 8.0.12, this function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
COUNT(expr) [over_clause]
Returns a count of the number of non-NULL values of expr in the rows retrieved by a SELECT statement. The result is a BIGINT value.
If there are no matching rows, COUNT() returns 0.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
```
mysql> SELECT student.student_name,COUNT(*)
       FROM student,course
       WHERE student.student_id=course.student_id
       GROUP BY student_name;
```
COUNT(*) is somewhat different in that it returns a count of the number of rows retrieved, whether or not they contain NULL values.
For MyISAM tables, COUNT(*) is optimized to return very quickly if the SELECT retrieves from one table, no other columns are retrieved, and there is no WHERE clause. For example:
```
mysql> SELECT COUNT(*) FROM student;
```
This optimization only applies to MyISAM tables, because an exact row count is stored for this storage engine and can be accessed very quickly. COUNT(1) is only subject to the same optimization if the first column is defined as NOT NULL.
For transactional storage engines such as InnoDB, storing an exact row count is problematic because multiple transactions may be occurring, each of which may affect the count. For more information about how InnoDB handles COUNT(*) operations, see Section 15.8.1.7, “Limits on InnoDB Tables”.
COUNT(DISTINCT expr,[expr...])
Returns a count of the number of rows with different non-NULL expr values.
If there are no matching rows, COUNT(DISTINCT) returns 0.
```
mysql> SELECT COUNT(DISTINCT results) FROM student;
```
In MySQL, you can obtain the number of distinct expression combinations that do not contain NULL by giving a list of expressions. In standard SQL, you would have to do a concatenation of all expressions inside COUNT(DISTINCT ...).
GROUP_CONCAT(expr)
This function returns a string result with the concatenated non-NULL values from a group. It returns NULL if there are no non-NULL values. The full syntax is as follows:
```
GROUP_CONCAT([DISTINCT] expr [,expr ...]
             [ORDER BY {unsigned_integer | col_name | expr}
                 [ASC | DESC] [,col_name ...]]
             [SEPARATOR str_val])
```
```
mysql> SELECT student_name,
         GROUP_CONCAT(test_score)
       FROM student
       GROUP BY student_name;
```
Or:
```
mysql> SELECT student_name,
         GROUP_CONCAT(DISTINCT test_score
                      ORDER BY test_score DESC SEPARATOR ' ')
       FROM student
       GROUP BY student_name;
```
In MySQL, you can get the concatenated values of expression combinations. To eliminate duplicate values, use the DISTINCT clause. To sort values in the result, use the ORDER BY clause. To sort in reverse order, add the DESC (descending) keyword to the name of the column you are sorting by in the ORDER BY clause. The default is ascending order; this may be specified explicitly using the ASC keyword. The default separator between values in a group is comma (,). To specify a separator explicitly, use SEPARATOR followed by the string literal value that should be inserted between group values. To eliminate the separator altogether, specify SEPARATOR ''.
The result is truncated to the maximum length that is given by the group_concat_max_len system variable, which has a default value of 1024. The value can be set higher, although the effective maximum length of the return value is constrained by the value of max_allowed_packet. The syntax to change the value of group_concat_max_len at runtime is as follows, where val is an unsigned integer:
```
SET [GLOBAL | SESSION] group_concat_max_len = val;
```
The return value is a nonbinary or binary string, depending on whether the arguments are nonbinary or binary strings. The result type is TEXT or BLOB unless group_concat_max_len is less than or equal to 512, in which case the result type is VARCHAR or VARBINARY.
See also CONCAT() and CONCAT_WS(): Section 12.5, “String Functions”.

JSON_ARRAYAGG(col_or_expr)

Aggregates a result set as a single JSON array whose elements consist of the rows. The order of elements in this array is undefined. The function acts on a column or an expression that evaluates to a single value. Returns NULL if the result contains no rows, or in the event of an error.

mysql> SELECT o_id, attribute, value FROM t3;
+------+-----------+-------+
| o_id | attribute | value |
+------+-----------+-------+
|    2 | color     | red   |
|    2 | fabric    | silk  |
|    3 | color     | green |
|    3 | shape     | square|
+------+-----------+-------+
4 rows in set (0.00 sec)

mysql> SELECT o_id, JSON_ARRAYAGG(attribute) AS attributes 
     > FROM t3 GROUP BY o_id;
+------+---------------------+
| o_id | attributes          |
+------+---------------------+
|    2 | ["color", "fabric"] |
|    3 | ["color", "shape"]  |
+------+---------------------+
2 rows in set (0.00 sec)

JSON_OBJECTAGG(key, value)

Takes two column names or expressions as arguments, the first of these being used as a key and the second as a value, and returns a JSON object containing key-value pairs. Returns NULL if the result contains no rows, or in the event of an error. An error occurs if any key name is NULL or the number of arguments is not equal to 2.

mysql> SELECT o_id, attribute, value FROM t3;
+------+-----------+-------+
| o_id | attribute | value |
+------+-----------+-------+
|    2 | color     | red   |
|    2 | fabric    | silk  |
|    3 | color     | green |
|    3 | shape     | square|
+------+-----------+-------+
4 rows in set (0.00 sec)

mysql> SELECT o_id, JSON_OBJECTAGG(attribute, value) FROM t3 GROUP BY o_id;
+------+----------------------------------------+
| o_id | JSON_OBJECTAGG(attribute, name)        |
+------+----------------------------------------+
|    2 | {"color": "red", "fabric": "silk"}     |
|    3 | {"color": "green", "shape": "square"}  |
+------+----------------------------------------+
1 row in set (0.00 sec)

MAX([DISTINCT] expr) [over_clause]
Returns the maximum value of expr. MAX() may take a string argument; in such cases, it returns the maximum string value. See Section 8.3.1, “How MySQL Uses Indexes”. The DISTINCT keyword can be used to find the maximum of the distinct values of expr, however, this produces the same result as omitting DISTINCT.
If there are no matching rows, MAX() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with DISTINCT.
```
mysql> SELECT student_name, MIN(test_score), MAX(test_score)
       FROM student
       GROUP BY student_name;
```
For MAX(), MySQL currently compares ENUM and SET columns by their string value rather than by the string's relative position in the set. This differs from how ORDER BY compares them.
MIN([DISTINCT] expr) [over_clause]
Returns the minimum value of expr. MIN() may take a string argument; in such cases, it returns the minimum string value. See Section 8.3.1, “How MySQL Uses Indexes”. The DISTINCT keyword can be used to find the minimum of the distinct values of expr, however, this produces the same result as omitting DISTINCT.
If there are no matching rows, MIN() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with DISTINCT.
```
mysql> SELECT student_name, MIN(test_score), MAX(test_score)
       FROM student
       GROUP BY student_name;
```
For MIN(), MySQL currently compares ENUM and SET columns by their string value rather than by the string's relative position in the set. This differs from how ORDER BY compares them.
STD(expr) [over_clause]
Returns the population standard deviation of expr. STD() is a synonym for the standard SQL function STDDEV_POP(), provided as a MySQL extension.
If there are no matching rows, STD() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
STDDEV(expr) [over_clause]
Returns the population standard deviation of expr. STDDEV() is a synonym for the standard SQL function STDDEV_POP(), provided for compatibility with Oracle.
If there are no matching rows, STDDEV() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
STDDEV_POP(expr) [over_clause]
Returns the population standard deviation of expr (the square root of VAR_POP()). You can also use STD() or STDDEV(), which are equivalent but not standard SQL.
If there are no matching rows, STDDEV_POP() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
STDDEV_SAMP(expr) [over_clause]
Returns the sample standard deviation of expr (the square root of VAR_SAMP().
If there are no matching rows, STDDEV_SAMP() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
SUM([DISTINCT] expr) [over_clause]
Returns the sum of expr. If the return set has no rows, SUM() returns NULL. The DISTINCT keyword can be used to sum only the distinct values of expr.
If there are no matching rows, SUM() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with DISTINCT.
VAR_POP(expr) [over_clause]
Returns the population standard variance of expr. It considers rows as the whole population, not as a sample, so it has the number of rows as the denominator. You can also use VARIANCE(), which is equivalent but is not standard SQL.
If there are no matching rows, VAR_POP() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
VAR_SAMP(expr) [over_clause]
Returns the sample variance of expr. That is, the denominator is the number of rows minus one.
If there are no matching rows, VAR_SAMP() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
VARIANCE(expr) [over_clause]
Returns the population standard variance of expr. VARIANCE() is a synonym for the standard SQL function VAR_POP(), provided as a MySQL extension.
If there are no matching rows, VARIANCE() returns NULL.
This function executes as a window function if over_clause is present. over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.

12.19.2 GROUP BY Modifiers

The GROUP BY clause permits a WITH ROLLUP modifier that causes summary output to include extra rows that represent higher-level (that is, super-aggregate) summary operations. ROLLUP thus enables you to answer questions at multiple levels of analysis with a single query. For example, ROLLUP can be used to provide support for OLAP (Online Analytical Processing) operations.

Suppose that a sales table has year, country, product, and profit columns for recording sales profitability:

CREATE TABLE sales
(
    year    INT,
    country VARCHAR(20),
    product VARCHAR(32),
    profit  INT
);

To summarize table contents per year, use a simple GROUP BY like this:

mysql> SELECT year, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC;
+------+--------+
| year | profit |
+------+--------+
| 2000 |   4525 |
| 2001 |   3010 |
+------+--------+

The output shows the total profit for each year. To also determine the total profit summed over all years, you must add up the individual values yourself or run an additional query. Or you can use ROLLUP, which provides both levels of analysis with a single query. Adding a WITH ROLLUP modifier to the GROUP BY clause causes the query to produce another row that shows the grand total over all year values:

mysql> SELECT year, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC WITH ROLLUP;
+------+--------+
| year | profit |
+------+--------+
| 2000 |   4525 |
| 2001 |   3010 |
| NULL |   7535 |
+------+--------+

The NULL value in the year column identifies the grand total super-aggregate line.

ROLLUP has a more complex effect when there are multiple GROUP BY columns. In this case, each time there is a change in value in any but the last grouping column, the query produces an extra super-aggregate summary row.

For example, without ROLLUP, a summary of the sales table based on year, country, and product might look like this, where the output indicates summary values only at the year/country/product level of analysis:

mysql> SELECT year, country, product, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC, country ASC, product ASC;
+------+---------+------------+--------+
| year | country | product    | profit |
+------+---------+------------+--------+
| 2000 | Finland | Computer   |   1500 |
| 2000 | Finland | Phone      |    100 |
| 2000 | India   | Calculator |    150 |
| 2000 | India   | Computer   |   1200 |
| 2000 | USA     | Calculator |     75 |
| 2000 | USA     | Computer   |   1500 |
| 2001 | Finland | Phone      |     10 |
| 2001 | USA     | Calculator |     50 |
| 2001 | USA     | Computer   |   2700 |
| 2001 | USA     | TV         |    250 |
+------+---------+------------+--------+

With ROLLUP added, the query produces several extra rows:

mysql> SELECT year, country, product, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC, country ASC, product ASC WITH ROLLUP;
+------+---------+------------+--------+
| year | country | product    | profit |
+------+---------+------------+--------+
| 2000 | Finland | Computer   |   1500 |
| 2000 | Finland | Phone      |    100 |
| 2000 | Finland | NULL       |   1600 |
| 2000 | India   | Calculator |    150 |
| 2000 | India   | Computer   |   1200 |
| 2000 | India   | NULL       |   1350 |
| 2000 | USA     | Calculator |     75 |
| 2000 | USA     | Computer   |   1500 |
| 2000 | USA     | NULL       |   1575 |
| 2000 | NULL    | NULL       |   4525 |
| 2001 | Finland | Phone      |     10 |
| 2001 | Finland | NULL       |     10 |
| 2001 | USA     | Calculator |     50 |
| 2001 | USA     | Computer   |   2700 |
| 2001 | USA     | TV         |    250 |
| 2001 | USA     | NULL       |   3000 |
| 2001 | NULL    | NULL       |   3010 |
| NULL | NULL    | NULL       |   7535 |
+------+---------+------------+--------+

Now the output includes summary information at four levels of analysis, not just one:

Following each set of product rows for a given year and country, an extra summary row appears showing the total for all products. These rows have the product column set to NULL.
Following each set of rows for a given year, an extra summary row appears showing the total for all countries and products. These rows have the country and products columns set to NULL.
Finally, following all other rows, an extra summary row appears showing the grand total for all years, countries, and products. This row has the year, country, and products columns set to NULL.

Previously, MySQL did not allow the use of DISTINCT or ORDER BY in a query having a WITH ROLLUP option. This restriction is lifted in MySQL 8.0.12 and later. (Bug #87450, Bug #86311, Bug #26640100, Bug #26073513)

The GROUPING() function is available for use in the select list or HAVING clause of GROUP BY ... WITH ROLLUP queries, to test whether NULL values in the result represent super-aggregate values. For example, GROUPING(year) returns 1 when NULL in the year column occurs in a super-aggregate row, and 0 otherwise. Similarly, GROUPING(country) and GROUPING(product) return 1 for super-aggregate NULL values in the country and product columns, respectively:

mysql> SELECT
         year, country, product, SUM(profit) AS profit,
         GROUPING(year) AS grp_year,
         GROUPING(country) AS grp_country,
         GROUPING(product) AS grp_product
       FROM sales
       GROUP BY year ASC, country ASC, product ASC WITH ROLLUP;
+------+---------+------------+--------+----------+-------------+-------------+
| year | country | product    | profit | grp_year | grp_country | grp_product |
+------+---------+------------+--------+----------+-------------+-------------+
| 2000 | Finland | Computer   |   1500 |        0 |           0 |           0 |
| 2000 | Finland | Phone      |    100 |        0 |           0 |           0 |
| 2000 | Finland | NULL       |   1600 |        0 |           0 |           1 |
| 2000 | India   | Calculator |    150 |        0 |           0 |           0 |
| 2000 | India   | Computer   |   1200 |        0 |           0 |           0 |
| 2000 | India   | NULL       |   1350 |        0 |           0 |           1 |
| 2000 | USA     | Calculator |     75 |        0 |           0 |           0 |
| 2000 | USA     | Computer   |   1500 |        0 |           0 |           0 |
| 2000 | USA     | NULL       |   1575 |        0 |           0 |           1 |
| 2000 | NULL    | NULL       |   4525 |        0 |           1 |           1 |
| 2001 | Finland | Phone      |     10 |        0 |           0 |           0 |
| 2001 | Finland | NULL       |     10 |        0 |           0 |           1 |
| 2001 | USA     | Calculator |     50 |        0 |           0 |           0 |
| 2001 | USA     | Computer   |   2700 |        0 |           0 |           0 |
| 2001 | USA     | TV         |    250 |        0 |           0 |           0 |
| 2001 | USA     | NULL       |   3000 |        0 |           0 |           1 |
| 2001 | NULL    | NULL       |   3010 |        0 |           1 |           1 |
| NULL | NULL    | NULL       |   7535 |        1 |           1 |           1 |
+------+---------+------------+--------+----------+-------------+-------------+

Instead of displaying the GROUPING() results directly, you can use GROUPING() to substitute labels for super-aggregate NULL values:

mysql> SELECT
         IF(GROUPING(year), 'All years', year) AS year,
         IF(GROUPING(country), 'All countries', country) AS country,
         IF(GROUPING(product), 'All products', product) AS product,
         SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC, country ASC, product ASC WITH ROLLUP;
+-----------+---------------+--------------+--------+
| year      | country       | product      | profit |
+-----------+---------------+--------------+--------+
| 2000      | Finland       | Computer     |   1500 |
| 2000      | Finland       | Phone        |    100 |
| 2000      | Finland       | All products |   1600 |
| 2000      | India         | Calculator   |    150 |
| 2000      | India         | Computer     |   1200 |
| 2000      | India         | All products |   1350 |
| 2000      | USA           | Calculator   |     75 |
| 2000      | USA           | Computer     |   1500 |
| 2000      | USA           | All products |   1575 |
| 2000      | All countries | All products |   4525 |
| 2001      | Finland       | Phone        |     10 |
| 2001      | Finland       | All products |     10 |
| 2001      | USA           | Calculator   |     50 |
| 2001      | USA           | Computer     |   2700 |
| 2001      | USA           | TV           |    250 |
| 2001      | USA           | All products |   3000 |
| 2001      | All countries | All products |   3010 |
| All years | All countries | All products |   7535 |
+-----------+---------------+--------------+--------+

With multiple expression arguments, GROUPING() returns a result representing a bitmask the combines the results for each expression, with the lowest-order bit corresponding to the result for the rightmost expression. For example, GROUPING(year, country, product) is evaluated like this:

  result for GROUPING(product)
+ result for GROUPING(country) << 1
+ result for GROUPING(year) << 2

The result of such a GROUPING() is nonzero if any of the expressions represents a super-aggregate NULL, so you can return only the super-aggregate rows and filter out the regular grouped rows like this:

mysql> SELECT year, country, product, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC, country ASC, product ASC WITH ROLLUP
       HAVING GROUPING(year, country, product) <> 0;
+------+---------+---------+--------+
| year | country | product | profit |
+------+---------+---------+--------+
| 2000 | Finland | NULL    |   1600 |
| 2000 | India   | NULL    |   1350 |
| 2000 | USA     | NULL    |   1575 |
| 2000 | NULL    | NULL    |   4525 |
| 2001 | Finland | NULL    |     10 |
| 2001 | USA     | NULL    |   3000 |
| 2001 | NULL    | NULL    |   3010 |
| NULL | NULL    | NULL    |   7535 |
+------+---------+---------+--------+

The sales table contains no NULL values, so all NULL values in a ROLLUP result represent super-aggregate values. When the data set contains NULL values, ROLLUP summaries may contain NULL values not only in super-aggregate rows, but also in regular grouped rows. GROUPING() enables these to be distinguished. Suppose that table t1 contains a simple data set with two grouping factors for a set of quantity values, where NULL indicates something like “other” or “unknown”:

mysql> SELECT * FROM t1;
+------+-------+----------+
| name | size  | quantity |
+------+-------+----------+
| ball | small |       10 |
| ball | large |       20 |
| ball | NULL  |        5 |
| hoop | small |       15 |
| hoop | large |        5 |
| hoop | NULL  |        3 |
+------+-------+----------+

A simple ROLLUP operation produces these results, in which it is not so easy to distinguish NULL values in super-aggregate rows from NULL values in regular grouped rows:

mysql> SELECT name, size, SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size WITH ROLLUP;
+------+-------+----------+
| name | size  | quantity |
+------+-------+----------+
| ball | NULL  |        5 |
| ball | large |       20 |
| ball | small |       10 |
| ball | NULL  |       35 |
| hoop | NULL  |        3 |
| hoop | large |        5 |
| hoop | small |       15 |
| hoop | NULL  |       23 |
| NULL | NULL  |       58 |
+------+-------+----------+

Using GROUPING() to substitute labels for the super-aggregate NULL values makes the result easier to interpret:

mysql> SELECT
         IF(GROUPING(name) = 1, 'All items', name) AS name,
         IF(GROUPING(size) = 1, 'All sizes', size) AS size,
         SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size WITH ROLLUP;
+-----------+-----------+----------+
| name      | size      | quantity |
+-----------+-----------+----------+
| ball      | NULL      |        5 |
| ball      | large     |       20 |
| ball      | small     |       10 |
| ball      | All sizes |       35 |
| hoop      | NULL      |        3 |
| hoop      | large     |        5 |
| hoop      | small     |       15 |
| hoop      | All sizes |       23 |
| All items | All sizes |       58 |
+-----------+-----------+----------+

Other Considerations When using ROLLUP

The following discussion lists some behaviors specific to the MySQL implementation of ROLLUP.

When you use ROLLUP, you cannot also use an ORDER BY clause to sort the results. In other words, ROLLUP and ORDER BY are mutually exclusive in MySQL. However, you still have some control over sort order. GROUP BY in MySQL implicitly sorts results by default (in the absence of ASC or DESC designators). However, implicit GROUP BY sorting in MySQL is deprecated. To achieve a specific sort order of grouped results:

Use explicit ASC and DESC keywords with columns named in the GROUP BY list to specify sort order for individual columns. In this case, the super-aggregate summary rows added by ROLLUP still appear after the rows from which they are calculated, regardless of the sort order.
To work around the restriction that prevents using ROLLUP with ORDER BY, generate the grouped result set as a derived table and apply ORDER BY to it. For example:
```
SELECT * FROM
(SELECT year, SUM(profit) FROM sales GROUP BY year WITH ROLLUP) AS dt
ORDER BY year;
```
In this case, the super-aggregate summary rows sort with the rows from which they are calculated, and their placement depends on sort order (at the beginning for ascending sort, at the end for descending sort).

LIMIT can be used to restrict the number of rows returned to the client. LIMIT is applied after ROLLUP, so the limit applies against the extra rows added by ROLLUP. For example:

mysql> SELECT year, country, product, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC, country ASC, product ASC WITH ROLLUP
       LIMIT 5;
+------+---------+------------+--------+
| year | country | product    | profit |
+------+---------+------------+--------+
| 2000 | Finland | Computer   |   1500 |
| 2000 | Finland | Phone      |    100 |
| 2000 | Finland | NULL       |   1600 |
| 2000 | India   | Calculator |    150 |
| 2000 | India   | Computer   |   1200 |
+------+---------+------------+--------+

Using LIMIT with ROLLUP may produce results that are more difficult to interpret, because there is less context for understanding the super-aggregate rows.

The NULL indicators in each super-aggregate row are produced when the row is sent to the client. The server looks at the columns named in the GROUP BY clause following the leftmost one that has changed value. For any column in the result set with a name that matches any of those names, its value is set to NULL. (If you specify grouping columns by column position, the server identifies which columns to set to NULL by position.)

Because the NULL values in the super-aggregate rows are placed into the result set at such a late stage in query processing, you can test them as NULL values only in the select list or HAVING clause. You cannot test them as NULL values in join conditions or the WHERE clause to determine which rows to select. For example, you cannot add WHERE product IS NULL to the query to eliminate from the output all but the super-aggregate rows.

The NULL values do appear as NULL on the client side and can be tested as such using any MySQL client programming interface. However, at this point, you cannot distinguish whether a NULL represents a regular grouped value or a super-aggregate value.

A MySQL extension permits a column that does not appear in the GROUP BY list to be named in the select list. (For information about nonaggregated columns and GROUP BY, see Section 12.19.3, “MySQL Handling of GROUP BY”.) In this case, the server is free to choose any value from this nonaggregated column in summary rows, and this includes the extra rows added by WITH ROLLUP. For example, in the following query, country is a nonaggregated column that does not appear in the GROUP BY list and values chosen for this column are nondeterministic:

mysql> SELECT year, country, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC WITH ROLLUP;
+------+---------+--------+
| year | country | profit |
+------+---------+--------+
| 2000 | India   |   4525 |
| 2001 | USA     |   3010 |
| NULL | USA     |   7535 |
+------+---------+--------+

This behavior is permitted when the ONLY_FULL_GROUP_BY SQL mode is not enabled. If that mode is enabled, the server rejects the query as illegal because country is not listed in the GROUP BY clause. With ONLY_FULL_GROUP_BY enabled, you can still execute the query by using the ANY_VALUE() function for nondeterministic-value columns:

mysql> SELECT year, ANY_VALUE(country) AS country, SUM(profit) AS profit
       FROM sales
       GROUP BY year ASC WITH ROLLUP;
+------+---------+--------+
| year | country | profit |
+------+---------+--------+
| 2000 | India   |   4525 |
| 2001 | USA     |   3010 |
| NULL | USA     |   7535 |
+------+---------+--------+

12.19.3 MySQL Handling of GROUP BY

SQL92 and earlier does not permit queries for which the select list, HAVING condition, or ORDER BY list refer to nonaggregated columns that are not named in the GROUP BY clause. For example, this query is illegal in standard SQL92 because the nonaggregated name column in the select list does not appear in the GROUP BY:

SELECT o.custid, c.name, MAX(o.payment)
  FROM orders AS o, customers AS c
  WHERE o.custid = c.custid
  GROUP BY o.custid;

For the query to be legal in SQL92, the name column must be omitted from the select list or named in the GROUP BY clause.

SQL99 and later permits such nonaggregates per optional feature T301 if they are functionally dependent on GROUP BY columns: If such a relationship exists between name and custid, the query is legal. This would be the case, for example, were custid a primary key of customers.

MySQL implements detection of functional dependence. If the ONLY_FULL_GROUP_BY SQL mode is enabled (which it is by default), MySQL rejects queries for which the select list, HAVING condition, or ORDER BY list refer to nonaggregated columns that are neither named in the GROUP BY clause nor are functionally dependent on them.

If ONLY_FULL_GROUP_BY is disabled, a MySQL extension to the standard SQL use of GROUP BY permits the select list, HAVING condition, or ORDER BY list to refer to nonaggregated columns even if the columns are not functionally dependent on GROUP BY columns. This causes MySQL to accept the preceding query. In this case, the server is free to choose any value from each group, so unless they are the same, the values chosen are nondeterministic, which is probably not what you want. Furthermore, the selection of values from each group cannot be influenced by adding an ORDER BY clause. Result set sorting occurs after values have been chosen, and ORDER BY does not affect which value within each group the server chooses. Disabling ONLY_FULL_GROUP_BY is useful primarily when you know that, due to some property of the data, all values in each nonaggregated column not named in the GROUP BY are the same for each group.

You can achieve the same effect without disabling ONLY_FULL_GROUP_BY by using ANY_VALUE() to refer to the nonaggregated column.

The following discussion demonstrates functional dependence, the error message MySQL produces when functional dependence is absent, and ways of causing MySQL to accept a query in the absence of functional dependence.

This query might be invalid with ONLY_FULL_GROUP_BY enabled because the nonaggregated address column in the select list is not named in the GROUP BY clause:

SELECT name, address, MAX(age) FROM t GROUP BY name;

The query is valid if name is a primary key of t or is a unique NOT NULL column. In such cases, MySQL recognizes that the selected column is functionally dependent on a grouping column. For example, if name is a primary key, its value determines the value of address because each group has only one value of the primary key and thus only one row. As a result, there is no randomness in the choice of address value in a group and no need to reject the query.

The query is invalid if name is not a primary key of t or a unique NOT NULL column. In this case, no functional dependency can be inferred and an error occurs:


mysql> SELECT name, address, MAX(age) FROM t GROUP BY name;
ERROR 1055 (42000): Expression #2 of SELECT list is not in GROUP
BY clause and contains nonaggregated column 'mydb.t.address' which
is not functionally dependent on columns in GROUP BY clause; this
is incompatible with sql_mode=only_full_group_by

If you know that, for a given data set, each name value in fact uniquely determines the address value, address is effectively functionally dependent on name. To tell MySQL to accept the query, you can use the ANY_VALUE() function:

SELECT name, ANY_VALUE(address), MAX(age) FROM t GROUP BY name;

Alternatively, disable ONLY_FULL_GROUP_BY.

The preceding example is quite simple, however. In particular, it is unlikely you would group on a single primary key column because every group would contain only one row. For addtional examples demonstrating functional dependence in more complex queries, see Section 12.19.4, “Detection of Functional Dependence”.

If a query has aggregate functions and no GROUP BY clause, it cannot have nonaggregated columns in the select list, HAVING condition, or ORDER BY list with ONLY_FULL_GROUP_BY enabled:


mysql> SELECT name, MAX(age) FROM t;
ERROR 1140 (42000): In aggregated query without GROUP BY, expression
#1 of SELECT list contains nonaggregated column 'mydb.t.name'; this
is incompatible with sql_mode=only_full_group_by

Without GROUP BY, there is a single group and it is nondeterministic which name value to choose for the group. Here, too, ANY_VALUE() can be used, if it is immaterial which name value MySQL chooses:

SELECT ANY_VALUE(name), MAX(age) FROM t;

ONLY_FULL_GROUP_BY also affects handling of queries that use DISTINCT and ORDER BY. Consider the case of a table t with three columns c1, c2, and c3 that contains these rows:

Suppose that we execute the following query, expecting the results to be ordered by c3:

SELECT DISTINCT c1, c2 FROM t ORDER BY c3;

To order the result, duplicates must be eliminated first. But to do so, should we keep the first row or the third? This arbitrary choice influences the retained value of c3, which in turn influences ordering and makes it arbitrary as well. To prevent this problem, a query that has DISTINCT and ORDER BY is rejected as invalid if any ORDER BY expression does not satisfy at least one of these conditions:

The expression is equal to one in the select list
All columns referenced by the expression and belonging to the query's selected tables are elements of the select list

Another MySQL extension to standard SQL permits references in the HAVING clause to aliased expressions in the select list. For example, the following query returns name values that occur only once in table orders:

SELECT name, COUNT(name) FROM orders
  GROUP BY name
  HAVING COUNT(name) = 1;

The MySQL extension permits the use of an alias in the HAVING clause for the aggregated column:

SELECT name, COUNT(name) AS c FROM orders
  GROUP BY name
  HAVING c = 1;

Standard SQL permits only column expressions in GROUP BY clauses, so a statement such as this is invalid because FLOOR(value/100) is a noncolumn expression:

SELECT id, FLOOR(value/100)
  FROM tbl_name
  GROUP BY id, FLOOR(value/100);

MySQL extends standard SQL to permit noncolumn expressions in GROUP BY clauses and considers the preceding statement valid.

Standard SQL also does not permit aliases in GROUP BY clauses. MySQL extends standard SQL to permit aliases, so another way to write the query is as follows:

SELECT id, FLOOR(value/100) AS val
  FROM tbl_name
  GROUP BY id, val;

The alias val is considered a column expression in the GROUP BY clause.

In the presence of a noncolumn expression in the GROUP BY clause, MySQL recognizes equality between that expression and expressions in the select list. This means that with ONLY_FULL_GROUP_BY SQL mode enabled, the query containing GROUP BY id, FLOOR(value/100) is valid because that same FLOOR() expression occurs in the select list. However, MySQL does not try to recognize functional dependence on GROUP BY noncolumn expressions, so the following query is invalid with ONLY_FULL_GROUP_BY enabled, even though the third selected expression is a simple formula of the id column and the FLOOR() expression in the GROUP BY clause:

SELECT id, FLOOR(value/100), id+FLOOR(value/100)
  FROM tbl_name
  GROUP BY id, FLOOR(value/100);

A workaround is to use a derived table:

SELECT id, F, id+F
  FROM
    (SELECT id, FLOOR(value/100) AS F
     FROM tbl_name
     GROUP BY id, FLOOR(value/100)) AS dt;

12.19.4 Detection of Functional Dependence

The following discussion provides several examples of the ways in which MySQL detects functional dependencies. The examples use this notation:

{X} -> {Y}

Understand this as “X uniquely determines Y,” which also means that Y is functionally dependent on X.

The examples use the world database, which can be downloaded from the MySQL Documentation page. You can find details on how to install the database on the same page.

Functional Dependencies Derived from Keys

The following query selects, for each country, a count of spoken languages:

SELECT co.Name, COUNT(*)
FROM countrylanguage cl, country co
WHERE cl.CountryCode = co.Code
GROUP BY co.Code;

co.Code is a primary key of co, so all columns of co are functionally dependent on it, as expressed using this notation:

{co.Code} -> {co.*}

Thus, co.name is functionally dependent on GROUP BY columns and the query is valid.

A UNIQUE index over a NOT NULL column could be used instead of a primary key and the same functional dependence would apply. (This is not true for a UNIQUE index that permits NULL values because it permits multiple NULL values and in that case uniqueness is lost.)

Functional Dependencies Derived from Multiple-Column Keys and from Equalities

This query selects, for each country, a list of all spoken languages and how many people speak them:

SELECT co.Name, cl.Language,
cl.Percentage * co.Population / 100.0 AS SpokenBy
FROM countrylanguage cl, country co
WHERE cl.CountryCode = co.Code
GROUP BY cl.CountryCode, cl.Language;

The pair (cl.CountryCode, cl.Language) is a two-column composite primary key of cl, so that column pair uniquely determines all columns of cl:

{cl.CountryCode, cl.Language} -> {cl.*}

Moreover, because of the equality in the WHERE clause:

{cl.CountryCode} -> {co.Code}

And, because co.Code is primary key of co:

{co.Code} -> {co.*}

“Uniquely determines” relationships are transitive, therefore:

{cl.CountryCode, cl.Language} -> {cl.*,co.*}

As a result, the query is valid.

As with the previous example, a UNIQUE key over NOT NULL columns could be used instead of a primary key.

An INNER JOIN condition can be used instead of WHERE. The same functional dependencies apply:

SELECT co.Name, cl.Language,
cl.Percentage * co.Population/100.0 AS SpokenBy
FROM countrylanguage cl INNER JOIN country co
ON cl.CountryCode = co.Code
GROUP BY cl.CountryCode, cl.Language;

Functional Dependency Special Cases

Whereas an equality test in a WHERE condition or INNER JOIN condition is symmetric, an equality test in an outer join condition is not, because tables play different roles.

Assume that referential integrity has been accidentally broken and there exists a row of countrylanguage without a corresponding row in country. Consider the same query as in the previous example, but with a LEFT JOIN:

SELECT co.Name, cl.Language,
cl.Percentage * co.Population/100.0 AS SpokenBy
FROM countrylanguage cl LEFT JOIN country co
ON cl.CountryCode = co.Code
GROUP BY cl.CountryCode, cl.Language;

For a given value of cl.CountryCode, the value of co.Code in the join result is either found in a matching row (determined by cl.CountryCode) or is NULL-complemented if there is no match (also determined by cl.CountryCode). In each case, this relationship applies:

{cl.CountryCode} -> {co.Code}

cl.CountryCode is itself functionally dependent on {cl.CountryCode, cl.Language} which is a primary key.

If in the join result co.Code is NULL-complemented, co.Name is as well. If co.Code is not NULL-complemented, then because co.Code is a primary key, it determines co.Name. Therefore, in all cases:

{co.Code} -> {co.Name}

Which yields:

{cl.CountryCode, cl.Language} -> {cl.*,co.*}

As a result, the query is valid.

However, suppose that the tables are swapped, as in this query:

SELECT co.Name, cl.Language,
cl.Percentage * co.Population/100.0 AS SpokenBy
FROM country co LEFT JOIN countrylanguage cl
ON cl.CountryCode = co.Code
GROUP BY cl.CountryCode, cl.Language;

Now this relationship does not apply:

{cl.CountryCode, cl.Language} -> {cl.*,co.*}

Indeed, all NULL-complemented rows made for cl will be put into a single group (they have both GROUP BY columns equal to NULL), and inside this group the value of co.Name can vary. The query is invalid and MySQL rejects it.

Functional dependence in outer joins is thus linked to whether determinant columns belong to the left or right side of the LEFT JOIN. Determination of functional dependence becomes more complex if there are nested outer joins or the join condition does not consist entirely of equality comparisons.

Functional Dependencies and Views

Suppose that a view on countries produces their code, their name in uppercase, and how many different official languages they have:

CREATE VIEW Country2 AS
SELECT co.Code, UPPER(co.Name) AS UpperName,
COUNT(cl.Language) AS OfficialLanguages
FROM country AS co JOIN countrylanguage AS cl
ON cl.CountryCode = co.Code
WHERE cl.isOfficial = 'T'
GROUP BY co.Code;

This definition is valid because:

{co.Code} -> {co.*}

In the view result, the first selected column is co.Code, which is also the group column and thus determines all other selected expressions:

{Country2.Code} -> {Country2.*}

MySQL understands this and uses this information, as described following.

This query displays countries, how many different official languages they have, and how many cities they have, by joining the view with the city table:

SELECT co2.Code, co2.UpperName, co2.OfficialLanguages,
COUNT(*) AS Cities
FROM country2 AS co2 JOIN city ci
ON ci.CountryCode = co2.Code
GROUP BY co2.Code;

This query is valid because, as seen previously:

{co2.Code} -> {co2.*}

MySQL is able to discover a functional dependency in the result of a view and use that to validate a query which uses the view. The same would be true if country2 were a derived table (or common table expression), as in:

SELECT co2.Code, co2.UpperName, co2.OfficialLanguages,
COUNT(*) AS Cities
FROM
(
 SELECT co.Code, UPPER(co.Name) AS UpperName,
 COUNT(cl.Language) AS OfficialLanguages
 FROM country AS co JOIN countrylanguage AS cl
 ON cl.CountryCode=co.Code
 WHERE cl.isOfficial='T'
 GROUP BY co.Code
) AS co2
JOIN city ci ON ci.CountryCode = co2.Code
GROUP BY co2.Code;

Combinations of Functional Dependencies

MySQL is able to combine all of the preceding types of functional dependencies (key based, equality based, view based) to validate more complex queries.

12.20 Window Functions

12.20.1 Window Function Descriptions
12.20.2 Window Function Concepts and Syntax
12.20.3 Window Function Frame Specification
12.20.4 Named Windows
12.20.5 Window Function Restrictions

MySQL supports window functions that, for each row from a query, perform a calculation using rows related to that row. The following sections discuss how to use window functions, including descriptions of the OVER and WINDOW clauses. The first section provides descriptions of the nonaggregate window functions. For descriptions of the aggregate window functions, see Section 12.19.1, “Aggregate (GROUP BY) Function Descriptions”.

For information about optimization and window functions, see Section 8.2.1.18, “Window Function Optimization”.

12.20.1 Window Function Descriptions

This section describes nonaggregate window functions that, for each row from a query, perform a calculation using rows related to that row. Most aggregate functions also can be used as window functions; see Section 12.19.1, “Aggregate (GROUP BY) Function Descriptions”.

For window function usage information and examples, and definitions of terms such as the OVER clause, window, partition, frame, and peer, see Section 12.20.2, “Window Function Concepts and Syntax”.

Table 12.26 Window Functions

Name	Description
`CUME_DIST()`	Cumulative distribution value
`DENSE_RANK()`	Rank of current row within its partition, without gaps
`FIRST_VALUE()`	Value of argument from first row of window frame
`LAG()`	Value of argument from row lagging current row within partition
`LAST_VALUE()`	Value of argument from last row of window frame
`LEAD()`	Value of argument from row leading current row within partition
`NTH_VALUE()`	Value of argument from N-th row of window frame
`NTILE()`	Bucket number of current row within its partition.
`PERCENT_RANK()`	Percentage rank value
`RANK()`	Rank of current row within its partition, with gaps
`ROW_NUMBER()`	Number of current row within its partition

In the following function descriptions, over_clause represents the OVER clause, described in Section 12.20.2, “Window Function Concepts and Syntax”. Some window functions permit a null_treatment clause that specifies how to handle NULL values when calculating results. This clause is optional. It is part of the SQL standard, but the MySQL implementation permits only RESPECT NULLS (which is also the default). This means that NULL values are considered when calculating results. IGNORE NULLS is parsed, but produces an error.

CUME_DIST() over_clause
Returns the cumulative distribution of a value within a group of values; that is, the percentage of partition values less than or equal to the value in the current row. This represents the number of rows preceding or peer with the current row in the window ordering of the window partition divided by the total number of rows in the window partition. Return values range from 0 to 1.
This function should be used with ORDER BY to sort partition rows into the desired order. Without ORDER BY, all rows are peers and have value N/N = 1, where N is the partition size.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
The following query shows, for the set of values in the val column, the CUME_DIST() value for each row, as well as the percentage rank value returned by the similar PERCENT_RANK() function. For reference, the query also displays row numbers using ROW_NUMBER():
```
mysql> SELECT
         val,
         ROW_NUMBER()   OVER w AS 'row_number',
         CUME_DIST()    OVER w AS 'cume_dist',
         PERCENT_RANK() OVER w AS 'percent_rank'
       FROM numbers
       WINDOW w AS (ORDER BY val);
+------+------------+--------------------+--------------+
| val  | row_number | cume_dist          | percent_rank |
+------+------------+--------------------+--------------+
|    1 |          1 | 0.2222222222222222 |            0 |
|    1 |          2 | 0.2222222222222222 |            0 |
|    2 |          3 | 0.3333333333333333 |         0.25 |
|    3 |          4 | 0.6666666666666666 |        0.375 |
|    3 |          5 | 0.6666666666666666 |        0.375 |
|    3 |          6 | 0.6666666666666666 |        0.375 |
|    4 |          7 | 0.8888888888888888 |         0.75 |
|    4 |          8 | 0.8888888888888888 |         0.75 |
|    5 |          9 |                  1 |            1 |
+------+------------+--------------------+--------------+
```
DENSE_RANK() over_clause
Returns the rank of the current row within its partition, without gaps. Peers are considered ties and receive the same rank. This function assigns consecutive ranks to peer groups; the result is that groups of size greater than one do not produce noncontiguous rank numbers. For an example, see the RANK() function description.
This function should be used with ORDER BY to sort partition rows into the desired order. Without ORDER BY, all rows are peers.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.

FIRST_VALUE(expr) [null_treatment] over_clause

Returns the value of expr from the first row of the window frame.

over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”. null_treatment is as described in the section introduction.

The following query demonstrates FIRST_VALUE(), LAST_VALUE(), and two instances of NTH_VALUE():

mysql> SELECT
         time, subject, val,
         FIRST_VALUE(val)  OVER w AS 'first',
         LAST_VALUE(val)   OVER w AS 'last',
         NTH_VALUE(val, 2) OVER w AS 'second',
         NTH_VALUE(val, 4) OVER w AS 'fourth'
       FROM observations
       WINDOW w AS (PARTITION BY subject ORDER BY time
                    ROWS UNBOUNDED PRECEDING);
+----------+---------+------+-------+------+--------+--------+
| time     | subject | val  | first | last | second | fourth |
+----------+---------+------+-------+------+--------+--------+
| 07:00:00 | st113   |   10 |    10 |   10 |   NULL |   NULL |
| 07:15:00 | st113   |    9 |    10 |    9 |      9 |   NULL |
| 07:30:00 | st113   |   25 |    10 |   25 |      9 |   NULL |
| 07:45:00 | st113   |   20 |    10 |   20 |      9 |     20 |
| 07:00:00 | xh458   |    0 |     0 |    0 |   NULL |   NULL |
| 07:15:00 | xh458   |   10 |     0 |   10 |     10 |   NULL |
| 07:30:00 | xh458   |    5 |     0 |    5 |     10 |   NULL |
| 07:45:00 | xh458   |   30 |     0 |   30 |     10 |     30 |
| 08:00:00 | xh458   |   25 |     0 |   25 |     10 |     30 |
+----------+---------+------+-------+------+--------+--------+

Each function uses the rows in the current frame, which, per the window definition shown, extends from the first partition row to the current row. For the NTH_VALUE() calls, the current frame does not always include the requested row; in such cases, the return value is NULL.

LAG(expr [, N[, default]]) [null_treatment] over_clause
Returns the value of expr from the row that lags (precedes) the current row by N rows within its partition. If there is no such row, the return value is default. For example, if N is 3, the return value is default for the first two rows. If N or default are missing, the defaults are 1 and NULL, respectively.
N must be a literal nonnegative integer. If N is 0, expr is evaluated for the current row.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”. null_treatment is as described in the section introduction.
LAG() (and the similar LEAD() function) are often used to compute differences between rows. The following query shows a set of time-ordered observations and, for each one, the LAG() and LEAD() values from the adjoining rows, as well as the differences between the current and adjoining rows:
```
mysql> SELECT
         t, val,
         LAG(val)        OVER w AS 'lag',
         LEAD(val)       OVER w AS 'lead',
         val - LAG(val)  OVER w AS 'lag diff',
         val - LEAD(val) OVER w AS 'lead diff'
       FROM series
       WINDOW w AS (ORDER BY t);
+----------+------+------+------+----------+-----------+
| t        | val  | lag  | lead | lag diff | lead diff |
+----------+------+------+------+----------+-----------+
| 12:00:00 |  100 | NULL |  125 |     NULL |       -25 |
| 13:00:00 |  125 |  100 |  132 |       25 |        -7 |
| 14:00:00 |  132 |  125 |  145 |        7 |       -13 |
| 15:00:00 |  145 |  132 |  140 |       13 |         5 |
| 16:00:00 |  140 |  145 |  150 |       -5 |       -10 |
| 17:00:00 |  150 |  140 |  200 |       10 |       -50 |
| 18:00:00 |  200 |  150 | NULL |       50 |      NULL |
+----------+------+------+------+----------+-----------+
```
In the example, the LAG() and LEAD() calls use the default N and default values of 1 and NULL, respectively.
The first row shows what happens when there is no previous row for LAG(): The function returns the default value (in this case, NULL). The last row shows the same thing when there is no next row for LEAD().
LAG() and LEAD() also serve to compute sums rather than differences. Consider this data set, which contains the first few numbers of the Fibonacci series:
```
mysql> SELECT n FROM fib ORDER BY n;
+------+
| n    |
+------+
|    1 |
|    1 |
|    2 |
|    3 |
|    5 |
|    8 |
+------+
```
The following query shows the LAG() and LEAD() values for the rows adjacent to the current row. It also uses those functions to add to the current row value the values from the preceding and following rows. The effect is to generate the next number in the Fibonacci series, and the next number after that:
```
mysql> SELECT
         n,
         LAG(n, 1, 0)      OVER w AS 'lag',
         LEAD(n, 1, 0)     OVER w AS 'lead',
         n + LAG(n, 1, 0)  OVER w AS 'next_n',
         n + LEAD(n, 1, 0) OVER w AS 'next_next_n'
       FROM fib
       WINDOW w AS (ORDER BY n);
+------+------+------+--------+-------------+
| n    | lag  | lead | next_n | next_next_n |
+------+------+------+--------+-------------+
|    1 |    0 |    1 |      1 |           2 |
|    1 |    1 |    2 |      2 |           3 |
|    2 |    1 |    3 |      3 |           5 |
|    3 |    2 |    5 |      5 |           8 |
|    5 |    3 |    8 |      8 |          13 |
|    8 |    5 |    0 |     13 |           8 |
+------+------+------+--------+-------------+
```
One way to generate the initial set of Fibonacci numbers is to use a recursive common table expression. For an example, see Fibonacci Series Generation.
LAST_VALUE(expr) [null_treatment] over_clause
Returns the value of expr from the last row of the window frame.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”. null_treatment is as described in the section introduction.
For an example, see the FIRST_VALUE() function description.
LEAD(expr [, N[, default]]) [null_treatment] over_clause
Returns the value of expr from the row that leads (follows) the current row by N rows within its partition. If there is no such row, the return value is default. For example, if N is 3, the return value is default for the last two rows. If N or default are missing, the defaults are 1 and NULL, respectively.
N must be a literal nonnegative integer. If N is 0, expr is evaluated for the current row.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”. null_treatment is as described in the section introduction.
For an example, see the LAG() function description.
NTH_VALUE(expr, N) [from_first_last] [null_treatment] over_clause
Returns the value of expr from the N-th row of the window frame. If there is no such row, the return value is NULL.
N must be a literal positive integer.
from_first_last is part of the SQL standard, but the MySQL implementation permits only FROM FIRST (which is also the default). This means that calculations begin at the first row of the window. FROM LAST is parsed, but produces an error. To obtain the same effect as FROM LAST (begin calculations at the last row of the window), use ORDER BY to sort in reverse order.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”. null_treatment is as described in the section introduction.
For an example, see the FIRST_VALUE() function description.
NTILE(N) over_clause
Divides a partition into N groups (buckets), assigns each row in the partition its bucket number, and returns the bucket number of the current row within its partition. For example, if N is 4, NTILE() divides rows into four buckets. If N is 100, NTILE() divides rows into 100 buckets.
N must be a literal positive integer. Bucket number return values range from 1 to N.
This function should be used with ORDER BY to sort partition rows into the desired order.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
The following query shows, for the set of values in the val column, the percentile values resulting from dividing the rows into two or four groups. For reference, the query also displays row numbers using ROW_NUMBER():
```
mysql> SELECT
         val,
         ROW_NUMBER() OVER w AS 'row_number',
         NTILE(2)     OVER w AS 'ntile2',
         NTILE(4)     OVER w AS 'ntile4'
       FROM numbers
       WINDOW w AS (ORDER BY val);
+------+------------+--------+--------+
| val  | row_number | ntile2 | ntile4 |
+------+------------+--------+--------+
|    1 |          1 |      1 |      1 |
|    1 |          2 |      1 |      1 |
|    2 |          3 |      1 |      1 |
|    3 |          4 |      1 |      2 |
|    3 |          5 |      1 |      2 |
|    3 |          6 |      2 |      3 |
|    4 |          7 |      2 |      3 |
|    4 |          8 |      2 |      4 |
|    5 |          9 |      2 |      4 |
+------+------------+--------+--------+
```
PERCENT_RANK() over_clause
Returns the the percentage of partition values less than the value in the current row, excluding the highest value. Return values range from 0 to 1 and represent the row relative rank, calculated as the result of this formula, where rank is the row rank and rows is the number of partition rows:
```
(rank - 1) / (rows - 1)
```
This function should be used with ORDER BY to sort partition rows into the desired order. Without ORDER BY, all rows are peers.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
For an example, see the CUME_DIST() function description.
RANK() over_clause
Returns the rank of the current row within its partition, with gaps. Peers are considered ties and receive the same rank. This function does not assign consecutive ranks to peer groups if groups of size greater than one exist; the result is noncontiguous rank numbers.
This function should be used with ORDER BY to sort partition rows into the desired order. Without ORDER BY, all rows are peers.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.
The following query shows the difference between RANK(), which produces ranks with gaps, and DENSE_RANK(), which produces ranks without gaps. The query shows rank values for each member of a set of values in the val column, which contains some duplicates. RANK() assigns peers (the duplicates) the same rank value, and the next greater value has a rank higher by the number of peers minus one. DENSE_RANK() also assigns peers the same rank value, but the next higher value has a rank one greater. For reference, the query also displays row numbers using ROW_NUMBER():
```
mysql> SELECT
         val,
         ROW_NUMBER() OVER w AS 'row_number',
         RANK()       OVER w AS 'rank',
         DENSE_RANK() OVER w AS 'dense_rank'
       FROM numbers
       WINDOW w AS (ORDER BY val);
+------+------------+------+------------+
| val  | row_number | rank | dense_rank |
+------+------------+------+------------+
|    1 |          1 |    1 |          1 |
|    1 |          2 |    1 |          1 |
|    2 |          3 |    3 |          2 |
|    3 |          4 |    4 |          3 |
|    3 |          5 |    4 |          3 |
|    3 |          6 |    4 |          3 |
|    4 |          7 |    7 |          4 |
|    4 |          8 |    7 |          4 |
|    5 |          9 |    9 |          5 |
+------+------------+------+------------+
```
ROW_NUMBER() over_clause
Returns the number of the current row within its partition. Rows numbers range from 1 to the number of partition rows.
ORDER BY affects the order in which rows are numbered. Without ORDER BY, row numbering is nondeterministic.
ROW_NUMBER() assigns peers different row numbers. To assign peers the same value, use RANK() or DENSE_RANK(). For an example, see the RANK() function description.
over_clause is as described in Section 12.20.2, “Window Function Concepts and Syntax”.

12.20.2 Window Function Concepts and Syntax

This section describes how to use window functions. Examples use the same sales information data set as found in the discussion of the GROUPING() function in Section 12.19.2, “GROUP BY Modifiers”:

mysql> SELECT * FROM sales ORDER BY country, year, product;
+------+---------+------------+--------+
| year | country | product    | profit |
+------+---------+------------+--------+
| 2000 | Finland | Computer   |   1500 |
| 2000 | Finland | Phone      |    100 |
| 2001 | Finland | Phone      |     10 |
| 2000 | India   | Calculator |     75 |
| 2000 | India   | Calculator |     75 |
| 2000 | India   | Computer   |   1200 |
| 2000 | USA     | Calculator |     75 |
| 2000 | USA     | Computer   |   1500 |
| 2001 | USA     | Calculator |     50 |
| 2001 | USA     | Computer   |   1500 |
| 2001 | USA     | Computer   |   1200 |
| 2001 | USA     | TV         |    150 |
| 2001 | USA     | TV         |    100 |
+------+---------+------------+--------+

A window function performs an aggregate-like operation on a set of query rows. However, whereas an aggregate operation groups query rows into a single result row, a window function produces a result for each query row:

The row for which function evaluation occurs is called the current row.
The query rows related to the current row over which function evaluation occurs comprise the window for the current row.

For example, using the sales information table, these two queries perform aggregate operations that produce a single global sum for all rows taken as a group, and sums grouped per country:

mysql> SELECT SUM(profit) AS total_profit
       FROM sales;
+--------------+
| total_profit |
+--------------+
|         7535 |
+--------------+
mysql> SELECT country, SUM(profit) AS country_profit
       FROM sales
       GROUP BY country
       ORDER BY country;
+---------+----------------+
| country | country_profit |
+---------+----------------+
| Finland |           1610 |
| India   |           1350 |
| USA     |           4575 |
+---------+----------------+

By contrast, window operations do not collapse groups of query rows to a single output row. Instead, they produce a result for each row. Like the preceding queries, the following query uses SUM(), but this time as a window function:

mysql> SELECT
         year, country, product, profit,
         SUM(profit) OVER() AS total_profit,
         SUM(profit) OVER(PARTITION BY country) AS country_profit
       FROM sales
       ORDER BY country, year, product, profit;
+------+---------+------------+--------+--------------+----------------+
| year | country | product    | profit | total_profit | country_profit |
+------+---------+------------+--------+--------------+----------------+
| 2000 | Finland | Computer   |   1500 |         7535 |           1610 |
| 2000 | Finland | Phone      |    100 |         7535 |           1610 |
| 2001 | Finland | Phone      |     10 |         7535 |           1610 |
| 2000 | India   | Calculator |     75 |         7535 |           1350 |
| 2000 | India   | Calculator |     75 |         7535 |           1350 |
| 2000 | India   | Computer   |   1200 |         7535 |           1350 |
| 2000 | USA     | Calculator |     75 |         7535 |           4575 |
| 2000 | USA     | Computer   |   1500 |         7535 |           4575 |
| 2001 | USA     | Calculator |     50 |         7535 |           4575 |
| 2001 | USA     | Computer   |   1200 |         7535 |           4575 |
| 2001 | USA     | Computer   |   1500 |         7535 |           4575 |
| 2001 | USA     | TV         |    100 |         7535 |           4575 |
| 2001 | USA     | TV         |    150 |         7535 |           4575 |
+------+---------+------------+--------+--------------+----------------+

Each window operation in the query is signified by inclusion of an OVER clause that specifies how to partition query rows into groups for processing by the window function:

The first OVER clause is empty, which treats the entire set of query rows as a single partition. The window function thus produces a global sum, but does so for each row.
The second OVER clause partitions rows by country, producing a sum per partition (per country). The function produces this sum for each partition row.

Window functions are permitted only in the select list and ORDER BY clause. Query result rows are determined from the FROM clause, after WHERE, GROUP BY, and HAVING processing, and windowing execution occurs before ORDER BY, LIMIT, and SELECT DISTINCT.

The OVER clause is permitted for many aggregate functions, which therefore can be used as window or nonwindow functions, depending on whether the OVER clause is present or absent:

AVG()
BIT_AND()
BIT_OR()
BIT_XOR()
COUNT()
MAX()
MIN()
STDDEV_POP(), STDDEV(), STD()
STDDEV_SAMP()
SUM()
VAR_POP(), VARIANCE()
VAR_SAMP()

For details about each aggregate function, see Section 12.19.1, “Aggregate (GROUP BY) Function Descriptions”.

MySQL also supports nonaggregate functions that are used only as window functions. For these, the OVER clause is mandatory:

CUME_DIST()
DENSE_RANK()
FIRST_VALUE()
LAG()
LAST_VALUE()
LEAD()
NTH_VALUE()
NTILE()
PERCENT_RANK()
RANK()
ROW_NUMBER()

For details about each nonaggregate function, see Section 12.20.1, “Window Function Descriptions”.

As an example of one of those nonaggregate window functions, this query uses ROW_NUMBER(), which produces the row number of each row within its partition. In this case, rows are numbered per country. By default, partition rows are unordered and row numbering is nondeterministic. To sort partition rows, include an ORDER BY clause within the window definition. The query uses unordered and ordered partitions (the row_num1 and row_num2 columns) to illustrate the difference between omitting and including ORDER BY:

mysql> SELECT
         year, country, product, profit,
         ROW_NUMBER() OVER(PARTITION BY country) AS row_num1,
         ROW_NUMBER() OVER(PARTITION BY country ORDER BY year, product) AS row_num2
       FROM sales;
+------+---------+------------+--------+----------+----------+
| year | country | product    | profit | row_num1 | row_num2 |
+------+---------+------------+--------+----------+----------+
| 2000 | Finland | Computer   |   1500 |        2 |        1 |
| 2000 | Finland | Phone      |    100 |        1 |        2 |
| 2001 | Finland | Phone      |     10 |        3 |        3 |
| 2000 | India   | Calculator |     75 |        2 |        1 |
| 2000 | India   | Calculator |     75 |        3 |        2 |
| 2000 | India   | Computer   |   1200 |        1 |        3 |
| 2000 | USA     | Calculator |     75 |        5 |        1 |
| 2000 | USA     | Computer   |   1500 |        4 |        2 |
| 2001 | USA     | Calculator |     50 |        2 |        3 |
| 2001 | USA     | Computer   |   1500 |        3 |        4 |
| 2001 | USA     | Computer   |   1200 |        7 |        5 |
| 2001 | USA     | TV         |    150 |        1 |        6 |
| 2001 | USA     | TV         |    100 |        6 |        7 |
+------+---------+------------+--------+----------+----------+

As mentioned previously, to use a window function (or treat an aggregate function as a window function), include an OVER clause following the function call. The OVER clause has two forms:

over_clause:
    {OVER (window_spec) | OVER window_name}

Both forms define how the window function should process query rows. They differ in whether the window is defined directly in the OVER clause, or supplied by a reference to a named window defined elsewhere in the query:

In the first case, the window specification appears directly in the OVER clause, between the parentheses.
In the second case, window_name is the name for a window specification defined by a WINDOW clause elsewhere in the query. For details, see Section 12.20.4, “Named Windows”.

For OVER (window_spec) syntax, the window specification has several parts, all optional:

window_spec:
    [window_name] [partition_clause] [order_clause] [frame_clause]

If OVER() is empty, the window consists of all query rows and the window function computes a result using all rows. Otherwise, the clauses present within the parentheses determine which query rows are used to compute the function result and how they are partitioned and ordered:

window_name: The name of a window defined by a WINDOW clause elsewhere in the query. If window_name appears by itself within the OVER clause, it completely defines the window. If partitioning, ordering, or framing clauses are also given, they modify interpretation of the named window. For details, see Section 12.20.4, “Named Windows”.
partition_clause: A PARTITION BY clause indicates how to divide the query rows into groups. The window function result for a given row is based on the rows of the partition that contains the row. If PARTITION BY is omitted, there is a single partition consisting of all query rows.

Note

Partitioning for window functions differs from table partitioning. For information about table partitioning, see Chapter 22, Partitioning.

partition_clause has this syntax:
```
partition_clause:
    PARTITION BY expr [, expr] ...
```
Standard SQL requires PARTITION BY to be followed by column names only. A MySQL extension is to permit expressions, not just column names. For example, if a table contains a TIMESTAMP column named ts, standard SQL permits PARTITION BY ts but not PARTITION BY HOUR(ts), whereas MySQL permits both.
order_clause: An ORDER BY clause indicates how to sort rows in each partition. Partition rows that are equal according to the ORDER BY clause are considered peers. If ORDER BY is omitted, partition rows are unordered, with no processing order implied, and all partition rows are peers.
order_clause has this syntax:
```
order_clause:
    ORDER BY expr [ASC|DESC] [, expr [ASC|DESC]] ...
```
Each ORDER BY expression optionally can be followed by ASC or DESC to indicate sort direction. The default is ASC if no direction is specified. NULL values sort first for ascending sorts, last for descending sorts.
An ORDER BY in a window definition applies within individual partitions. To sort the result set as a whole, include an ORDER BY at the query top level.
frame_clause: A frame is a subset of the current partition and the frame clause specifies how to define the subset. The frame clause has many subclauses of its own. For details, see Section 12.20.3, “Window Function Frame Specification”.

12.20.3 Window Function Frame Specification

The definition of a window used with a window function can include a frame clause. A frame is a subset of the current partition and the frame clause specifies how to define the subset.

Frames are determined with respect to the current row, which enables a frame to move within a partition depending on the location of the current row within its partition. Examples:

By defining a frame to be all rows from the partition start to the current row, you can compute running totals for each row.
By defining a frame as extending N rows on either side of the current row, you can compute rolling averages.

The following query demonstrates the use of moving frames to compute running totals within each group of time-ordered level values, as well as rolling averages computed from the current row and the rows that immediately precede and follow it:

mysql> SELECT
         time, subject, val,
         SUM(val) OVER (PARTITION BY subject ORDER BY time
                        ROWS UNBOUNDED PRECEDING)
           AS running_total,
         AVG(val) OVER (PARTITION BY subject ORDER BY time
                        ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING)
           AS running_average
       FROM observations;
+----------+---------+------+---------------+-----------------+
| time     | subject | val  | running_total | running_average |
+----------+---------+------+---------------+-----------------+
| 07:00:00 | st113   |   10 |            10 |          9.5000 |
| 07:15:00 | st113   |    9 |            19 |         14.6667 |
| 07:30:00 | st113   |   25 |            44 |         18.0000 |
| 07:45:00 | st113   |   20 |            64 |         22.5000 |
| 07:00:00 | xh458   |    0 |             0 |          5.0000 |
| 07:15:00 | xh458   |   10 |            10 |          5.0000 |
| 07:30:00 | xh458   |    5 |            15 |         15.0000 |
| 07:45:00 | xh458   |   30 |            45 |         20.0000 |
| 08:00:00 | xh458   |   25 |            70 |         27.5000 |
+----------+---------+------+---------------+-----------------+

For the running_average column, there is no frame row preceding the first one or following the last. In these cases, AVG() computes the average of the rows that are available.

Aggregate functions used as window functions operate on rows in the current row frame, as do these nonaggregate window functions:

FIRST_VALUE()
LAST_VALUE()
NTH_VALUE()

Standard SQL specifies that window functions that operate on the entire partition should have no frame clause. MySQL permits a frame clause for such functions but ignores it. These functions use the entire partition even if a frame is specified:

CUME_DIST()
DENSE_RANK()
LAG()
LEAD()
NTILE()
PERCENT_RANK()
RANK()
ROW_NUMBER()

The frame clause, if given, has this syntax:

frame_clause:
    frame_units frame_extent

frame_units:
    {ROWS | RANGE}

In the absence of a frame clause, the default frame depends on whether an ORDER BY clause is present, as described later in this section.

The frame_units value indicates the type of relationship between the current row and frame rows:

ROWS: The frame is defined by beginning and ending row positions. Offsets are differences in row numbers from the current row number.
RANGE: The frame is defined by rows within a value range. Offsets are differences in row values from the current row value.

The frame_extent value indicates the start and end points of the frame. You can specify just the start of the frame (in which case the current row is implicitly the end) or use BETWEEN to specify both frame endpoints:

frame_extent:
    {frame_start | frame_between}

frame_between:
    BETWEEN frame_start AND frame_end

frame_start, frame_end: {
    CURRENT ROW
  | UNBOUNDED PRECEDING
  | UNBOUNDED FOLLOWING
  | expr PRECEDING
  | expr FOLLOWING
}

With BETWEEN syntax, frame_start must not occur later than frame_end.

The permitted frame_start and frame_end values have these meanings:

CURRENT ROW: For ROWS, the bound is the current row. For RANGE, the bound is the peers of the current row.
UNBOUNDED PRECEDING: The bound is the first partition row.
UNBOUNDED FOLLOWING: The bound is the last partition row.
expr PRECEDING: For ROWS, the bound is expr rows before the current row. For RANGE, the bound is the rows with values equal to the current row value minus expr; if the current row value is NULL, the bound is the peers of the row.
For expr PRECEDING (and expr FOLLOWING), expr can be a ? parameter marker (for use in a prepared statement), a nonnegative numeric literal, or a temporal interval of the form INTERVAL val unit. For INTERVAL expressions, val specifies nonnegative interval value, and unit is a keyword indicating the units in which the value should be interpreted. (For details about the permitted units specifiers, see the description of the DATE_ADD() function in Section 12.7, “Date and Time Functions”.)
RANGE on a numeric or temporal expr requires ORDER BY on a numeric or temporal expression, respectively.
Examples of valid expr PRECEDING and expr FOLLOWING indicators:
```
10 PRECEDING
INTERVAL 5 DAY PRECEDING
5 FOLLOWING
INTERVAL '2:30' MINUTE_SECOND FOLLOWING
```
expr FOLLOWING: For ROWS, the bound is expr rows after the current row. For RANGE, the bound is the rows with values equal to the current row value plus expr; if the current row value is NULL, the bound is the peers of the row.
For permitted values of expr, see the description of expr PRECEDING.

The following query demonstrates FIRST_VALUE(), LAST_VALUE(), and two instances of NTH_VALUE():

mysql> SELECT
         time, subject, val,
         FIRST_VALUE(val)  OVER w AS 'first',
         LAST_VALUE(val)   OVER w AS 'last',
         NTH_VALUE(val, 2) OVER w AS 'second',
         NTH_VALUE(val, 4) OVER w AS 'fourth'
       FROM observations
       WINDOW w AS (PARTITION BY subject ORDER BY time
                    ROWS UNBOUNDED PRECEDING);
+----------+---------+------+-------+------+--------+--------+
| time     | subject | val  | first | last | second | fourth |
+----------+---------+------+-------+------+--------+--------+
| 07:00:00 | st113   |   10 |    10 |   10 |   NULL |   NULL |
| 07:15:00 | st113   |    9 |    10 |    9 |      9 |   NULL |
| 07:30:00 | st113   |   25 |    10 |   25 |      9 |   NULL |
| 07:45:00 | st113   |   20 |    10 |   20 |      9 |     20 |
| 07:00:00 | xh458   |    0 |     0 |    0 |   NULL |   NULL |
| 07:15:00 | xh458   |   10 |     0 |   10 |     10 |   NULL |
| 07:30:00 | xh458   |    5 |     0 |    5 |     10 |   NULL |
| 07:45:00 | xh458   |   30 |     0 |   30 |     10 |     30 |
| 08:00:00 | xh458   |   25 |     0 |   25 |     10 |     30 |
+----------+---------+------+-------+------+--------+--------+

In the absence of a frame clause, the default frame depends on whether an ORDER BY clause is present:

With ORDER BY: The default frame includes rows from the partition start through the current row, including all peers of the current row (rows equal to the current row according to the ORDER BY clause). The default is equivalent to this frame specification:
```
RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
```
Without ORDER BY: The default frame includes all partition rows (because, without ORDER BY, all partition rows are peers). The default is equivalent to this frame specification:
```
RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING
```

Because the default frame differs depending on presence or absence of ORDER BY, adding ORDER BY to a query to get deterministic results may change the results. (For example, the values produced by SUM() might change.) To obtain the same results but ordered per ORDER BY, provide an explicit frame specification to be used regardless of whether ORDER BY is present.

The meaning of a frame specification can be nonobvious when the current row value is NULL. Assuming that to be the case, these examples illustrate how various frame specifications apply:

ORDER BY X ASC RANGE BETWEEN 10 FOLLOWING AND 15 FOLLOWING
The frame starts at NULL and stops at NULL, thus includes only rows with value NULL.
ORDER BY X ASC RANGE BETWEEN 10 FOLLOWING AND UNBOUNDED FOLLOWING
The frame starts at NULL and stops at the end of the partition. Because an ASC sort puts NULL values first, the frame is the entire partition.
ORDER BY X DESC RANGE BETWEEN 10 FOLLOWING AND UNBOUNDED FOLLOWING
The frame starts at NULL and stops at the end of the partition. Because a DESC sort puts NULL values last, the frame is only the NULL values.
ORDER BY X ASC RANGE BETWEEN 10 PRECEDING AND UNBOUNDED FOLLOWING
The frame starts at NULL and stops at the end of the partition. Because an ASC sort puts NULL values first, the frame is the entire partition.
ORDER BY X ASC RANGE BETWEEN 10 PRECEDING AND 10 FOLLOWING
The frame starts at NULL and stops at NULL, thus includes only rows with value NULL.
ORDER BY X ASC RANGE BETWEEN 10 PRECEDING AND 1 PRECEDING
The frame starts at NULL and stops at NULL, thus includes only rows with value NULL.
ORDER BY X ASC RANGE BETWEEN UNBOUNDED PRECEDING AND 10 FOLLOWING
The frame starts at the beginning of the partition and stops at rows with value NULL. Because an ASC sort puts NULL values first, the frame is only the NULL values.

12.20.4 Named Windows

Windows can be defined and given names by which to refer to them in OVER clauses. To do this, use a WINDOW clause. If present in a query, the WINDOW clause falls between the positions of the HAVING and ORDER BY clauses, and has this syntax:

WINDOW window_name AS (window_spec)
    [, window_name AS (window_spec)] ...

For each window definition, window_name is the window name, and window_spec is the same type of window specification as given between the parentheses of an OVER clause, as described in Section 12.20.2, “Window Function Concepts and Syntax”:

window_spec:
    [window_name] [partition_clause] [order_clause] [frame_clause]

A WINDOW clause is useful for queries in which multiple OVER clauses would otherwise define the same window. Instead, you can define the window once, give it a name, and refer to the name in the OVER clauses. Consider this query, which defines the same window multiple times:

SELECT
  val,
  ROW_NUMBER() OVER (ORDER BY val) AS 'row_number',
  RANK()       OVER (ORDER BY val) AS 'rank',
  DENSE_RANK() OVER (ORDER BY val) AS 'dense_rank'
FROM numbers;

The query can be written more simply by using WINDOW to define the window once and referring to the window by name in the OVER clauses:

SELECT
  val,
  ROW_NUMBER() OVER w AS 'row_number',
  RANK()       OVER w AS 'rank',
  DENSE_RANK() OVER w AS 'dense_rank'
FROM numbers
WINDOW w AS (ORDER BY val);

A named window also makes it easier to experiment with the window definition to see the effect on query results. You need only modify the window definition in the WINDOW clause, rather than multiple OVER clause definitions.

If an OVER clause uses OVER (window_name ...) rather than OVER window_name, the named window can be modified by the addition of other clauses. For example, this query defines a window that includes partitioning, and uses ORDER BY in the OVER clauses to modify the window in different ways:

SELECT
  DISTINCT year, country,
  FIRST_VALUE(year) OVER (w ORDER BY year ASC) AS first,
  FIRST_VALUE(year) OVER (w ORDER BY year DESC) AS last
FROM sales
WINDOW w AS (PARTITION BY country);

An OVER clause can only add properties to a named window, not modify them. If the named window definition includes a partitioning, ordering, or framing property, the OVER clause that refers to the window name cannot also include the same kind of property or an error occurs:

This construct is permitted because the window definition and the referring OVER clause do not contain the same kind of properties:
```
OVER (w ORDER BY country)
... WINDOW w AS (PARTITION BY country)
```
This construct is not permitted because the OVER clause specifies PARTITION BY for a named window that already has PARTITION BY:
```
OVER (w PARTITION BY year)
... WINDOW w AS (PARTITION BY country)
```

The definition of a named window can itself begin with a window_name. In such cases, forward and backward references are permitted, but not cycles:

This is permitted; it contains forward and backward references but no cycles:
```
WINDOW w1 AS (w2), w2 AS (), w3 AS (w1)
```
This is not permitted because it contains a cycle:
```
WINDOW w1 AS (w2), w2 AS (w3), w3 AS (w1)
```

12.20.5 Window Function Restrictions

The SQL standard imposes a constraint on window functions that they cannot be used in UPDATE or DELETE statements to update rows. Using such functions in a subquery of these statements (to select rows) is permitted.

MySQL does not support these window function features:

DISTINCT syntax for aggregate window functions.
Nested window functions.
Dynamic frame endpoints that depend on the value of the current row.

The parser recognizes these window constructs which nevertheless are not supported:

The GROUPS frame units specifier is parsed, but produces an error. Only ROWS and RANGE are supported.
The EXCLUDE clause for frame specification is parsed, but produces an error.
IGNORE NULLS is parsed, but produces an error. Only RESPECT NULLS is supported.
FROM LAST is parsed, but produces an error. Only FROM FIRST is supported.

12.21 Internal Functions

Table 12.27 Internal Functions

Name	Description
`CAN_ACCESS_COLUMN()`	Internal use only
`CAN_ACCESS_DATABASE()`	Internal use only
`CAN_ACCESS_TABLE()`	Internal use only
`CAN_ACCESS_VIEW()`	Internal use only
`GET_DD_COLUMN_PRIVILEGES()`	Internal use only
`GET_DD_CREATE_OPTIONS()`	Internal use only
`GET_DD_INDEX_SUB_PART_LENGTH()`	Internal use only
`INTERNAL_AUTO_INCREMENT()`	Internal use only
`INTERNAL_AVG_ROW_LENGTH()`	Internal use only
`INTERNAL_CHECK_TIME()`	Internal use only
`INTERNAL_CHECKSUM()`	Internal use only
`INTERNAL_DATA_FREE()`	Internal use only
`INTERNAL_DATA_LENGTH()`	Internal use only
`INTERNAL_DD_CHAR_LENGTH()`	Internal use only
`INTERNAL_GET_COMMENT_OR_ERROR()`	Internal use only
`INTERNAL_GET_VIEW_WARNING_OR_ERROR()`	Internal use only
`INTERNAL_INDEX_COLUMN_CARDINALITY()`	Internal use only
`INTERNAL_INDEX_LENGTH()`	Internal use only
`INTERNAL_KEYS_DISABLED()`	Internal use only
`INTERNAL_MAX_DATA_LENGTH()`	Internal use only
`INTERNAL_TABLE_ROWS()`	Internal use only
`INTERNAL_UPDATE_TIME()`	Internal use only

The functions listed in this section are intended only for internal use by the server. Attempts by users to invoke them result in an error.

12.22 Miscellaneous Functions

Table 12.28 Miscellaneous Functions

Name	Description
`ANY_VALUE()`	Suppress ONLY_FULL_GROUP_BY value rejection
`BIN_TO_UUID()`	Convert binary UUID to string
`DEFAULT()`	Return the default value for a table column
`GET_LOCK()`	Get a named lock
`GROUPING()`	Distinguish super-aggregate ROLLUP rows from regular rows
`INET_ATON()`	Return the numeric value of an IP address
`INET_NTOA()`	Return the IP address from a numeric value
`INET6_ATON()`	Return the numeric value of an IPv6 address
`INET6_NTOA()`	Return the IPv6 address from a numeric value
`IS_FREE_LOCK()`	Whether the named lock is free
`IS_IPV4()`	Whether argument is an IPv4 address
`IS_IPV4_COMPAT()`	Whether argument is an IPv4-compatible address
`IS_IPV4_MAPPED()`	Whether argument is an IPv4-mapped address
`IS_IPV6()`	Whether argument is an IPv6 address
`IS_USED_LOCK()`	Whether the named lock is in use; return connection identifier if true
`IS_UUID()`	Whether argument is a valid UUID
`MASTER_POS_WAIT()`	Block until the slave has read and applied all updates up to the specified position
`NAME_CONST()`	Causes the column to have the given name
`RAND()`	Return a random floating-point value
`RELEASE_ALL_LOCKS()`	Releases all current named locks
`RELEASE_LOCK()`	Releases the named lock
`SLEEP()`	Sleep for a number of seconds
`UUID()`	Return a Universal Unique Identifier (UUID)
`UUID_SHORT()`	Return an integer-valued universal identifier
`UUID_TO_BIN()`	Convert string UUID to binary
`VALUES()`	Defines the values to be used during an INSERT

ANY_VALUE(arg)
This function is useful for GROUP BY queries when the ONLY_FULL_GROUP_BY SQL mode is enabled, for cases when MySQL rejects a query that you know is valid for reasons that MySQL cannot determine. The function return value and type are the same as the return value and type of its argument, but the function result is not checked for the ONLY_FULL_GROUP_BY SQL mode.
For example, if name is a nonindexed column, the following query fails with ONLY_FULL_GROUP_BY enabled:
```
mysql> SELECT name, address, MAX(age) FROM t GROUP BY name;
ERROR 1055 (42000): Expression #2 of SELECT list is not in GROUP
BY clause and contains nonaggregated column 'mydb.t.address' which
is not functionally dependent on columns in GROUP BY clause; this
is incompatible with sql_mode=only_full_group_by
```
The failure occurs because address is a nonaggregated column that is neither named among GROUP BY columns nor functionally dependent on them. As a result, the address value for rows within each name group is nondeterministic. There are multiple ways to cause MySQL to accept the query:
- Alter the table to make name a primary key or a unique NOT NULL column. This enables MySQL to determine that address is functionally dependent on name; that is, address is uniquely determined by name. (This technique is inapplicable if NULL must be permitted as a valid name value.)
- Use ANY_VALUE() to refer to address:
```
SELECT name, ANY_VALUE(address), MAX(age) FROM t GROUP BY name;
```
  In this case, MySQL ignores the nondeterminism of address values within each name group and accepts the query. This may be useful if you simply do not care which value of a nonaggregated column is chosen for each group. ANY_VALUE() is not an aggregate function, unlike functions such as SUM() or COUNT(). It simply acts to suppress the test for nondeterminism.
- Disable ONLY_FULL_GROUP_BY. This is equivalent to using ANY_VALUE() with ONLY_FULL_GROUP_BY enabled, as described in the previous item.
ANY_VALUE() is also useful if functional dependence exists between columns but MySQL cannot determine it. The following query is valid because age is functionally dependent on the grouping column age-1, but MySQL cannot tell that and rejects the query with ONLY_FULL_GROUP_BY enabled:
```
SELECT age FROM t GROUP BY age-1;
```
To cause MySQL to accept the query, use ANY_VALUE():
```
SELECT ANY_VALUE(age) FROM t GROUP BY age-1;
```
ANY_VALUE() can be used for queries that refer to aggregate functions in the absence of a GROUP BY clause:
```
mysql> SELECT name, MAX(age) FROM t;
ERROR 1140 (42000): In aggregated query without GROUP BY, expression
#1 of SELECT list contains nonaggregated column 'mydb.t.name'; this
is incompatible with sql_mode=only_full_group_by
```
Without GROUP BY, there is a single group and it is nondeterministic which name value to choose for the group. ANY_VALUE() tells MySQL to accept the query:
```
SELECT ANY_VALUE(name), MAX(age) FROM t;
```
It may be that, due to some property of a given data set, you know that a selected nonaggregated column is effectively functionally dependent on a GROUP BY column. For example, an application may enforce uniqueness of one column with respect to another. In this case, using ANY_VALUE() for the effectively functionally dependent column may make sense.
For additional discussion, see Section 12.19.3, “MySQL Handling of GROUP BY”.
BIN_TO_UUID(binary_uuid), BIN_TO_UUID(binary_uuid, swap_flag)
BIN_TO_UUID() is the inverse of UUID_TO_BIN(). It converts a binary UUID to a string UUID and returns the result. The binary value should be a UUID as a VARBINARY(16) value. The return value is a utf8 string of five hexadecimal numbers separated by dashes. (For details about this format, see the UUID() function description.) If the UUID argument is NULL, the return value is NULL. If any argument is invalid, an error occurs.
BIN_TO_UUID() takes one or two arguments:
- The one-argument form takes a binary UUID value. The UUID value is assumed not to have its time-low and time-high parts swapped. The string result is in the same order as the binary argument.
- The two-argument form takes a binary UUID value and a swap-flag value:
  - If swap_flag is 0, the two-argument form is equivalent to the one-argument form. The string result is in the same order as the binary argument.
  - If swap_flag is 1, the UUID value is assumed to have its time-low and time-high parts swapped. These parts are swapped back to their original position in the result value.
For usage examples and information about time-part swapping, see the UUID_TO_BIN() function description.
DEFAULT(col_name)
Returns the default value for a table column. An error results if the column has no default value.
```
mysql> UPDATE t SET i = DEFAULT(i)+1 WHERE id < 100;
```
FORMAT(X,D)
Formats the number X to a format like '#,###,###.##', rounded to D decimal places, and returns the result as a string. For details, see Section 12.5, “String Functions”.
GET_LOCK(str,timeout)
Tries to obtain a lock with a name given by the string str, using a timeout of timeout seconds. A negative timeout value means infinite timeout. The lock is exclusive. While held by one session, other sessions cannot obtain a lock of the same name.
Returns 1 if the lock was obtained successfully, 0 if the attempt timed out (for example, because another client has previously locked the name), or NULL if an error occurred (such as running out of memory or the thread was killed with mysqladmin kill).
A lock obtained with GET_LOCK() is released explicitly by executing RELEASE_LOCK() or implicitly when your session terminates (either normally or abnormally). Lock release may also occur with another call to GET_LOCK():
- GET_LOCK() is implemented using the metadata locking (MDL) subsystem. Multiple simultaneous locks can be acquired and GET_LOCK() does not release any existing locks. It is even possible for a given session to acquire multiple locks for the same name. Other sessions cannot acquire a lock with that name until the acquiring session releases all its locks for the name.
  Locks acquired with GET_LOCK() appear in the Performance Schema metadata_locks table. The OBJECT_TYPE column says USER LEVEL LOCK and the OBJECT_NAME column indicates the lock name. Also, the capability of acquiring multiple locks introduces the possibility of deadlock among clients. When this happens, the server chooses a caller and terminates its lock-acquisition request with an ER_USER_LOCK_DEADLOCK error. This error does not cause transactions to roll back.
For example, suppose that you execute these statements:
```
SELECT GET_LOCK('lock1',10);
SELECT GET_LOCK('lock2',10);
SELECT RELEASE_LOCK('lock2');
SELECT RELEASE_LOCK('lock1');
```
The second GET_LOCK() acquires a second lock and both RELEASE_LOCK() calls return 1 (success).
MySQL enforces a maximum length on lock names of 64 characters.
Locks obtained with GET_LOCK() are not released when transactions commit or roll back.
GET_LOCK() can be used to implement application locks or to simulate record locks. Names are locked on a server-wide basis. If a name has been locked within one session, GET_LOCK() blocks any request by another session for a lock with the same name. This enables clients that agree on a given lock name to use the name to perform cooperative advisory locking. But be aware that it also enables a client that is not among the set of cooperating clients to lock a name, either inadvertently or deliberately, and thus prevent any of the cooperating clients from locking that name. One way to reduce the likelihood of this is to use lock names that are database-specific or application-specific. For example, use lock names of the form db_name.str or app_name.str.
If multiple clients are waiting for a lock, the order in which they will acquire it is undefined. Applications should not assume that clients will acquire the lock in the same order that they issued the lock requests.
GET_LOCK() is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
Caution

With the capability of acquiring multiple named locks in MySQL 5.7.5, it is possible for a single statement to acquire a large number of locks. For example:
```
INSERT INTO ... SELECT GET_LOCK(t1.col_name) FROM t1;
```
These types of statements may have certain adverse effects. For example, if the statement fails part way through and rolls back, locks acquired up to the point of failure will still exist. If the intent is for there to be a correspondence between rows inserted and locks acquired, that intent will not be satisfied. Also, if it is important that locks are granted in a certain order, be aware that result set order may differ depending on which execution plan the optimizer chooses. For these reasons, it may be best to limit applications to a single lock-acquisition call per statement.
A different locking interface is available as either a plugin service or a set of user-defined functions. This interface provides lock namespaces and distinct read and write locks, unlike the interface provided by GET_LOCK() and related functions. For details, see Section 28.3.1, “The Locking Service”.

GROUPING(expr [, expr] ...)

For GROUP BY queries that include a WITH ROLLUP modifier, the ROLLUP operation produces super-aggregate output rows where NULL represents the set of all values. The GROUPING() function enables you to distinguish NULL values for super-aggregate rows from NULL values in regular grouped rows.

GROUPING() is permitted only in the select list or HAVING clause.

Each argument to GROUPING() must be an expression that exactly matches an expression in the GROUP BY clause. The expression cannot be a positional specifier. For each expression, GROUPING() produces 1 if the expression value in the current row is a NULL representing a super-aggregate value. Otherwise, GROUPING() produces 0, indicating that the expression value is a NULL for a regular result row or is not NULL.

Suppose that table t1 contains these rows, where NULL indicates something like “other” or “unknown”:

mysql> SELECT * FROM t1;
+------+-------+----------+
| name | size  | quantity |
+------+-------+----------+
| ball | small |       10 |
| ball | large |       20 |
| ball | NULL  |        5 |
| hoop | small |       15 |
| hoop | large |        5 |
| hoop | NULL  |        3 |
+------+-------+----------+

A summary of the table without WITH ROLLUP looks like this:

mysql> SELECT name, size, SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size;
+------+-------+----------+
| name | size  | quantity |
+------+-------+----------+
| ball | small |       10 |
| ball | large |       20 |
| ball | NULL  |        5 |
| hoop | small |       15 |
| hoop | large |        5 |
| hoop | NULL  |        3 |
+------+-------+----------+

The result contains NULL values, but those do not represent super-aggregate rows because the query does not include WITH ROLLUP.

Adding WITH ROLLUP produces super-aggregate summary rows containing additional NULL values. However, without comparing this result to the previous one, it is not easy to see which NULL values occur in super-aggregate rows and which occur in regular grouped rows:

mysql> SELECT name, size, SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size WITH ROLLUP;
+------+-------+----------+
| name | size  | quantity |
+------+-------+----------+
| ball | NULL  |        5 |
| ball | large |       20 |
| ball | small |       10 |
| ball | NULL  |       35 |
| hoop | NULL  |        3 |
| hoop | large |        5 |
| hoop | small |       15 |
| hoop | NULL  |       23 |
| NULL | NULL  |       58 |
+------+-------+----------+

To distinguish NULL values in in super-aggregate rows from those in regular grouped rows, use GROUPING(), which returns 1 only for super-aggregate NULL values:

mysql> SELECT
         name, size, SUM(quantity) AS quantity,
         GROUPING(name) AS grp_name,
         GROUPING(size) AS grp_size
       FROM t1
       GROUP BY name, size WITH ROLLUP;
+------+-------+----------+----------+----------+
| name | size  | quantity | grp_name | grp_size |
+------+-------+----------+----------+----------+
| ball | NULL  |        5 |        0 |        0 |
| ball | large |       20 |        0 |        0 |
| ball | small |       10 |        0 |        0 |
| ball | NULL  |       35 |        0 |        1 |
| hoop | NULL  |        3 |        0 |        0 |
| hoop | large |        5 |        0 |        0 |
| hoop | small |       15 |        0 |        0 |
| hoop | NULL  |       23 |        0 |        1 |
| NULL | NULL  |       58 |        1 |        1 |
+------+-------+----------+----------+----------+

Common uses for GROUPING():

Substitute a label for super-aggregate NULL values:

mysql> SELECT
         IF(GROUPING(name) = 1, 'All items', name) AS name,
         IF(GROUPING(size) = 1, 'All sizes', size) AS size,
         SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size WITH ROLLUP;
+-----------+-----------+----------+
| name      | size      | quantity |
+-----------+-----------+----------+
| ball      | NULL      |        5 |
| ball      | large     |       20 |
| ball      | small     |       10 |
| ball      | All sizes |       35 |
| hoop      | NULL      |        3 |
| hoop      | large     |        5 |
| hoop      | small     |       15 |
| hoop      | All sizes |       23 |
| All items | All sizes |       58 |
+-----------+-----------+----------+

Return only super-aggregate lines by filtering out the regular grouped lines:

mysql> SELECT name, size, SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size WITH ROLLUP
       HAVING GROUPING(name) = 1 OR GROUPING(size) = 1;
+------+------+----------+
| name | size | quantity |
+------+------+----------+
| ball | NULL |       35 |
| hoop | NULL |       23 |
| NULL | NULL |       58 |
+------+------+----------+

GROUPING() permits multiple expression arguments. In this case, the GROUPING() return value represents a bitmask combined from the results for each expression, where the lowest-order bit corresponds to the result for the rightmost expression. For example, with three expression arguments, GROUPING(expr1, expr2, expr3) is evaluated like this:

  result for GROUPING(expr3)
+ result for GROUPING(expr2) << 1
+ result for GROUPING(expr1) << 2

The following query shows how GROUPING() results for single arguments combine for a multiple-argument call to produce a bitmask value:

mysql> SELECT
         name, size, SUM(quantity) AS quantity,
         GROUPING(name) AS grp_name,
         GROUPING(size) AS grp_size,
       GROUPING(name, size) AS grp_all
       FROM t1
       GROUP BY name, size WITH ROLLUP;
+------+-------+----------+----------+----------+---------+
| name | size  | quantity | grp_name | grp_size | grp_all |
+------+-------+----------+----------+----------+---------+
| ball | NULL  |        5 |        0 |        0 |       0 |
| ball | large |       20 |        0 |        0 |       0 |
| ball | small |       10 |        0 |        0 |       0 |
| ball | NULL  |       35 |        0 |        1 |       1 |
| hoop | NULL  |        3 |        0 |        0 |       0 |
| hoop | large |        5 |        0 |        0 |       0 |
| hoop | small |       15 |        0 |        0 |       0 |
| hoop | NULL  |       23 |        0 |        1 |       1 |
| NULL | NULL  |       58 |        1 |        1 |       3 |
+------+-------+----------+----------+----------+---------+

With multiple expression arguments, the GROUPING() return value is nonzero if any expression represents a super-aggregate value. Multiple-argument GROUPING() syntax thus provides a simpler way to write the earlier query that returned only super-aggregate rows, by using a single multiple-argument GROUPING() call rather than multiple single-argument calls:

mysql> SELECT name, size, SUM(quantity) AS quantity
       FROM t1
       GROUP BY name, size WITH ROLLUP
       HAVING GROUPING(name, size) <> 0;
+------+------+----------+
| name | size | quantity |
+------+------+----------+
| ball | NULL |       35 |
| hoop | NULL |       23 |
| NULL | NULL |       58 |
+------+------+----------+

Use of GROUPING() is subject to these limitations:

Do not use subquery GROUP BY expressions as GROUPING() arguments because matching might fail. For example, matching fails for this query:

mysql> SELECT GROUPING((SELECT MAX(name) FROM t1))
       FROM t1
       GROUP BY (SELECT MAX(name) FROM t1) WITH ROLLUP;
ERROR 3580 (HY000): Argument #1 of GROUPING function is not in GROUP BY

GROUP BY literal expressions should not be used within a HAVING clause as GROUPING() arguments. Due to differences between when the optimizer evaluates GROUP BY and HAVING, matching may succeed but GROUPING() evaluation does not produce the expected result. Consider this query:
```
SELECT a AS f1, 'w' AS f2
FROM t
GROUP BY f1, f2 WITH ROLLUP
HAVING GROUPING(f2) = 1;
```
GROUPING() is evaluated earlier for the literal constant expression than for the HAVING clause as a whole and returns 0. To check whether a query such as this is affected, use EXPLAIN and look for Impossible having in the Extra column.

For more information about WITH ROLLUP and GROUPING(), see Section 12.19.2, “GROUP BY Modifiers”.

INET_ATON(expr)
Given the dotted-quad representation of an IPv4 network address as a string, returns an integer that represents the numeric value of the address in network byte order (big endian). INET_ATON() returns NULL if it does not understand its argument.
```
mysql> SELECT INET_ATON('10.0.5.9');
        -> 167773449
```
For this example, the return value is calculated as 10×256³ + 0×256² + 5×256 + 9.
INET_ATON() may or may not return a non-NULL result for short-form IP addresses (such as '127.1' as a representation of '127.0.0.1'). Because of this, INET_ATON()a should not be used for such addresses.

Note

To store values generated by INET_ATON(), use an INT UNSIGNED column rather than INT, which is signed. If you use a signed column, values corresponding to IP addresses for which the first octet is greater than 127 cannot be stored correctly. See Section 11.2.6, “Out-of-Range and Overflow Handling”.
INET_NTOA(expr)
Given a numeric IPv4 network address in network byte order, returns the dotted-quad string representation of the address as a string in the connection character set. INET_NTOA() returns NULL if it does not understand its argument.
```
mysql> SELECT INET_NTOA(167773449);
        -> '10.0.5.9'
```
INET6_ATON(expr)
Given an IPv6 or IPv4 network address as a string, returns a binary string that represents the numeric value of the address in network byte order (big endian). Because numeric-format IPv6 addresses require more bytes than the largest integer type, the representation returned by this function has the VARBINARY data type: VARBINARY(16) for IPv6 addresses and VARBINARY(4) for IPv4 addresses. If the argument is not a valid address, INET6_ATON() returns NULL.
The following examples use HEX() to display the INET6_ATON() result in printable form:
```
mysql> SELECT HEX(INET6_ATON('fdfe::5a55:caff:fefa:9089'));
        -> 'FDFE0000000000005A55CAFFFEFA9089'
mysql> SELECT HEX(INET6_ATON('10.0.5.9'));
        -> '0A000509'
```
INET6_ATON() observes several constraints on valid arguments. These are given in the following list along with examples.
- A trailing zone ID is not permitted, as in fe80::3%1 or fe80::3%eth0.
- A trailing network mask is not permitted, as in 2001:45f:3:ba::/64 or 198.51.100.0/24.
- For values representing IPv4 addresses, only classless addresses are supported. Classful addresses such as 198.51.1 are rejected. A trailing port number is not permitted, as in 198.51.100.2:8080. Hexadecimal numbers in address components are not permitted, as in 198.0xa0.1.2. Octal numbers are not supported: 198.51.010.1 is treated as 198.51.10.1, not 198.51.8.1. These IPv4 constraints also apply to IPv6 addresses that have IPv4 address parts, such as IPv4-compatible or IPv4-mapped addresses.
To convert an IPv4 address expr represented in numeric form as an INT value to an IPv6 address represented in numeric form as a VARBINARY value, use this expression:
```
INET6_ATON(INET_NTOA(expr))
```
For example:
```
mysql> SELECT HEX(INET6_ATON(INET_NTOA(167773449)));
        -> '0A000509'
```
INET6_NTOA(expr)
Given an IPv6 or IPv4 network address represented in numeric form as a binary string, returns the string representation of the address as a string in the connection character set. If the argument is not a valid address, INET6_NTOA() returns NULL.
INET6_NTOA() has these properties:
- It does not use operating system functions to perform conversions, thus the output string is platform independent.
- The return string has a maximum length of 39 (4 x 8 + 7). Given this statement:
```
CREATE TABLE t AS SELECT INET6_NTOA(expr) AS c1;
```
  The resulting table would have this definition:
```
CREATE TABLE t (c1 VARCHAR(39) CHARACTER SET utf8 DEFAULT NULL);
```
- The return string uses lowercase letters for IPv6 addresses.
```
mysql> SELECT INET6_NTOA(INET6_ATON('fdfe::5a55:caff:fefa:9089'));
        -> 'fdfe::5a55:caff:fefa:9089'
mysql> SELECT INET6_NTOA(INET6_ATON('10.0.5.9'));
        -> '10.0.5.9'

mysql> SELECT INET6_NTOA(UNHEX('FDFE0000000000005A55CAFFFEFA9089'));
        -> 'fdfe::5a55:caff:fefa:9089'
mysql> SELECT INET6_NTOA(UNHEX('0A000509'));
        -> '10.0.5.9'
```
IS_FREE_LOCK(str)
Checks whether the lock named str is free to use (that is, not locked). Returns 1 if the lock is free (no one is using the lock), 0 if the lock is in use, and NULL if an error occurs (such as an incorrect argument).
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
IS_IPV4(expr)
Returns 1 if the argument is a valid IPv4 address specified as a string, 0 otherwise.
```
mysql> SELECT IS_IPV4('10.0.5.9'), IS_IPV4('10.0.5.256');
        -> 1, 0
```
For a given argument, if IS_IPV4() returns 1, INET_ATON() (and INET6_ATON()) will return non-NULL. The converse statement is not true: In some cases, INET_ATON() returns non-NULL when IS_IPV4() returns 0.
As implied by the preceding remarks, IS_IPV4() is more strict than INET_ATON() about what constitutes a valid IPv4 address, so it may be useful for applications that need to perform strong checks against invalid values. Alternatively, use INET6_ATON() to convert IPv4 addresses to internal form and check for a NULL result (which indicates an invalid address). INET6_ATON() is equally strong as IS_IPV4() about checking IPv4 addresses.
IS_IPV4_COMPAT(expr)
This function takes an IPv6 address represented in numeric form as a binary string, as returned by INET6_ATON(). It returns 1 if the argument is a valid IPv4-compatible IPv6 address, 0 otherwise. IPv4-compatible addresses have the form ::ipv4_address.
```
mysql> SELECT IS_IPV4_COMPAT(INET6_ATON('::10.0.5.9'));
        -> 1
mysql> SELECT IS_IPV4_COMPAT(INET6_ATON('::ffff:10.0.5.9'));
        -> 0
```
The IPv4 part of an IPv4-compatible address can also be represented using hexadecimal notation. For example, 198.51.100.1 has this raw hexadecimal value:
```
mysql> SELECT HEX(INET6_ATON('198.51.100.1'));
        -> 'C6336401'
```
Expressed in IPv4-compatible form, ::198.51.100.1 is equivalent to ::c0a8:0001 or (without leading zeros) ::c0a8:1
```
mysql> SELECT
    ->   IS_IPV4_COMPAT(INET6_ATON('::198.51.100.1')),
    ->   IS_IPV4_COMPAT(INET6_ATON('::c0a8:0001')),
    ->   IS_IPV4_COMPAT(INET6_ATON('::c0a8:1'));
        -> 1, 1, 1
```
IS_IPV4_MAPPED(expr)
This function takes an IPv6 address represented in numeric form as a binary string, as returned by INET6_ATON(). It returns 1 if the argument is a valid IPv4-mapped IPv6 address, 0 otherwise. IPv4-mapped addresses have the form ::ffff:ipv4_address.
```
mysql> SELECT IS_IPV4_MAPPED(INET6_ATON('::10.0.5.9'));
        -> 0
mysql> SELECT IS_IPV4_MAPPED(INET6_ATON('::ffff:10.0.5.9'));
        -> 1
```
As with IS_IPV4_COMPAT() the IPv4 part of an IPv4-mapped address can also be represented using hexadecimal notation:
```
mysql> SELECT
    ->   IS_IPV4_MAPPED(INET6_ATON('::ffff:198.51.100.1')),
    ->   IS_IPV4_MAPPED(INET6_ATON('::ffff:c0a8:0001')),
    ->   IS_IPV4_MAPPED(INET6_ATON('::ffff:c0a8:1'));
        -> 1, 1, 1
```
IS_IPV6(expr)
Returns 1 if the argument is a valid IPv6 address specified as a string, 0 otherwise. This function does not consider IPv4 addresses to be valid IPv6 addresses.
```
mysql> SELECT IS_IPV6('10.0.5.9'), IS_IPV6('::1');
        -> 0, 1
```
For a given argument, if IS_IPV6() returns 1, INET6_ATON() will return non-NULL.
IS_USED_LOCK(str)
Checks whether the lock named str is in use (that is, locked). If so, it returns the connection identifier of the client session that holds the lock. Otherwise, it returns NULL.
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.

IS_UUID(string_uuid)

Returns 1 if the argument is a valid string-format UUID, 0 if the argument is not a valid UUID, and NULL if the argument is NULL.

“Valid” means that the value is in a format that can be parsed. That is, it has the correct length and contains only the permitted characters (hexadecimal digits in any lettercase and, optionally, dashes and curly braces). This format is most common:

aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee

These other formats are also permitted:

aaaaaaaabbbbccccddddeeeeeeeeeeee
{aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee}

For the meanings of fields within the value, see the UUID() function description.

mysql> SELECT IS_UUID('6ccd780c-baba-1026-9564-5b8c656024db');
+-------------------------------------------------+
| IS_UUID('6ccd780c-baba-1026-9564-5b8c656024db') |
+-------------------------------------------------+
|                                               1 |
+-------------------------------------------------+
mysql> SELECT IS_UUID('6CCD780C-BABA-1026-9564-5B8C656024DB');
+-------------------------------------------------+
| IS_UUID('6CCD780C-BABA-1026-9564-5B8C656024DB') |
+-------------------------------------------------+
|                                               1 |
+-------------------------------------------------+
mysql> SELECT IS_UUID('6ccd780cbaba102695645b8c656024db');
+---------------------------------------------+
| IS_UUID('6ccd780cbaba102695645b8c656024db') |
+---------------------------------------------+
|                                           1 |
+---------------------------------------------+
mysql> SELECT IS_UUID('{6ccd780c-baba-1026-9564-5b8c656024db}');
+---------------------------------------------------+
| IS_UUID('{6ccd780c-baba-1026-9564-5b8c656024db}') |
+---------------------------------------------------+
|                                                 1 |
+---------------------------------------------------+
mysql> SELECT IS_UUID('6ccd780c-baba-1026-9564-5b8c6560');
+---------------------------------------------+
| IS_UUID('6ccd780c-baba-1026-9564-5b8c6560') |
+---------------------------------------------+
|                                           0 |
+---------------------------------------------+
mysql> SELECT IS_UUID(RAND());
+-----------------+
| IS_UUID(RAND()) |
+-----------------+
|               0 |
+-----------------+

MASTER_POS_WAIT(log_name,log_pos[,timeout][,channel])
This function is useful for control of master/slave synchronization. It blocks until the slave has read and applied all updates up to the specified position in the master log. The return value is the number of log events the slave had to wait for to advance to the specified position. The function returns NULL if the slave SQL thread is not started, the slave's master information is not initialized, the arguments are incorrect, or an error occurs. It returns -1 if the timeout has been exceeded. If the slave SQL thread stops while MASTER_POS_WAIT() is waiting, the function returns NULL. If the slave is past the specified position, the function returns immediately.
On a multithreaded slave, the function waits until expiry of the limit set by the slave_checkpoint_group or slave_checkpoint_period system variable, when the checkpoint operation is called to update the status of the slave. Depending on the setting for the system variables, the function might therefore return some time after the specified position was reached.
If a timeout value is specified, MASTER_POS_WAIT() stops waiting when timeout seconds have elapsed. timeout must be greater than 0; a zero or negative timeout means no timeout.
The optional channel value enables you to name which replication channel the function applies to. See Section 17.2.3, “Replication Channels” for more information.
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
NAME_CONST(name,value)
Returns the given value. When used to produce a result set column, NAME_CONST() causes the column to have the given name. The arguments should be constants.
```
mysql> SELECT NAME_CONST('myname', 14);
+--------+
| myname |
+--------+
|     14 |
+--------+
```
This function is for internal use only. The server uses it when writing statements from stored programs that contain references to local program variables, as described in Section 23.7, “Binary Logging of Stored Programs”. You might see this function in the output from mysqlbinlog.
For your applications, you can obtain exactly the same result as in the example just shown by using simple aliasing, like this:
```
mysql> SELECT 14 AS myname;
+--------+
| myname |
+--------+
|     14 |
+--------+
1 row in set (0.00 sec)
```
See Section 13.2.10, “SELECT Syntax”, for more information about column aliases.
RELEASE_ALL_LOCKS()
Releases all named locks held by the current session and returns the number of locks released (0 if there were none)
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
RELEASE_LOCK(str)
Releases the lock named by the string str that was obtained with GET_LOCK(). Returns 1 if the lock was released, 0 if the lock was not established by this thread (in which case the lock is not released), and NULL if the named lock did not exist. The lock does not exist if it was never obtained by a call to GET_LOCK() or if it has previously been released.
The DO statement is convenient to use with RELEASE_LOCK(). See Section 13.2.3, “DO Syntax”.
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
SLEEP(duration)
Sleeps (pauses) for the number of seconds given by the duration argument, then returns 0. The duration may have a fractional part. If the argument is NULL or negative, SLEEP() produces a warning, or an error in strict SQL mode.
When sleep returns normally (without interruption), it returns 0:
```
mysql> SELECT SLEEP(1000);
+-------------+
| SLEEP(1000) |
+-------------+
|           0 |
+-------------+
```
When SLEEP() is the only thing invoked by a query that is interrupted, it returns 1 and the query itself returns no error. This is true whether the query is killed or times out:
- This statement is interrupted using KILL QUERY from another session:
```
mysql> SELECT SLEEP(1000);
+-------------+
| SLEEP(1000) |
+-------------+
|           1 |
+-------------+
```
- This statement is interrupted by timing out:
```
mysql> SELECT /*+ MAX_EXECUTION_TIME(1) */ SLEEP(1000);
+-------------+
| SLEEP(1000) |
+-------------+
|           1 |
+-------------+
```
When SLEEP() is only part of a query that is interrupted, the query returns an error:
- This statement is interrupted using KILL QUERY from another session:
```
mysql> SELECT 1 FROM t1 WHERE SLEEP(1000);
ERROR 1317 (70100): Query execution was interrupted
```
- This statement is interrupted by timing out:
```
mysql> SELECT /*+ MAX_EXECUTION_TIME(1000) */ 1 FROM t1 WHERE SLEEP(1000);
ERROR 3024 (HY000): Query execution was interrupted, maximum statement
execution time exceeded
```
This function is unsafe for statement-based replication. A warning is logged if you use this function when binlog_format is set to STATEMENT.
UUID()
Returns a Universal Unique Identifier (UUID) generated according to RFC 4122, “A Universally Unique IDentifier (UUID) URN Namespace” (http://www.ietf.org/rfc/rfc4122.txt).
A UUID is designed as a number that is globally unique in space and time. Two calls to UUID() are expected to generate two different values, even if these calls are performed on two separate devices not connected to each other.

Warning

Although UUID() values are intended to be unique, they are not necessarily unguessable or unpredictable. If unpredictability is required, UUID values should be generated some other way.

UUID() returns a value that conforms to UUID version 1 as described in RFC 4122. The value is a 128-bit number represented as a utf8 string of five hexadecimal numbers in aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee format:
- The first three numbers are generated from the low, middle, and high parts of a timestamp. The high part also includes the UUID version number.
- The fourth number preserves temporal uniqueness in case the timestamp value loses monotonicity (for example, due to daylight saving time).
- The fifth number is an IEEE 802 node number that provides spatial uniqueness. A random number is substituted if the latter is not available (for example, because the host device has no Ethernet card, or it is unknown how to find the hardware address of an interface on the host operating system). In this case, spatial uniqueness cannot be guaranteed. Nevertheless, a collision should have very low probability.
  The MAC address of an interface is taken into account only on FreeBSD and Linux. On other operating systems, MySQL uses a randomly generated 48-bit number.
```
mysql> SELECT UUID();
        -> '6ccd780c-baba-1026-9564-5b8c656024db'
```
To convert between string and binary UUID values, use the UUID_TO_BIN() and BIN_TO_UUID() functions. To check whether a string is a valid UUID value, use the IS_UUID() function.

Note

UUID() does not work with statement-based replication.
UUID_SHORT()
Returns a “short” universal identifier as a 64-bit unsigned integer. Values returned by UUID_SHORT() differ from the string-format 128-bit identifiers returned by the UUID() function and have different uniqueness properties. The value of UUID_SHORT() is guaranteed to be unique if the following conditions hold:
- The server_id value of the current server is between 0 and 255 and is unique among your set of master and slave servers
- You do not set back the system time for your server host between mysqld restarts
- You invoke UUID_SHORT() on average fewer than 16 million times per second between mysqld restarts
The UUID_SHORT() return value is constructed this way:
```
 (server_id & 255) << 56
+ (server_startup_time_in_seconds << 24)
+ incremented_variable++;
```
```
mysql> SELECT UUID_SHORT();
 -> 92395783831158784
```
Note

UUID_SHORT() does not work with statement-based replication.
UUID_TO_BIN(string_uuid), UUID_TO_BIN(string_uuid, swap_flag)
Converts a string UUID to a binary UUID and returns the result. (The IS_UUID() function description lists the permitted string UUID formats.) The return binary UUID is a VARBINARY(16) value. If the UUID argument is NULL, the return value is NULL. If any argument is invalid, an error occurs.
UUID_TO_BIN() takes one or two arguments:
- The one-argument form takes a string UUID value. The binary result is in the same order as the string argument.
- The two-argument form takes a string UUID value and a flag value:
  - If swap_flag is 0, the two-argument form is equivalent to the one-argument form. The binary result is in the same order as the string argument.
  - If swap_flag is 1, the format of the return value differs: The time-low and time-high parts (the first and third groups of hexadecimal digits, respectively) are swapped. This moves the more rapidly varying part to the right and can improve indexing efficiency if the result is stored in an indexed column.
Time-part swapping assumes the use of UUID version 1 values, such as are generated by the UUID() function. For UUID values produced by other means that do not follow version 1 format, time-part swapping provides no benefit. For details about version 1 format, see the UUID() function description.
Suppose that you have the following string UUID value:
```
mysql> SET @uuid = '6ccd780c-baba-1026-9564-5b8c656024db';
```
To convert the string UUID to binary with or without time-part swapping, use UUID_TO_BIN():
```
mysql> SELECT HEX(UUID_TO_BIN(@uuid));
+----------------------------------+
| HEX(UUID_TO_BIN(@uuid))          |
+----------------------------------+
| 6CCD780CBABA102695645B8C656024DB |
+----------------------------------+
mysql> SELECT HEX(UUID_TO_BIN(@uuid, 0));
+----------------------------------+
| HEX(UUID_TO_BIN(@uuid, 0))       |
+----------------------------------+
| 6CCD780CBABA102695645B8C656024DB |
+----------------------------------+
mysql> SELECT HEX(UUID_TO_BIN(@uuid, 1));
+----------------------------------+
| HEX(UUID_TO_BIN(@uuid, 1))       |
+----------------------------------+
| 1026BABA6CCD780C95645B8C656024DB |
+----------------------------------+
```
To convert a binary UUID returned by UUID_TO_BIN() to a string UUID, use BIN_TO_UUID(). If you produce a binary UUID by calling UUID_TO_BIN() with a second argument of 1 to swap time parts, you should also pass a second argument of 1 to BIN_TO_UUID() to unswap the time parts when converting the binary UUID back to a string UUID:
```
mysql> SELECT BIN_TO_UUID(UUID_TO_BIN(@uuid));
+--------------------------------------+
| BIN_TO_UUID(UUID_TO_BIN(@uuid))      |
+--------------------------------------+
| 6ccd780c-baba-1026-9564-5b8c656024db |
+--------------------------------------+
mysql> SELECT BIN_TO_UUID(UUID_TO_BIN(@uuid,0),0);
+--------------------------------------+
| BIN_TO_UUID(UUID_TO_BIN(@uuid,0),0)  |
+--------------------------------------+
| 6ccd780c-baba-1026-9564-5b8c656024db |
+--------------------------------------+
mysql> SELECT BIN_TO_UUID(UUID_TO_BIN(@uuid,1),1);
+--------------------------------------+
| BIN_TO_UUID(UUID_TO_BIN(@uuid,1),1)  |
+--------------------------------------+
| 6ccd780c-baba-1026-9564-5b8c656024db |
+--------------------------------------+
```
If the use of time-part swapping is not the same for the conversion in both directions, the original UUID will not be recovered properly:
```
mysql> SELECT BIN_TO_UUID(UUID_TO_BIN(@uuid,0),1);
+--------------------------------------+
| BIN_TO_UUID(UUID_TO_BIN(@uuid,0),1)  |
+--------------------------------------+
| baba1026-780c-6ccd-9564-5b8c656024db |
+--------------------------------------+
mysql> SELECT BIN_TO_UUID(UUID_TO_BIN(@uuid,1),0);
+--------------------------------------+
| BIN_TO_UUID(UUID_TO_BIN(@uuid,1),0)  |
+--------------------------------------+
| 1026baba-6ccd-780c-9564-5b8c656024db |
+--------------------------------------+
```
VALUES(col_name)
In an INSERT ... ON DUPLICATE KEY UPDATE statement, you can use the VALUES(col_name) function in the UPDATE clause to refer to column values from the INSERT portion of the statement. In other words, VALUES(col_name) in the UPDATE clause refers to the value of col_name that would be inserted, had no duplicate-key conflict occurred. This function is especially useful in multiple-row inserts. The VALUES() function is meaningful only in the ON DUPLICATE KEY UPDATE clause of INSERT statements and returns NULL otherwise. See Section 13.2.6.2, “INSERT ... ON DUPLICATE KEY UPDATE Syntax”.
```
mysql> INSERT INTO table (a,b,c) VALUES (1,2,3),(4,5,6)
    -> ON DUPLICATE KEY UPDATE c=VALUES(a)+VALUES(b);
```

12.23 Precision Math

12.23.1 Types of Numeric Values
12.23.2 DECIMAL Data Type Characteristics
12.23.3 Expression Handling
12.23.4 Rounding Behavior
12.23.5 Precision Math Examples

MySQL provides support for precision math: numeric value handling that results in extremely accurate results and a high degree control over invalid values. Precision math is based on these two features:

SQL modes that control how strict the server is about accepting or rejecting invalid data.
The MySQL library for fixed-point arithmetic.

These features have several implications for numeric operations and provide a high degree of compliance with standard SQL:

Precise calculations: For exact-value numbers, calculations do not introduce floating-point errors. Instead, exact precision is used. For example, MySQL treats a number such as .0001 as an exact value rather than as an approximation, and summing it 10,000 times produces a result of exactly 1, not a value that is merely “close” to 1.
Well-defined rounding behavior: For exact-value numbers, the result of ROUND() depends on its argument, not on environmental factors such as how the underlying C library works.
Platform independence: Operations on exact numeric values are the same across different platforms such as Windows and Unix.
Control over handling of invalid values: Overflow and division by zero are detectable and can be treated as errors. For example, you can treat a value that is too large for a column as an error rather than having the value truncated to lie within the range of the column's data type. Similarly, you can treat division by zero as an error rather than as an operation that produces a result of NULL. The choice of which approach to take is determined by the setting of the server SQL mode.

The following discussion covers several aspects of how precision math works, including possible incompatibilities with older applications. At the end, some examples are given that demonstrate how MySQL handles numeric operations precisely. For information about controlling the SQL mode, see Section 5.1.10, “Server SQL Modes”.

12.23.1 Types of Numeric Values

The scope of precision math for exact-value operations includes the exact-value data types (integer and DECIMAL types) and exact-value numeric literals. Approximate-value data types and numeric literals are handled as floating-point numbers.

Exact-value numeric literals have an integer part or fractional part, or both. They may be signed. Examples: 1, .2, 3.4, -5, -6.78, +9.10.

Approximate-value numeric literals are represented in scientific notation with a mantissa and exponent. Either or both parts may be signed. Examples: 1.2E3, 1.2E-3, -1.2E3, -1.2E-3.

Two numbers that look similar may be treated differently. For example, 2.34 is an exact-value (fixed-point) number, whereas 2.34E0 is an approximate-value (floating-point) number.

The DECIMAL data type is a fixed-point type and calculations are exact. In MySQL, the DECIMAL type has several synonyms: NUMERIC, DEC, FIXED. The integer types also are exact-value types.

The FLOAT and DOUBLE data types are floating-point types and calculations are approximate. In MySQL, types that are synonymous with FLOAT or DOUBLE are DOUBLE PRECISION and REAL.

12.23.2 DECIMAL Data Type Characteristics

This section discusses the characteristics of the DECIMAL data type (and its synonyms), with particular regard to the following topics:

Maximum number of digits
Storage format
Storage requirements
The nonstandard MySQL extension to the upper range of DECIMAL columns

The declaration syntax for a DECIMAL column is DECIMAL(M,D). The ranges of values for the arguments are as follows:

M is the maximum number of digits (the precision). It has a range of 1 to 65.
D is the number of digits to the right of the decimal point (the scale). It has a range of 0 to 30 and must be no larger than M.

The maximum value of 65 for M means that calculations on DECIMAL values are accurate up to 65 digits. This limit of 65 digits of precision also applies to exact-value numeric literals, so the maximum range of such literals differs from before.

Values for DECIMAL columns are stored using a binary format that packs nine decimal digits into 4 bytes. The storage requirements for the integer and fractional parts of each value are determined separately. Each multiple of nine digits requires 4 bytes, and any remaining digits left over require some fraction of 4 bytes. The storage required for remaining digits is given by the following table.

Leftover Digits	Number of Bytes
0	0
1–2	1
3–4	2
5–6	3
7–9	4

For example, a DECIMAL(18,9) column has nine digits on either side of the decimal point, so the integer part and the fractional part each require 4 bytes. A DECIMAL(20,6) column has fourteen integer digits and six fractional digits. The integer digits require four bytes for nine of the digits and 3 bytes for the remaining five digits. The six fractional digits require 3 bytes.

DECIMAL columns do not store a leading + character or - character or leading 0 digits. If you insert +0003.1 into a DECIMAL(5,1) column, it is stored as 3.1. For negative numbers, a literal - character is not stored.

DECIMAL columns do not permit values larger than the range implied by the column definition. For example, a DECIMAL(3,0) column supports a range of -999 to 999. A DECIMAL(M,D) column permits up to M - D digits to the left of the decimal point.

The SQL standard requires that the precision of NUMERIC(M,D) be exactly M digits. For DECIMAL(M,D), the standard requires a precision of at least M digits but permits more. In MySQL, DECIMAL(M,D) and NUMERIC(M,D) are the same, and both have a precision of exactly M digits.

For a full explanation of the internal format of DECIMAL values, see the file strings/decimal.c in a MySQL source distribution. The format is explained (with an example) in the decimal2bin() function.

12.23.3 Expression Handling

With precision math, exact-value numbers are used as given whenever possible. For example, numbers in comparisons are used exactly as given without a change in value. In strict SQL mode, for INSERT into a column with an exact data type (DECIMAL or integer), a number is inserted with its exact value if it is within the column range. When retrieved, the value should be the same as what was inserted. (If strict SQL mode is not enabled, truncation for INSERT is permissible.)

Handling of a numeric expression depends on what kind of values the expression contains:

If any approximate values are present, the expression is approximate and is evaluated using floating-point arithmetic.
If no approximate values are present, the expression contains only exact values. If any exact value contains a fractional part (a value following the decimal point), the expression is evaluated using DECIMAL exact arithmetic and has a precision of 65 digits. The term “exact” is subject to the limits of what can be represented in binary. For example, 1.0/3.0 can be approximated in decimal notation as .333..., but not written as an exact number, so (1.0/3.0)*3.0 does not evaluate to exactly 1.0.
Otherwise, the expression contains only integer values. The expression is exact and is evaluated using integer arithmetic and has a precision the same as BIGINT (64 bits).

If a numeric expression contains any strings, they are converted to double-precision floating-point values and the expression is approximate.

Inserts into numeric columns are affected by the SQL mode, which is controlled by the sql_mode system variable. (See Section 5.1.10, “Server SQL Modes”.) The following discussion mentions strict mode (selected by the STRICT_ALL_TABLES or STRICT_TRANS_TABLES mode values) and ERROR_FOR_DIVISION_BY_ZERO. To turn on all restrictions, you can simply use TRADITIONAL mode, which includes both strict mode values and ERROR_FOR_DIVISION_BY_ZERO:

mysql> SET sql_mode='TRADITIONAL';

If a number is inserted into an exact type column (DECIMAL or integer), it is inserted with its exact value if it is within the column range.

If the value has too many digits in the fractional part, rounding occurs and a warning is generated. Rounding is done as described in Section 12.23.4, “Rounding Behavior”.

If the value has too many digits in the integer part, it is too large and is handled as follows:

If strict mode is not enabled, the value is truncated to the nearest legal value and a warning is generated.
If strict mode is enabled, an overflow error occurs.

Underflow is not detected, so underflow handling is undefined.

For inserts of strings into numeric columns, conversion from string to number is handled as follows if the string has nonnumeric contents:

A string that does not begin with a number cannot be used as a number and produces an error in strict mode, or a warning otherwise. This includes the empty string.
A string that begins with a number can be converted, but the trailing nonnumeric portion is truncated. If the truncated portion contains anything other than spaces, this produces an error in strict mode, or a warning otherwise.

By default, division by zero produces a result of NULL and no warning. By setting the SQL mode appropriately, division by zero can be restricted.

With the ERROR_FOR_DIVISION_BY_ZERO SQL mode enabled, MySQL handles division by zero differently:

If strict mode is not enabled, a warning occurs.
If strict mode is enabled, inserts and updates involving division by zero are prohibited, and an error occurs.

In other words, inserts and updates involving expressions that perform division by zero can be treated as errors, but this requires ERROR_FOR_DIVISION_BY_ZERO in addition to strict mode.

Suppose that we have this statement:

INSERT INTO t SET i = 1/0;

This is what happens for combinations of strict and ERROR_FOR_DIVISION_BY_ZERO modes.

`sql_mode` Value	Result
`''` (Default)	No warning, no error; `i` is set to `NULL`.
strict	No warning, no error; `i` is set to `NULL`.
`ERROR_FOR_DIVISION_BY_ZERO`	Warning, no error; `i` is set to `NULL`.
strict,`ERROR_FOR_DIVISION_BY_ZERO`	Error condition; no row is inserted.

12.23.4 Rounding Behavior

This section discusses precision math rounding for the ROUND() function and for inserts into columns with exact-value types (DECIMAL and integer).

The ROUND() function rounds differently depending on whether its argument is exact or approximate:

For exact-value numbers, ROUND() uses the “round half up” rule: A value with a fractional part of .5 or greater is rounded up to the next integer if positive or down to the next integer if negative. (In other words, it is rounded away from zero.) A value with a fractional part less than .5 is rounded down to the next integer if positive or up to the next integer if negative.
For approximate-value numbers, the result depends on the C library. On many systems, this means that ROUND() uses the “round to nearest even” rule: A value with any fractional part is rounded to the nearest even integer.

The following example shows how rounding differs for exact and approximate values:

mysql> SELECT ROUND(2.5), ROUND(25E-1);
+------------+--------------+
| ROUND(2.5) | ROUND(25E-1) |
+------------+--------------+
| 3          |            2 |
+------------+--------------+

For inserts into a DECIMAL or integer column, the target is an exact data type, so rounding uses “round half away from zero,” regardless of whether the value to be inserted is exact or approximate:

mysql> CREATE TABLE t (d DECIMAL(10,0));
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO t VALUES(2.5),(2.5E0);
Query OK, 2 rows affected, 2 warnings (0.00 sec)
Records: 2  Duplicates: 0  Warnings: 2

mysql> SELECT d FROM t;
+------+
| d    |
+------+
| 3    |
| 3    |
+------+

12.23.5 Precision Math Examples

This section provides some examples that show precision math query results in MySQL. These examples demonstrate the principles described in Section 12.23.3, “Expression Handling”, and Section 12.23.4, “Rounding Behavior”.

Example 1. Numbers are used with their exact value as given when possible:

mysql> SELECT (.1 + .2) = .3;
+----------------+
| (.1 + .2) = .3 |
+----------------+
|              1 |
+----------------+

For floating-point values, results are inexact:

mysql> SELECT (.1E0 + .2E0) = .3E0;
+----------------------+
| (.1E0 + .2E0) = .3E0 |
+----------------------+
|                    0 |
+----------------------+

Another way to see the difference in exact and approximate value handling is to add a small number to a sum many times. Consider the following stored procedure, which adds .0001 to a variable 1,000 times.

CREATE PROCEDURE p ()
BEGIN
  DECLARE i INT DEFAULT 0;
  DECLARE d DECIMAL(10,4) DEFAULT 0;
  DECLARE f FLOAT DEFAULT 0;
  WHILE i < 10000 DO
    SET d = d + .0001;
    SET f = f + .0001E0;
    SET i = i + 1;
  END WHILE;
  SELECT d, f;
END;

The sum for both d and f logically should be 1, but that is true only for the decimal calculation. The floating-point calculation introduces small errors:

+--------+------------------+
| d      | f                |
+--------+------------------+
| 1.0000 | 0.99999999999991 |
+--------+------------------+

Example 2. Multiplication is performed with the scale required by standard SQL. That is, for two numbers X1 and X2 that have scale S1 and S2, the scale of the result is S1 + S2:

mysql> SELECT .01 * .01;
+-----------+
| .01 * .01 |
+-----------+
| 0.0001    |
+-----------+

Example 3. Rounding behavior for exact-value numbers is well-defined:

Rounding behavior (for example, with the ROUND() function) is independent of the implementation of the underlying C library, which means that results are consistent from platform to platform.

Rounding for exact-value columns (DECIMAL and integer) and exact-valued numbers uses the “round half away from zero” rule. Values with a fractional part of .5 or greater are rounded away from zero to the nearest integer, as shown here:
```
mysql> SELECT ROUND(2.5), ROUND(-2.5);
+------------+-------------+
| ROUND(2.5) | ROUND(-2.5) |
+------------+-------------+
| 3          | -3          |
+------------+-------------+
```
Rounding for floating-point values uses the C library, which on many systems uses the “round to nearest even” rule. Values with any fractional part on such systems are rounded to the nearest even integer:
```
mysql> SELECT ROUND(2.5E0), ROUND(-2.5E0);
+--------------+---------------+
| ROUND(2.5E0) | ROUND(-2.5E0) |
+--------------+---------------+
|            2 |            -2 |
+--------------+---------------+
```

Example 4. In strict mode, inserting a value that is out of range for a column causes an error, rather than truncation to a legal value.

When MySQL is not running in strict mode, truncation to a legal value occurs:

mysql> SET sql_mode='';
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE t (i TINYINT);
Query OK, 0 rows affected (0.01 sec)

mysql> INSERT INTO t SET i = 128;
Query OK, 1 row affected, 1 warning (0.00 sec)

mysql> SELECT i FROM t;
+------+
| i    |
+------+
|  127 |
+------+
1 row in set (0.00 sec)

However, an error occurs if strict mode is in effect:

mysql> SET sql_mode='STRICT_ALL_TABLES';
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE t (i TINYINT);
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO t SET i = 128;
ERROR 1264 (22003): Out of range value adjusted for column 'i' at row 1

mysql> SELECT i FROM t;
Empty set (0.00 sec)

Example 5: In strict mode and with ERROR_FOR_DIVISION_BY_ZERO set, division by zero causes an error, not a result of NULL.

In nonstrict mode, division by zero has a result of NULL:

mysql> SET sql_mode='';
Query OK, 0 rows affected (0.01 sec)

mysql> CREATE TABLE t (i TINYINT);
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO t SET i = 1 / 0;
Query OK, 1 row affected (0.00 sec)

mysql> SELECT i FROM t;
+------+
| i    |
+------+
| NULL |
+------+
1 row in set (0.03 sec)

However, division by zero is an error if the proper SQL modes are in effect:

mysql> SET sql_mode='STRICT_ALL_TABLES,ERROR_FOR_DIVISION_BY_ZERO';
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE t (i TINYINT);
Query OK, 0 rows affected (0.00 sec)

mysql> INSERT INTO t SET i = 1 / 0;
ERROR 1365 (22012): Division by 0

mysql> SELECT i FROM t;
Empty set (0.01 sec)

Example 6. Exact-value literals are evaluated as exact values.

Approximate-value literals are evaluated using floating point, but exact-value literals are handled as DECIMAL:

mysql> CREATE TABLE t SELECT 2.5 AS a, 25E-1 AS b;
Query OK, 1 row affected (0.01 sec)
Records: 1  Duplicates: 0  Warnings: 0

mysql> DESCRIBE t;
+-------+-----------------------+------+-----+---------+-------+
| Field | Type                  | Null | Key | Default | Extra |
+-------+-----------------------+------+-----+---------+-------+
| a     | decimal(2,1) unsigned | NO   |     | 0.0     |       |
| b     | double                | NO   |     | 0       |       |
+-------+-----------------------+------+-----+---------+-------+
2 rows in set (0.01 sec)

Example 7. If the argument to an aggregate function is an exact numeric type, the result is also an exact numeric type, with a scale at least that of the argument.

Consider these statements:

mysql> CREATE TABLE t (i INT, d DECIMAL, f FLOAT);
mysql> INSERT INTO t VALUES(1,1,1);
mysql> CREATE TABLE y SELECT AVG(i), AVG(d), AVG(f) FROM t;

The result is a double only for the floating-point argument. For exact type arguments, the result is also an exact type:

mysql> DESCRIBE y;
+--------+---------------+------+-----+---------+-------+
| Field  | Type          | Null | Key | Default | Extra |
+--------+---------------+------+-----+---------+-------+
| AVG(i) | decimal(14,4) | YES  |     | NULL    |       |
| AVG(d) | decimal(14,4) | YES  |     | NULL    |       |
| AVG(f) | double        | YES  |     | NULL    |       |
+--------+---------------+------+-----+---------+-------+

The result is a double only for the floating-point argument. For exact type arguments, the result is also an exact type.

Prev	Up	Next
Chapter 11 Data Types	Home	Chapter 13 SQL Statement Syntax