Chapter 16 Alternative Storage Engines

When you create a new table, you can specify which storage engine to use by adding an ENGINE table option to the CREATE TABLE statement:

-- ENGINE=INNODB not needed unless you have set a different
-- default storage engine.
CREATE TABLE t1 (i INT) ENGINE = INNODB;
-- Simple table definitions can be switched from one to another.
CREATE TABLE t2 (i INT) ENGINE = CSV;
CREATE TABLE t3 (i INT) ENGINE = MEMORY;

When you omit the ENGINE option, the default storage engine is used. The default engine is InnoDB in MySQL 5.7. You can specify the default engine by using the --default-storage-engine server startup option, or by setting the default-storage-engine option in the my.cnf configuration file.

You can set the default storage engine for the current session by setting the default_storage_engine variable:

SET default_storage_engine=NDBCLUSTER;

The storage engine for TEMPORARY tables created with CREATE TEMPORARY TABLE can be set separately from the engine for permanent tables by setting the default_tmp_storage_engine, either at startup or at runtime.

To convert a table from one storage engine to another, use an ALTER TABLE statement that indicates the new engine:

ALTER TABLE t ENGINE = InnoDB;

See Section 14.1.18, “CREATE TABLE Syntax”, and Section 14.1.8, “ALTER TABLE Syntax”.

If you try to use a storage engine that is not compiled in or that is compiled in but deactivated, MySQL instead creates a table using the default storage engine. For example, in a replication setup, perhaps your master server uses InnoDB tables for maximum safety, but the slave servers use other storage engines for speed at the expense of durability or concurrency.

By default, a warning is generated whenever CREATE TABLE or ALTER TABLE cannot use the default storage engine. To prevent confusing, unintended behavior if the desired engine is unavailable, enable the NO_ENGINE_SUBSTITUTION SQL mode. If the desired engine is unavailable, this setting produces an error instead of a warning, and the table is not created or altered. See Section 6.1.8, “Server SQL Modes”.

For new tables, MySQL always creates an .frm file to hold the table and column definitions. The table's index and data may be stored in one or more other files, depending on the storage engine. The server creates the .frm file above the storage engine level. Individual storage engines create any additional files required for the tables that they manage. If a table name contains special characters, the names for the table files contain encoded versions of those characters as described in Section 10.2.3, “Mapping of Identifiers to File Names”.

MyISAM is based on the older (and no longer available) ISAM storage engine but has many useful extensions.

Each MyISAM table is stored on disk in three files. The files have names that begin with the table name and have an extension to indicate the file type. An .frm file stores the table format. The data file has an .MYD (MYData) extension. The index file has an .MYI (MYIndex) extension.

To specify explicitly that you want a MyISAM table, indicate that with an ENGINE table option:

CREATE TABLE t (i INT) ENGINE = MYISAM;

In MySQL 5.7, it is normally necessary to use ENGINE to specify the MyISAM storage engine because InnoDB is the default engine.

You can check or repair MyISAM tables with the mysqlcheck client or myisamchk utility. You can also compress MyISAM tables with myisampack to take up much less space. See Section 5.5.3, “mysqlcheck — A Table Maintenance Program”, Section 5.6.3, “myisamchk — MyISAM Table-Maintenance Utility”, and Section 5.6.5, “myisampack — Generate Compressed, Read-Only MyISAM Tables”.

MyISAM tables have the following characteristics:

MyISAM also supports the following features:

Additional Resources

Error: Couldn't repair table: test.g00pages

Warning: Found 344 of 354 rows when repairing ./test/g00pages

clients are using or haven't closed the table properly

The MEMORY storage engine (formerly known as HEAP) creates special-purpose tables with contents that are stored in memory. Because the data is vulnerable to crashes, hardware issues, or power outages, only use these tables as temporary work areas or read-only caches for data pulled from other tables.

When to Use MEMORY or MySQL Cluster.  Developers looking to deploy applications that use the MEMORY storage engine for important, highly available, or frequently updated data should consider whether MySQL Cluster is a better choice. A typical use case for the MEMORY engine involves these characteristics:

MySQL Cluster offers the same features as the MEMORY engine with higher performance levels, and provides additional features not available with MEMORY:

For a white paper with more detailed comparison of the MEMORY storage engine and MySQL Cluster, see Scaling Web Services with MySQL Cluster: An Alternative to the MySQL Memory Storage Engine. This white paper includes a performance study of the two technologies and a step-by-step guide describing how existing MEMORY users can migrate to MySQL Cluster.

Performance Characteristics

MEMORY performance is constrained by contention resulting from single-thread execution and table lock overhead when processing updates. This limits scalability when load increases, particularly for statement mixes that include writes.

Despite the in-memory processing for MEMORY tables, they are not necessarily faster than InnoDB tables on a busy server, for general-purpose queries, or under a read/write workload. In particular, the table locking involved with performing updates can slow down concurrent usage of MEMORY tables from multiple sessions.

Depending on the kinds of queries performed on a MEMORY table, you might create indexes as either the default hash data structure (for looking up single values based on a unique key), or a general-purpose B-tree data structure (for all kinds of queries involving equality, inequality, or range operators such as less than or greater than). The following sections illustrate the syntax for creating both kinds of indexes. A common performance issue is using the default hash indexes in workloads where B-tree indexes are more efficient.

Physical Characteristics of MEMORY Tables

The MEMORY storage engine associates each table with one disk file, which stores the table definition (not the data). The file name begins with the table name and has an extension of .frm.

MEMORY tables have the following characteristics:

DDL Operations for MEMORY Tables

To create a MEMORY table, specify the clause ENGINE=MEMORY on the CREATE TABLE statement.

CREATE TABLE t (i INT) ENGINE = MEMORY;

As indicated by the engine name, MEMORY tables are stored in memory. They use hash indexes by default, which makes them very fast for single-value lookups, and very useful for creating temporary tables. However, when the server shuts down, all rows stored in MEMORY tables are lost. The tables themselves continue to exist because their definitions are stored in .frm files on disk, but they are empty when the server restarts.

This example shows how you might create, use, and remove a MEMORY table:

mysql> CREATE TABLE test ENGINE=MEMORY
    ->     SELECT ip,SUM(downloads) AS down
    ->     FROM log_table GROUP BY ip;
mysql> SELECT COUNT(ip),AVG(down) FROM test;
mysql> DROP TABLE test;

The maximum size of MEMORY tables is limited by the max_heap_table_size system variable, which has a default value of 16MB. To enforce different size limits for MEMORY tables, change the value of this variable. The value in effect for CREATE TABLE, or a subsequent ALTER TABLE or TRUNCATE TABLE, is the value used for the life of the table. A server restart also sets the maximum size of existing MEMORY tables to the global max_heap_table_size value. You can set the size for individual tables as described later in this section.

Indexes

The MEMORY storage engine supports both HASH and BTREE indexes. You can specify one or the other for a given index by adding a USING clause as shown here:

CREATE TABLE lookup
    (id INT, INDEX USING HASH (id))
    ENGINE = MEMORY;
CREATE TABLE lookup
    (id INT, INDEX USING BTREE (id))
    ENGINE = MEMORY;

For general characteristics of B-tree and hash indexes, see Section 9.3.1, “How MySQL Uses Indexes”.

MEMORY tables can have up to 64 indexes per table, 16 columns per index and a maximum key length of 3072 bytes.

If a MEMORY table hash index has a high degree of key duplication (many index entries containing the same value), updates to the table that affect key values and all deletes are significantly slower. The degree of this slowdown is proportional to the degree of duplication (or, inversely proportional to the index cardinality). You can use a BTREE index to avoid this problem.

MEMORY tables can have nonunique keys. (This is an uncommon feature for implementations of hash indexes.)

Columns that are indexed can contain NULL values.

User-Created and Temporary Tables

MEMORY table contents are stored in memory, which is a property that MEMORY tables share with internal temporary tables that the server creates on the fly while processing queries. However, the two types of tables differ in that MEMORY tables are not subject to storage conversion, whereas internal temporary tables are:

Loading Data

To populate a MEMORY table when the MySQL server starts, you can use the --init-file option. For example, you can put statements such as INSERT INTO ... SELECT or LOAD DATA INFILE into this file to load the table from a persistent data source. See Section 6.1.4, “Server Command Options”, and Section 14.2.6, “LOAD DATA INFILE Syntax”.

MEMORY Tables and Replication

A server's MEMORY tables become empty when it is shut down and restarted. If the server is a replication master, its slaves are not aware that these tables have become empty, so you see out-of-date content if you select data from the tables on the slaves. To synchronize master and slave MEMORY tables, when a MEMORY table is used on a master for the first time since it was started, a DELETE statement is written to the master's binary log, to empty the table on the slaves also. The slave still has outdated data in the table during the interval between the master's restart and its first use of the table. To avoid this interval when a direct query to the slave could return stale data, use the --init-file option to populate the MEMORY table on the master at startup.

Managing Memory Use

The server needs sufficient memory to maintain all MEMORY tables that are in use at the same time.

Memory is not reclaimed if you delete individual rows from a MEMORY table. Memory is reclaimed only when the entire table is deleted. Memory that was previously used for deleted rows is re-used for new rows within the same table. To free all the memory used by a MEMORY table when you no longer require its contents, execute DELETE or TRUNCATE TABLE to remove all rows, or remove the table altogether using DROP TABLE. To free up the memory used by deleted rows, use ALTER TABLE ENGINE=MEMORY to force a table rebuild.

The memory needed for one row in a MEMORY table is calculated using the following expression:

SUM_OVER_ALL_BTREE_KEYS(max_length_of_key + sizeof(char*) * 4)
+ SUM_OVER_ALL_HASH_KEYS(sizeof(char*) * 2)
+ ALIGN(length_of_row+1, sizeof(char*))

ALIGN() represents a round-up factor to cause the row length to be an exact multiple of the char pointer size. sizeof(char*) is 4 on 32-bit machines and 8 on 64-bit machines.

As mentioned earlier, the max_heap_table_size system variable sets the limit on the maximum size of MEMORY tables. To control the maximum size for individual tables, set the session value of this variable before creating each table. (Do not change the global max_heap_table_size value unless you intend the value to be used for MEMORY tables created by all clients.) The following example creates two MEMORY tables, with a maximum size of 1MB and 2MB, respectively:

mysql> SET max_heap_table_size = 1024*1024;
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE t1 (id INT, UNIQUE(id)) ENGINE = MEMORY;
Query OK, 0 rows affected (0.01 sec)

mysql> SET max_heap_table_size = 1024*1024*2;
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE t2 (id INT, UNIQUE(id)) ENGINE = MEMORY;
Query OK, 0 rows affected (0.00 sec)

Both tables revert to the server's global max_heap_table_size value if the server restarts.

You can also specify a MAX_ROWS table option in CREATE TABLE statements for MEMORY tables to provide a hint about the number of rows you plan to store in them. This does not enable the table to grow beyond the max_heap_table_size value, which still acts as a constraint on maximum table size. For maximum flexibility in being able to use MAX_ROWS, set max_heap_table_size at least as high as the value to which you want each MEMORY table to be able to grow.

Additional Resources

A forum dedicated to the MEMORY storage engine is available at http://forums.mysql.com/list.php?92.

The CSV storage engine stores data in text files using comma-separated values format.

The CSV storage engine is always compiled into the MySQL server.

To examine the source for the CSV engine, look in the storage/csv directory of a MySQL source distribution.

When you create a CSV table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. The storage engine also creates a data file. Its name begins with the table name and has a .CSV extension. The data file is a plain text file. When you store data into the table, the storage engine saves it into the data file in comma-separated values format.

mysql> CREATE TABLE test (i INT NOT NULL, c CHAR(10) NOT NULL)
    -> ENGINE = CSV;
Query OK, 0 rows affected (0.12 sec)

mysql> INSERT INTO test VALUES(1,'record one'),(2,'record two');
Query OK, 2 rows affected (0.00 sec)
Records: 2  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM test;
+------+------------+
| i    | c          |
+------+------------+
|    1 | record one |
|    2 | record two |
+------+------------+
2 rows in set (0.00 sec)

Creating a CSV table also creates a corresponding Metafile that stores the state of the table and the number of rows that exist in the table. The name of this file is the same as the name of the table with the extension CSM.

If you examine the test.CSV file in the database directory created by executing the preceding statements, its contents should look like this:

"1","record one"
"2","record two"

This format can be read, and even written, by spreadsheet applications such as Microsoft Excel or StarOffice Calc.

mysql> check table csvtest;
+--------------+-------+----------+----------+
| Table        | Op    | Msg_type | Msg_text |
+--------------+-------+----------+----------+
| test.csvtest | check | status   | OK       |
+--------------+-------+----------+----------+
1 row in set (0.00 sec)

mysql> check table csvtest;
+--------------+-------+----------+----------+
| Table        | Op    | Msg_type | Msg_text |
+--------------+-------+----------+----------+
| test.csvtest | check | error    | Corrupt  |
+--------------+-------+----------+----------+
1 row in set (0.01 sec)

mysql> check table csvtest;
+--------------+-------+----------+----------------------------+
| Table        | Op    | Msg_type | Msg_text                   |
+--------------+-------+----------+----------------------------+
| test.csvtest | check | warning  | Table is marked as crashed |
| test.csvtest | check | status   | OK                         |
+--------------+-------+----------+----------------------------+
2 rows in set (0.08 sec)

mysql> repair table csvtest;
+--------------+--------+----------+----------+
| Table        | Op     | Msg_type | Msg_text |
+--------------+--------+----------+----------+
| test.csvtest | repair | status   | OK       |
+--------------+--------+----------+----------+
1 row in set (0.02 sec)

The ARCHIVE storage engine produces special-purpose tables that store large amounts of unindexed data in a very small footprint.

The ARCHIVE storage engine is included in MySQL binary distributions. To enable this storage engine if you build MySQL from source, invoke CMake with the -DWITH_ARCHIVE_STORAGE_ENGINE option.

To examine the source for the ARCHIVE engine, look in the storage/archive directory of a MySQL source distribution.

You can check whether the ARCHIVE storage engine is available with the SHOW ENGINES statement.

When you create an ARCHIVE table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. The storage engine creates other files, all having names beginning with the table name. The data file has an extension of .ARZ. An .ARN file may appear during optimization operations.

The ARCHIVE engine supports INSERT, REPLACE, and SELECT, but not DELETE or UPDATE. It does support ORDER BY operations, BLOB columns, and basically all but spatial data types (see Section 12.5.1, “Spatial Data Types”). The ARCHIVE engine uses row-level locking.

The ARCHIVE engine supports the AUTO_INCREMENT column attribute. The AUTO_INCREMENT column can have either a unique or nonunique index. Attempting to create an index on any other column results in an error. The ARCHIVE engine also supports the AUTO_INCREMENT table option in CREATE TABLE statements to specify the initial sequence value for a new table or reset the sequence value for an existing table, respectively.

ARCHIVE does not support inserting a value into an AUTO_INCREMENT column less than the current maximum column value. Attempts to do so result in an ER_DUP_KEY error.

The ARCHIVE engine ignores BLOB columns if they are not requested and scans past them while reading.

Storage: Rows are compressed as they are inserted. The ARCHIVE engine uses zlib lossless data compression (see http://www.zlib.net/). You can use OPTIMIZE TABLE to analyze the table and pack it into a smaller format (for a reason to use OPTIMIZE TABLE, see later in this section). The engine also supports CHECK TABLE. There are several types of insertions that are used:

Retrieval: On retrieval, rows are uncompressed on demand; there is no row cache. A SELECT operation performs a complete table scan: When a SELECT occurs, it finds out how many rows are currently available and reads that number of rows. SELECT is performed as a consistent read. Note that lots of SELECT statements during insertion can deteriorate the compression, unless only bulk or delayed inserts are used. To achieve better compression, you can use OPTIMIZE TABLE or REPAIR TABLE. The number of rows in ARCHIVE tables reported by SHOW TABLE STATUS is always accurate. See Section 14.7.2.4, “OPTIMIZE TABLE Syntax”, Section 14.7.2.5, “REPAIR TABLE Syntax”, and Section 14.7.5.36, “SHOW TABLE STATUS Syntax”.

Additional Resources

The BLACKHOLE storage engine acts as a “black hole” that accepts data but throws it away and does not store it. Retrievals always return an empty result:

mysql> CREATE TABLE test(i INT, c CHAR(10)) ENGINE = BLACKHOLE;
Query OK, 0 rows affected (0.03 sec)

mysql> INSERT INTO test VALUES(1,'record one'),(2,'record two');
Query OK, 2 rows affected (0.00 sec)
Records: 2  Duplicates: 0  Warnings: 0

mysql> SELECT * FROM test;
Empty set (0.00 sec)

To enable the BLACKHOLE storage engine if you build MySQL from source, invoke CMake with the -DWITH_BLACKHOLE_STORAGE_ENGINE option.

To examine the source for the BLACKHOLE engine, look in the sql directory of a MySQL source distribution.

When you create a BLACKHOLE table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. There are no other files associated with the table.

The BLACKHOLE storage engine supports all kinds of indexes. That is, you can include index declarations in the table definition.

You can check whether the BLACKHOLE storage engine is available with the SHOW ENGINES statement.

Inserts into a BLACKHOLE table do not store any data, but if statement based binary logging is enabled, the SQL statements are logged and replicated to slave servers. This can be useful as a repeater or filter mechanism.

Suppose that your application requires slave-side filtering rules, but transferring all binary log data to the slave first results in too much traffic. In such a case, it is possible to set up on the master host a “dummy” slave process whose default storage engine is BLACKHOLE, depicted as follows:

The master writes to its binary log. The “dummy” mysqld process acts as a slave, applying the desired combination of replicate-do-* and replicate-ignore-* rules, and writes a new, filtered binary log of its own. (See Section 18.1.6, “Replication and Binary Logging Options and Variables”.) This filtered log is provided to the slave.

The dummy process does not actually store any data, so there is little processing overhead incurred by running the additional mysqld process on the replication master host. This type of setup can be repeated with additional replication slaves.

INSERT triggers for BLACKHOLE tables work as expected. However, because the BLACKHOLE table does not actually store any data, UPDATE and DELETE triggers are not activated: The FOR EACH ROW clause in the trigger definition does not apply because there are no rows.

Other possible uses for the BLACKHOLE storage engine include:

The BLACKHOLE engine is transaction-aware, in the sense that committed transactions are written to the binary log and rolled-back transactions are not.

Blackhole Engine and Auto Increment Columns

The Blackhole engine is a no-op engine. Any operations performed on a table using Blackhole will have no effect. This should be born in mind when considering the behavior of primary key columns that auto increment. The engine will not automatically increment field values, and does not retain auto increment field state. This has important implications in replication.

Consider the following replication scenario where all three of the following conditions apply:

In this scenario replication will fail with a duplicate entry error on the primary key column.

In statement based replication, the value of INSERT_ID in the context event will always be the same. Replication will therefore fail due to trying insert a row with a duplicate value for a primary key column.

In row based replication, the value that the engine returns for the row always be the same for each insert. This will result in the slave attempting to replay two insert log entries using the same value for the primary key column, and so replication will fail.

Column Filtering

When using row-based replication, (binlog_format=ROW), a slave where the last columns are missing from a table is supported, as described in the section Section 18.4.1.10, “Replication with Differing Table Definitions on Master and Slave”.

This filtering works on the slave side, that is, the columns are copied to the slave before they are filtered out. There are at least two cases where it is not desirable to copy the columns to the slave:

Master column filtering can be achieved using the BLACKHOLE engine. This is carried out in a way similar to how master table filtering is achieved - by using the BLACKHOLE engine and the --replicate-do-table or --replicate-ignore-table option.

The setup for the master is:

CREATE TABLE t1 (public_col_1, ..., public_col_N,
                 secret_col_1, ..., secret_col_M) ENGINE=MyISAM;

The setup for the trusted slave is:

CREATE TABLE t1 (public_col_1, ..., public_col_N) ENGINE=BLACKHOLE;

The setup for the untrusted slave is:

CREATE TABLE t1 (public_col_1, ..., public_col_N) ENGINE=MyISAM;

The MERGE storage engine, also known as the MRG_MyISAM engine, is a collection of identical MyISAM tables that can be used as one. “Identical” means that all tables have identical column and index information. You cannot merge MyISAM tables in which the columns are listed in a different order, do not have exactly the same columns, or have the indexes in different order. However, any or all of the MyISAM tables can be compressed with myisampack. See Section 5.6.5, “myisampack — Generate Compressed, Read-Only MyISAM Tables”. Differences in table options such as AVG_ROW_LENGTH, MAX_ROWS, or PACK_KEYS do not matter.

An alternative to a MERGE table is a partitioned table, which stores partitions of a single table in separate files. Partitioning enables some operations to be performed more efficiently and is not limited to the MyISAM storage engine. For more information, see Chapter 22, Partitioning.

When you create a MERGE table, MySQL creates two files on disk. The files have names that begin with the table name and have an extension to indicate the file type. An .frm file stores the table format, and an .MRG file contains the names of the underlying MyISAM tables that should be used as one. The tables do not have to be in the same database as the MERGE table.

You can use SELECT, DELETE, UPDATE, and INSERT on MERGE tables. You must have SELECT, DELETE, and UPDATE privileges on the MyISAM tables that you map to a MERGE table.

Use of DROP TABLE with a MERGE table drops only the MERGE specification. The underlying tables are not affected.

To create a MERGE table, you must specify a UNION=(list-of-tables) option that indicates which MyISAM tables to use. You can optionally specify an INSERT_METHOD option to control how inserts into the MERGE table take place. Use a value of FIRST or LAST to cause inserts to be made in the first or last underlying table, respectively. If you specify no INSERT_METHOD option or if you specify it with a value of NO, inserts into the MERGE table are not permitted and attempts to do so result in an error.

The following example shows how to create a MERGE table:

mysql> CREATE TABLE t1 (
    ->    a INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    ->    message CHAR(20)) ENGINE=MyISAM;
mysql> CREATE TABLE t2 (
    ->    a INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    ->    message CHAR(20)) ENGINE=MyISAM;
mysql> INSERT INTO t1 (message) VALUES ('Testing'),('table'),('t1');
mysql> INSERT INTO t2 (message) VALUES ('Testing'),('table'),('t2');
mysql> CREATE TABLE total (
    ->    a INT NOT NULL AUTO_INCREMENT,
    ->    message CHAR(20), INDEX(a))
    ->    ENGINE=MERGE UNION=(t1,t2) INSERT_METHOD=LAST;

Column a is indexed as a PRIMARY KEY in the underlying MyISAM tables, but not in the MERGE table. There it is indexed but not as a PRIMARY KEY because a MERGE table cannot enforce uniqueness over the set of underlying tables. (Similarly, a column with a UNIQUE index in the underlying tables should be indexed in the MERGE table but not as a UNIQUE index.)

After creating the MERGE table, you can use it to issue queries that operate on the group of tables as a whole:

mysql> SELECT * FROM total;
+---+---------+
| a | message |
+---+---------+
| 1 | Testing |
| 2 | table   |
| 3 | t1      |
| 1 | Testing |
| 2 | table   |
| 3 | t2      |
+---+---------+

To remap a MERGE table to a different collection of MyISAM tables, you can use one of the following methods:

The underlying table definitions and indexes must conform closely to the definition of the MERGE table. Conformance is checked when a table that is part of a MERGE table is opened, not when the MERGE table is created. If any table fails the conformance checks, the operation that triggered the opening of the table fails. This means that changes to the definitions of tables within a MERGE may cause a failure when the MERGE table is accessed. The conformance checks applied to each table are:

If a MERGE table cannot be opened or used because of a problem with an underlying table, CHECK TABLE displays information about which table caused the problem.

Additional Resources

The FEDERATED storage engine lets you access data from a remote MySQL database without using replication or cluster technology. Querying a local FEDERATED table automatically pulls the data from the remote (federated) tables. No data is stored on the local tables.

To include the FEDERATED storage engine if you build MySQL from source, invoke CMake with the -DWITH_FEDERATED_STORAGE_ENGINE option.

The FEDERATED storage engine is not enabled by default in the running server; to enable FEDERATED, you must start the MySQL server binary using the --federated option.

To examine the source for the FEDERATED engine, look in the storage/federated directory of a MySQL source distribution.

16.8.1 FEDERATED Storage Engine Overview

When you create a table using one of the standard storage engines (such as MyISAM, CSV or InnoDB), the table consists of the table definition and the associated data. When you create a FEDERATED table, the table definition is the same, but the physical storage of the data is handled on a remote server.

A FEDERATED table consists of two elements:

• A remote server with a database table, which in turn consists of the table definition (stored in the .frm file) and the associated table. The table type of the remote table may be any type supported by the remote mysqld server, including MyISAM or InnoDB.

• A local server with a database table, where the table definition matches that of the corresponding table on the remote server. The table definition is stored within the .frm file. However, there is no data file on the local server. Instead, the table definition includes a connection string that points to the remote table.

When executing queries and statements on a FEDERATED table on the local server, the operations that would normally insert, update or delete information from a local data file are instead sent to the remote server for execution, where they update the data file on the remote server or return matching rows from the remote server.

The basic structure of a FEDERATED table setup is shown in Figure 16.1, “FEDERATED Table Structure”.

Figure 16.1 FEDERATED Table Structure

When a client issues an SQL statement that refers to a FEDERATED table, the flow of information between the local server (where the SQL statement is executed) and the remote server (where the data is physically stored) is as follows:

1. The storage engine looks through each column that the FEDERATED table has and constructs an appropriate SQL statement that refers to the remote table.

2. The statement is sent to the remote server using the MySQL client API.

3. The remote server processes the statement and the local server retrieves any result that the statement produces (an affected-rows count or a result set).

4. If the statement produces a result set, each column is converted to internal storage engine format that the FEDERATED engine expects and can use to display the result to the client that issued the original statement.

The local server communicates with the remote server using MySQL client C API functions. It invokes mysql_real_query() to send the statement. To read a result set, it uses mysql_store_result() and fetches rows one at a time using mysql_fetch_row().

CREATE TABLE test_table (
    id     INT(20) NOT NULL AUTO_INCREMENT,
    name   VARCHAR(32) NOT NULL DEFAULT '',
    other  INT(20) NOT NULL DEFAULT '0',
    PRIMARY KEY  (id),
    INDEX name (name),
    INDEX other_key (other)
)
ENGINE=MyISAM
DEFAULT CHARSET=latin1;

CREATE TABLE federated_table (
    id     INT(20) NOT NULL AUTO_INCREMENT,
    name   VARCHAR(32) NOT NULL DEFAULT '',
    other  INT(20) NOT NULL DEFAULT '0',
    PRIMARY KEY  (id),
    INDEX name (name),
    INDEX other_key (other)
)
ENGINE=FEDERATED
DEFAULT CHARSET=latin1
CONNECTION='mysql://fed_user@remote_host:9306/federated/test_table';

scheme://user_name[:password]@host_name[:port_num]/db_name/tbl_name

CONNECTION='mysql://username:password@hostname:port/database/tablename'
CONNECTION='mysql://username@hostname/database/tablename'
CONNECTION='mysql://username:password@hostname/database/tablename'

CREATE SERVER
server_name
FOREIGN DATA WRAPPER wrapper_name
OPTIONS (option [, option] ...)

CONNECTION='mysql://fed_user@remote_host:9306/federated/test_table';

CREATE SERVER fedlink
FOREIGN DATA WRAPPER mysql
OPTIONS (USER 'fed_user', HOST 'remote_host', PORT 9306, DATABASE 'federated');

CREATE TABLE test_table (
    id     INT(20) NOT NULL AUTO_INCREMENT,
    name   VARCHAR(32) NOT NULL DEFAULT '',
    other  INT(20) NOT NULL DEFAULT '0',
    PRIMARY KEY  (id),
    INDEX name (name),
    INDEX other_key (other)
)
ENGINE=FEDERATED
DEFAULT CHARSET=latin1
CONNECTION='fedlink/test_table';

scheme://user_name[:password]@host_name[:port_num]/db_name/tbl_name

The EXAMPLE storage engine is a stub engine that does nothing. Its purpose is to serve as an example in the MySQL source code that illustrates how to begin writing new storage engines. As such, it is primarily of interest to developers.

To enable the EXAMPLE storage engine if you build MySQL from source, invoke CMake with the -DWITH_EXAMPLE_STORAGE_ENGINE option.

To examine the source for the EXAMPLE engine, look in the storage/example directory of a MySQL source distribution.

When you create an EXAMPLE table, the server creates a table format file in the database directory. The file begins with the table name and has an .frm extension. No other files are created. No data can be stored into the table. Retrievals return an empty result.

mysql> CREATE TABLE test (i INT) ENGINE = EXAMPLE;
Query OK, 0 rows affected (0.78 sec)

mysql> INSERT INTO test VALUES(1),(2),(3);
ERROR 1031 (HY000): Table storage engine for 'test' doesn't »
                    have this option

mysql> SELECT * FROM test;
Empty set (0.31 sec)

The EXAMPLE storage engine does not support indexing.

Other storage engines may be available from third parties and community members that have used the Custom Storage Engine interface.

Third party engines are not supported by MySQL. For further information, documentation, installation guides, bug reporting or for any help or assistance with these engines, please contact the developer of the engine directly.

For more information on developing a customer storage engine that can be used with the Pluggable Storage Engine Architecture, see MySQL Internals: Writing a Custom Storage Engine.

The MySQL pluggable storage engine architecture enables a database professional to select a specialized storage engine for a particular application need while being completely shielded from the need to manage any specific application coding requirements. The MySQL server architecture isolates the application programmer and DBA from all of the low-level implementation details at the storage level, providing a consistent and easy application model and API. Thus, although there are different capabilities across different storage engines, the application is shielded from these differences.

The pluggable storage engine architecture provides a standard set of management and support services that are common among all underlying storage engines. The storage engines themselves are the components of the database server that actually perform actions on the underlying data that is maintained at the physical server level.

This efficient and modular architecture provides huge benefits for those wishing to specifically target a particular application need—such as data warehousing, transaction processing, or high availability situations—while enjoying the advantage of utilizing a set of interfaces and services that are independent of any one storage engine.

The application programmer and DBA interact with the MySQL database through Connector APIs and service layers that are above the storage engines. If application changes bring about requirements that demand the underlying storage engine change, or that one or more storage engines be added to support new needs, no significant coding or process changes are required to make things work. The MySQL server architecture shields the application from the underlying complexity of the storage engine by presenting a consistent and easy-to-use API that applies across storage engines.

mysql> INSTALL PLUGIN example SONAME 'ha_example.so';

mysql> UNINSTALL PLUGIN example;