Before a storage engine can be used, the storage engine plugin shared library must be loaded into MySQL using the INSTALL PLUGIN statement. For example, if the EXAMPLE engine plugin is named ha_example and the shared library is named ha_example.so, you load it with the following statement:

INSTALL PLUGIN ha_example SONAME 'ha_example.so';

The shared library must be located in the MySQL server plugin directory, the location of which is given by the plugin_dir system variable.

To unplug a storage engine, use the UNINSTALL PLUGIN statement:

UNINSTALL PLUGIN ha_example;

If you unplug a storage engine that is needed by existing tables, those tables become inaccessible, but will still be present on disk (where applicable). Ensure that there are no tables using a storage engine before you unplug the storage engine.

To install a pluggable storage engine, the plugin file must be located in the MySQL plugin directory, and the user issuing the INSTALL PLUGIN statement must have the INSERT privilege for the mysql.plugin table.

Static format is the default for MyISAM tables. It is used when the table contains no variable-length columns (VARCHAR, VARBINARY, BLOB, or TEXT). Each row is stored using a fixed number of bytes.

Of the three MyISAM storage formats, static format is the simplest and most secure (least subject to corruption). It is also the fastest of the on-disk formats due to the ease with which rows in the data file can be found on disk: To look up a row based on a row number in the index, multiply the row number by the row length to calculate the row position. Also, when scanning a table, it is very easy to read a constant number of rows with each disk read operation.

The security is evidenced if your computer crashes while the MySQL server is writing to a fixed-format MyISAM file. In this case, myisamchk can easily determine where each row starts and ends, so it can usually reclaim all rows except the partially written one. Note that MyISAM table indexes can always be reconstructed based on the data rows.

Static-format tables have these characteristics:

Dynamic storage format is used if a MyISAM table contains any variable-length columns (VARCHAR, VARBINARY, BLOB, or TEXT), or if the table was created with the ROW_FORMAT=DYNAMIC table option.

Dynamic format is a little more complex than static format because each row has a header that indicates how long it is. A row can become fragmented (stored in non-contiguous pieces) when it is made longer as a result of an update.

You can use OPTIMIZE TABLE or myisamchk -r to defragment a table. If you have fixed-length columns that you access or change frequently in a table that also contains some variable-length columns, it might be a good idea to move the variable-length columns to other tables just to avoid fragmentation.

Dynamic-format tables have these characteristics:

Compressed storage format is a read-only format that is generated with the myisampack tool. Compressed tables can be uncompressed with myisamchk.

Compressed tables have the following characteristics:

Even though the MyISAM table format is very reliable (all changes to a table made by an SQL statement are written before the statement returns), you can still get corrupted tables if any of the following events occur:

Typical symptoms of a corrupt table are:

You can check the health of a MyISAM table using the CHECK TABLE statement, and repair a corrupted MyISAM table with REPAIR TABLE. When mysqld is not running, you can also check or repair a table with the myisamchk command. See Section 12.5.2.2, “CHECK TABLE Syntax”, Section 12.5.2.5, “REPAIR TABLE Syntax”, and Section 4.6.3, “myisamchk — MyISAM Table-Maintenance Utility”.

If your tables become corrupted frequently, you should try to determine why this is happening. The most important thing to know is whether the table became corrupted as a result of a server crash. You can verify this easily by looking for a recent restarted mysqld message in the error log. If there is such a message, it is likely that table corruption is a result of the server dying. Otherwise, corruption may have occurred during normal operation. This is a bug. You should try to create a reproducible test case that demonstrates the problem. See Section B.1.4.2, “What to Do If MySQL Keeps Crashing”, and MySQL Internals: Porting.

MySQL Enterprise Find out about problems before they occur. Subscribe to the MySQL Enterprise Monitor for expert advice about the state of your servers. For more information, see http://www.mysql.com/products/enterprise/advisors.html.

Each MyISAM index file (.MYI file) has a counter in the header that can be used to check whether a table has been closed properly. If you get the following warning from CHECK TABLE or myisamchk, it means that this counter has gone out of sync:

clients are using or haven't closed the table properly

This warning doesn't necessarily mean that the table is corrupted, but you should at least check the table.

The counter works as follows:

In other words, the counter can become incorrect only under these conditions:

You can store each InnoDB table and its indexes in its own file. This feature is called “multiple tablespaces” because in effect each table has its own tablespace.

Using multiple tablespaces can be beneficial to users who want to move specific tables to separate physical disks or who wish to restore backups of single tables quickly without interrupting the use of other InnoDB tables.

To enable multiple tablespaces, start the server with the --innodb_file_per_table option. For example, add a line to the [mysqld] section of my.cnf:

[mysqld]
innodb_file_per_table

With multiple tablespaces enabled, InnoDB stores each newly created table into its own tbl_name.ibd file in the database directory where the table belongs. This is similar to what the MyISAM storage engine does, but MyISAM divides the table into a tbl_name.MYD data file and an tbl_name.MYI index file. For InnoDB, the data and the indexes are stored together in the .ibd file. The tbl_name.frm file is still created as usual.

You cannot freely move .ibd files between database directories as you can with MyISAM table files. This is because the table definition that is stored in the InnoDB shared tablespace includes the database name, and because InnoDB must preserve the consistency of transaction IDs and log sequence numbers.

If you remove the innodb_file_per_table line from my.cnf and restart the server, InnoDB creates tables inside the shared tablespace files again.

The --innodb_file_per_table option affects only table creation, not access to existing tables. If you start the server with this option, new tables are created using .ibd files, but you can still access tables that exist in the shared tablespace. If you start the server without this option, new tables are created in the shared tablespace, but you can still access any tables that were created using multiple tablespaces.

To move an .ibd file and the associated table from one database to another, use a RENAME TABLE statement:

RENAME TABLE db1.tbl_name TO db2.tbl_name;

If you have a “clean” backup of an .ibd file, you can restore it to the MySQL installation from which it originated as follows:

In this context, a “clean” .ibd file backup is one for which the following requirements are satisfied:

You can make a clean backup .ibd file using the following method:

Another method for making a clean copy of an .ibd file is to use the commercial InnoDB Hot Backup tool:

You can use raw disk partitions as data files in the shared tablespace. By using a raw disk, you can perform non-buffered I/O on Windows and on some Unix systems without file system overhead. This may improve performance, but you are advised to perform tests with and without raw partitions to verify whether this is actually so on your system.

When you create a new data file, you must put the keyword newraw immediately after the data file size in innodb_data_file_path. The partition must be at least as large as the size that you specify. Note that 1MB in InnoDB is 1024 × 1024 bytes, whereas 1MB in disk specifications usually means 1,000,000 bytes.

[mysqld]
innodb_data_home_dir=
innodb_data_file_path=/dev/hdd1:3Gnewraw;/dev/hdd2:2Gnewraw

The next time you start the server, InnoDB notices the newraw keyword and initializes the new partition. However, do not create or change any InnoDB tables yet. Otherwise, when you next restart the server, InnoDB reinitializes the partition and your changes are lost. (As a safety measure InnoDB prevents users from modifying data when any partition with newraw is specified.)

After InnoDB has initialized the new partition, stop the server, change newraw in the data file specification to raw:

[mysqld]
innodb_data_home_dir=
innodb_data_file_path=/dev/hdd1:5Graw;/dev/hdd2:2Graw

Then restart the server and InnoDB allows changes to be made.

On Windows, you can allocate a disk partition as a data file like this:

[mysqld]
innodb_data_home_dir=
innodb_data_file_path=//./D::10Gnewraw

The //./ corresponds to the Windows syntax of \\.\ for accessing physical drives.

When you use a raw disk partition, be sure that it has permissions that allow read and write access by the account used for running the MySQL server. For example, if you run the server as the mysql user, the partition must allow read and write access to mysql. If you run the server with the --memlock option, the server must be run as root, so the partition must allow access to root.

Suppose that you have installed MySQL and have edited your option file so that it contains the necessary InnoDB configuration parameters. Before starting MySQL, you should verify that the directories you have specified for InnoDB data files and log files exist and that the MySQL server has access rights to those directories. InnoDB does not create directories, only files. Check also that you have enough disk space for the data and log files.

It is best to run the MySQL server mysqld from the command prompt when you first start the server with InnoDB enabled, not from mysqld_safe or as a Windows service. When you run from a command prompt you see what mysqld prints and what is happening. On Unix, just invoke mysqld. On Windows, start mysqld with the --console option to direct the output to the console window.

When you start the MySQL server after initially configuring InnoDB in your option file, InnoDB creates your data files and log files, and prints something like this:

InnoDB: The first specified datafile /home/heikki/data/ibdata1
did not exist:
InnoDB: a new database to be created!
InnoDB: Setting file /home/heikki/data/ibdata1 size to 134217728
InnoDB: Database physically writes the file full: wait...
InnoDB: datafile /home/heikki/data/ibdata2 did not exist:
new to be created
InnoDB: Setting file /home/heikki/data/ibdata2 size to 262144000
InnoDB: Database physically writes the file full: wait...
InnoDB: Log file /home/heikki/data/logs/ib_logfile0 did not exist:
new to be created
InnoDB: Setting log file /home/heikki/data/logs/ib_logfile0 size
to 5242880
InnoDB: Log file /home/heikki/data/logs/ib_logfile1 did not exist:
new to be created
InnoDB: Setting log file /home/heikki/data/logs/ib_logfile1 size
to 5242880
InnoDB: Doublewrite buffer not found: creating new
InnoDB: Doublewrite buffer created
InnoDB: Creating foreign key constraint system tables
InnoDB: Foreign key constraint system tables created
InnoDB: Started
mysqld: ready for connections

At this point InnoDB has initialized its tablespace and log files. You can connect to the MySQL server with the usual MySQL client programs like mysql. When you shut down the MySQL server with mysqladmin shutdown, the output is like this:

010321 18:33:34  mysqld: Normal shutdown
010321 18:33:34  mysqld: Shutdown Complete
InnoDB: Starting shutdown...
InnoDB: Shutdown completed

You can look at the data file and log directories and you see the files created there. When MySQL is started again, the data files and log files have been created already, so the output is much briefer:

InnoDB: Started
mysqld: ready for connections

If you add the innodb_file_per_table option to my.cnf, InnoDB stores each table in its own .ibd file in the same MySQL database directory where the .frm file is created. See Section 13.7.2.1, “Using Per-Table Tablespaces”.

If InnoDB prints an operating system error during a file operation, usually the problem has one of the following causes:

If something goes wrong when InnoDB attempts to initialize its tablespace or its log files, you should delete all files created by InnoDB. This means all ibdata files and all ib_logfile files. In case you have already created some InnoDB tables, delete the corresponding .frm files for these tables (and any .ibd files if you are using multiple tablespaces) from the MySQL database directories as well. Then you can try the InnoDB database creation again. It is best to start the MySQL server from a command prompt so that you see what is happening.

By default, each client that connects to the MySQL server begins with autocommit mode enabled, which automatically commits every SQL statement as you execute it. To use multiple-statement transactions, you can switch autocommit off with the SQL statement SET autocommit = 0 and end each transaction with either COMMIT or ROLLBACK. If you want to leave autocommit on, you can begin your transactions within START TRANSACTION and end them with COMMIT or ROLLBACK. The following example shows two transactions. The first is committed; the second is rolled back.

shell> mysql test

mysql> CREATE TABLE customer (a INT, b CHAR (20), INDEX (a))
    -> ENGINE=InnoDB;
Query OK, 0 rows affected (0.00 sec)
mysql> START TRANSACTION;
Query OK, 0 rows affected (0.00 sec)
mysql> INSERT INTO customer VALUES (10, 'Heikki');
Query OK, 1 row affected (0.00 sec)
mysql> COMMIT;
Query OK, 0 rows affected (0.00 sec)
mysql> SET autocommit=0;
Query OK, 0 rows affected (0.00 sec)
mysql> INSERT INTO customer VALUES (15, 'John');
Query OK, 1 row affected (0.00 sec)
mysql> ROLLBACK;
Query OK, 0 rows affected (0.00 sec)
mysql> SELECT * FROM customer;
+------+--------+
| a    | b      |
+------+--------+
|   10 | Heikki |
+------+--------+
1 row in set (0.00 sec)
mysql>

In APIs such as PHP, Perl DBI, JDBC, ODBC, or the standard C call interface of MySQL, you can send transaction control statements such as COMMIT to the MySQL server as strings just like any other SQL statements such as SELECT or INSERT. Some APIs also offer separate special transaction commit and rollback functions or methods.

To convert a non-InnoDB table to use InnoDB use ALTER TABLE:

ALTER TABLE t1 ENGINE=InnoDB;

InnoDB does not have a special optimization for separate index creation the way the MyISAM storage engine does. Therefore, it does not pay to export and import the table and create indexes afterward. The fastest way to alter a table to InnoDB is to do the inserts directly to an InnoDB table. That is, use ALTER TABLE ... ENGINE=INNODB, or create an empty InnoDB table with identical definitions and insert the rows with INSERT INTO ... SELECT * FROM ....

If you have UNIQUE constraints on secondary keys, you can speed up a table import by turning off the uniqueness checks temporarily during the import operation:

SET unique_checks=0;
... import operation ...
SET unique_checks=1;

For big tables, this saves a lot of disk I/O because InnoDB can then use its insert buffer to write secondary index records as a batch. Be certain that the data contains no duplicate keys. unique_checks allows but does not require storage engines to ignore duplicate keys.

To get better control over the insertion process, it might be good to insert big tables in pieces:

INSERT INTO newtable SELECT * FROM oldtable
   WHERE yourkey > something AND yourkey <= somethingelse;

After all records have been inserted, you can rename the tables.

During the conversion of big tables, you should increase the size of the InnoDB buffer pool to reduce disk I/O. Do not use more than 80% of the physical memory, though. You can also increase the sizes of the InnoDB log files.

Make sure that you do not fill up the tablespace: InnoDB tables require a lot more disk space than MyISAM tables. If an ALTER TABLE operation runs out of space, it starts a rollback, and that can take hours if it is disk-bound. For inserts, InnoDB uses the insert buffer to merge secondary index records to indexes in batches. That saves a lot of disk I/O. For rollback, no such mechanism is used, and the rollback can take 30 times longer than the insertion.

In the case of a runaway rollback, if you do not have valuable data in your database, it may be advisable to kill the database process rather than wait for millions of disk I/O operations to complete. For the complete procedure, see Section 13.7.6.1, “Forcing InnoDB Recovery”.

If you want all your (non-system) tables to be created as InnoDB tables, add the line default-storage-engine=innodb to the [mysqld] section of your server option file.

InnoDB provides a locking strategy that significantly improves scalability and performance of SQL statements that add rows to tables with AUTO_INCREMENT columns. This section provides background information on the original (“traditional”) implementation of auto-increment locking in InnoDB, explains the configurable locking mechanism, documents the parameter for configuring the mechanism, and describes its behavior and interaction with replication.

SELECT MAX(ai_col) FROM t FOR UPDATE;

CREATE TABLE t1 (
  c1 INT(11) NOT NULL AUTO_INCREMENT,
  c2 VARCHAR(10) DEFAULT NULL,
  PRIMARY KEY (c1)
) ENGINE=InnoDB;

Tx1: INSERT INTO t1 (c2) SELECT 1000 rows from another table ...
Tx2: INSERT INTO t1 (c2) VALUES ('xxx');

InnoDB supports foreign key constraints. The syntax for a foreign key constraint definition in InnoDB looks like this:

[CONSTRAINT [symbol]] FOREIGN KEY
    [index_name] (index_col_name, ...)
    REFERENCES tbl_name (index_col_name,...)
    [ON DELETE reference_option]
    [ON UPDATE reference_option]

reference_option:
    RESTRICT | CASCADE | SET NULL | NO ACTION

index_name represents a foreign key ID. If given, this is ignored if an index for the foreign key is defined explicitly. Otherwise, if InnoDB creates an index for the foreign key, it uses index_name for the index name.

Foreign keys definitions are subject to the following conditions:

InnoDB rejects any INSERT or UPDATE operation that attempts to create a foreign key value in a child table if there is no a matching candidate key value in the parent table. The action InnoDB takes for any UPDATE or DELETE operation that attempts to update or delete a candidate key value in the parent table that has some matching rows in the child table is dependent on the referential action specified using ON UPDATE and ON DELETE subclauses of the FOREIGN KEY clause. When the user attempts to delete or update a row from a parent table, and there are one or more matching rows in the child table, InnoDB supports five options regarding the action to be taken. If ON DELETE or ON UPDATE are not specified, the default action is RESTRICT.

InnoDB supports foreign key references within a table. In these cases, “child table records” really refers to dependent records within the same table.

Here is a simple example that relates parent and child tables through a single-column foreign key:

CREATE TABLE parent (id INT NOT NULL,
                     PRIMARY KEY (id)
) ENGINE=INNODB;
CREATE TABLE child (id INT, parent_id INT,
                    INDEX par_ind (parent_id),
                    FOREIGN KEY (parent_id) REFERENCES parent(id)
                      ON DELETE CASCADE
) ENGINE=INNODB;

A more complex example in which a product_order table has foreign keys for two other tables. One foreign key references a two-column index in the product table. The other references a single-column index in the customer table:

CREATE TABLE product (category INT NOT NULL, id INT NOT NULL,
                      price DECIMAL,
                      PRIMARY KEY(category, id)) ENGINE=INNODB;
CREATE TABLE customer (id INT NOT NULL,
                       PRIMARY KEY (id)) ENGINE=INNODB;
CREATE TABLE product_order (no INT NOT NULL AUTO_INCREMENT,
                            product_category INT NOT NULL,
                            product_id INT NOT NULL,
                            customer_id INT NOT NULL,
                            PRIMARY KEY(no),
                            INDEX (product_category, product_id),
                            FOREIGN KEY (product_category, product_id)
                              REFERENCES product(category, id)
                              ON UPDATE CASCADE ON DELETE RESTRICT,
                            INDEX (customer_id),
                            FOREIGN KEY (customer_id)
                              REFERENCES customer(id)) ENGINE=INNODB;

InnoDB allows you to add a new foreign key constraint to a table by using ALTER TABLE:

ALTER TABLE tbl_name
    ADD [CONSTRAINT [symbol]] FOREIGN KEY
    [index_name] (index_col_name, ...)
    REFERENCES tbl_name (index_col_name,...)
    [ON DELETE reference_option]
    [ON UPDATE reference_option]

The foreign key can be self referential (referring to the same table). When you add a foreign key constraint to a table using ALTER TABLE, remember to create the required indexes first.

InnoDB supports the use of ALTER TABLE to drop foreign keys:

ALTER TABLE tbl_name DROP FOREIGN KEY fk_symbol;

If the FOREIGN KEY clause included a CONSTRAINT name when you created the foreign key, you can refer to that name to drop the foreign key. Otherwise, the fk_symbol value is internally generated by InnoDB when the foreign key is created. To find out the symbol value when you want to drop a foreign key, use the SHOW CREATE TABLE statement. For example:

mysql> SHOW CREATE TABLE ibtest11c\G
*************************** 1. row ***************************
       Table: ibtest11c
Create Table: CREATE TABLE `ibtest11c` (
  `A` int(11) NOT NULL auto_increment,
  `D` int(11) NOT NULL default '0',
  `B` varchar(200) NOT NULL default '',
  `C` varchar(175) default NULL,
  PRIMARY KEY  (`A`,`D`,`B`),
  KEY `B` (`B`,`C`),
  KEY `C` (`C`),
  CONSTRAINT `0_38775` FOREIGN KEY (`A`, `D`)
REFERENCES `ibtest11a` (`A`, `D`)
ON DELETE CASCADE ON UPDATE CASCADE,
  CONSTRAINT `0_38776` FOREIGN KEY (`B`, `C`)
REFERENCES `ibtest11a` (`B`, `C`)
ON DELETE CASCADE ON UPDATE CASCADE
) ENGINE=INNODB CHARSET=latin1
1 row in set (0.01 sec)

mysql> ALTER TABLE ibtest11c DROP FOREIGN KEY `0_38775`;

You cannot add a foreign key and drop a foreign key in separate clauses of a single ALTER TABLE statement. Separate statements are required.

If ALTER TABLE for an InnoDB table results in changes to column values (for example, because a column is truncated), InnoDB's FOREIGN KEY constraint checks do not notice possible violations caused by changing the values.

The InnoDB parser allows table and column identifiers in a FOREIGN KEY ... REFERENCES ... clause to be quoted within backticks. (Alternatively, double quotes can be used if the ANSI_QUOTES SQL mode is enabled.) The InnoDB parser also takes into account the setting of the lower_case_table_names system variable.

InnoDB returns a table's foreign key definitions as part of the output of the SHOW CREATE TABLE statement:

SHOW CREATE TABLE tbl_name;

mysqldump also produces correct definitions of tables in the dump file, and does not forget about the foreign keys.

You can also display the foreign key constraints for a table like this:

SHOW TABLE STATUS FROM db_name LIKE 'tbl_name';

The foreign key constraints are listed in the Comment column of the output.

When performing foreign key checks, InnoDB sets shared row-level locks on child or parent records it has to look at. InnoDB checks foreign key constraints immediately; the check is not deferred to transaction commit.

To make it easier to reload dump files for tables that have foreign key relationships, mysqldump automatically includes a statement in the dump output to set foreign_key_checks to 0. This avoids problems with tables having to be reloaded in a particular order when the dump is reloaded. It is also possible to set this variable manually:

mysql> SET foreign_key_checks = 0;
mysql> SOURCE dump_file_name;
mysql> SET foreign_key_checks = 1;

This allows you to import the tables in any order if the dump file contains tables that are not correctly ordered for foreign keys. It also speeds up the import operation. Setting foreign_key_checks to 0 can also be useful for ignoring foreign key constraints during LOAD DATA and ALTER TABLE operations. However, even if foreign_key_checks = 0, InnoDB does not allow the creation of a foreign key constraint where a column references a non-matching column type. Also, if an InnoDB table has foreign key constraints, ALTER TABLE cannot be used to change the table to use another storage engine. To alter the storage engine, you must drop any foreign key constraints first.

InnoDB does not allow you to drop a table that is referenced by a FOREIGN KEY constraint, unless you do SET foreign_key_checks = 0. When you drop a table, the constraints that were defined in its create statement are also dropped.

If you re-create a table that was dropped, it must have a definition that conforms to the foreign key constraints referencing it. It must have the right column names and types, and it must have indexes on the referenced keys, as stated earlier. If these are not satisfied, MySQL returns error number 1005 and refers to error 150 in the error message.

If MySQL reports an error number 1005 from a CREATE TABLE statement, and the error message refers to error 150, table creation failed because a foreign key constraint was not correctly formed. Similarly, if an ALTER TABLE fails and it refers to error 150, that means a foreign key definition would be incorrectly formed for the altered table. You can use SHOW ENGINE INNODB STATUS to display a detailed explanation of the most recent InnoDB foreign key error in the server.

Deviation from SQL standards: If there are several rows in the parent table that have the same referenced key value, InnoDB acts in foreign key checks as if the other parent rows with the same key value do not exist. For example, if you have defined a RESTRICT type constraint, and there is a child row with several parent rows, InnoDB does not allow the deletion of any of those parent rows.

InnoDB performs cascading operations through a depth-first algorithm, based on records in the indexes corresponding to the foreign key constraints.

Deviation from SQL standards: A FOREIGN KEY constraint that references a non-UNIQUE key is not standard SQL. It is an InnoDB extension to standard SQL.

Deviation from SQL standards: If ON UPDATE CASCADE or ON UPDATE SET NULL recurses to update the same table it has previously updated during the cascade, it acts like RESTRICT. This means that you cannot use self-referential ON UPDATE CASCADE or ON UPDATE SET NULL operations. This is to prevent infinite loops resulting from cascaded updates. A self-referential ON DELETE SET NULL, on the other hand, is possible, as is a self-referential ON DELETE CASCADE. Cascading operations may not be nested more than 15 levels deep.

Deviation from SQL standards: Like MySQL in general, in an SQL statement that inserts, deletes, or updates many rows, InnoDB checks UNIQUE and FOREIGN KEY constraints row-by-row. According to the SQL standard, the default behavior should be deferred checking. That is, constraints are only checked after the entire SQL statement has been processed. Until InnoDB implements deferred constraint checking, some things will be impossible, such as deleting a record that refers to itself via a foreign key.

MySQL replication works for InnoDB tables as it does for MyISAM tables. It is also possible to use replication in a way where the storage engine on the slave is not the same as the original storage engine on the master. For example, you can replicate modifications to an InnoDB table on the master to a MyISAM table on the slave.

To set up a new slave for a master, you have to make a copy of the InnoDB tablespace and the log files, as well as the .frm files of the InnoDB tables, and move the copies to the slave. If the innodb_file_per_table variable is enabled, you must also copy the .ibd files as well. For the proper procedure to do this, see Section 13.7.6, “Backing Up and Recovering an InnoDB Database”.

If you can shut down the master or an existing slave, you can take a cold backup of the InnoDB tablespace and log files and use that to set up a slave. To make a new slave without taking down any server you can also use the commercial InnoDB Hot Backup tool.

Transactions that fail on the master do not affect replication at all. MySQL replication is based on the binary log where MySQL writes SQL statements that modify data. A transaction that fails (for example, because of a foreign key violation, or because it is rolled back) is not written to the binary log, so it is not sent to slaves. See Section 12.4.1, “START TRANSACTION, COMMIT, and ROLLBACK Syntax”.

Replication and CASCADE.  Cascading actions for InnoDB tables on the master are replicated on the slave only if the tables sharing the foreign key relation use InnoDB on both the master and slave. This is true whether you are using statement-based or row-based replication. For example, suppose you have started replication, and then create two tables on the master using the following CREATE TABLE statements:

CREATE TABLE fc1 (
    i INT PRIMARY KEY, 
    j INT
) ENGINE = InnoDB;

CREATE TABLE fc2 (
    m INT PRIMARY KEY, 
    n INT, 
    FOREIGN KEY ni (n) REFERENCES fc1 (i) 
        ON DELETE CASCADE
) ENGINE = InnoDB;

Suppose that the slave does not have InnoDB support enabled. If this is the case, then the tables on the slave are created, but they use the MyISAM storage engine, and the FOREIGN KEY option is ignored. Now we insert some rows into the tables on the master:

master> INSERT INTO fc1 VALUES (1, 1), (2, 2);
Query OK, 2 rows affected (0.09 sec)
Records: 2  Duplicates: 0  Warnings: 0

master> INSERT INTO fc2 VALUES (1, 1), (2, 2), (3, 1);
Query OK, 3 rows affected (0.19 sec)
Records: 3  Duplicates: 0  Warnings: 0

At this point, on both the master and the slave, table fc1 contains 2 rows, and table fc2 contains 3 rows, as shown here:

master> SELECT * FROM fc1;
+---+------+
| i | j    |
+---+------+
| 1 |    1 |
| 2 |    2 |
+---+------+
2 rows in set (0.00 sec)

master> SELECT * FROM fc2;
+---+------+
| m | n    |
+---+------+
| 1 |    1 |
| 2 |    2 |
| 3 |    1 |
+---+------+
3 rows in set (0.00 sec)

slave> SELECT * FROM fc1;
+---+------+
| i | j    |
+---+------+
| 1 |    1 |
| 2 |    2 |
+---+------+
2 rows in set (0.00 sec)

slave> SELECT * FROM fc2;
+---+------+
| m | n    |
+---+------+
| 1 |    1 |
| 2 |    2 |
| 3 |    1 |
+---+------+
3 rows in set (0.00 sec)

Now suppose that you perform the following DELETE statement on the master:

master> DELETE FROM fc1 WHERE i=1;
Query OK, 1 row affected (0.09 sec)

Due to the cascade, table fc2 on the master now contains only 1 row:

master> SELECT * FROM fc2;
+---+---+
| m | n |
+---+---+
| 2 | 2 |
+---+---+
1 row in set (0.00 sec)

However, the cascade does not propagate on the slave because on the slave the DELETE for fc1 deletes no rows from fc2. The slave's copy of fc2 still contains all of the rows that were originally inserted:

slave> SELECT * FROM fc2;
+---+---+
| m | n |
+---+---+
| 1 | 1 |
| 3 | 1 |
| 2 | 2 |
+---+---+
3 rows in set (0.00 sec)

This difference is due to the fact that the cascading deletes are handled internally by the InnoDB storage engine, which means that none of the changes are logged.

If there is database page corruption, you may want to dump your tables from the database with SELECT INTO ... OUTFILE. Usually, most of the data obtained in this way is intact. However, it is possible that the corruption might cause SELECT * FROM tbl_name statements or InnoDB background operations to crash or assert, or even cause InnoDB roll-forward recovery to crash. In such cases, you can use the innodb_force_recovery option to force the InnoDB storage engine to start up while preventing background operations from running, so that you are able to dump your tables. For example, you can add the following line to the [mysqld] section of your option file before restarting the server:

[mysqld]
innodb_force_recovery = 4

innodb_force_recovery is 0 by default (normal startup without forced recovery) The allowable non-zero values for innodb_force_recovery follow. A larger number includes all precautions of smaller numbers. If you are able to dump your tables with an option value of at most 4, then you are relatively safe that only some data on corrupt individual pages is lost. A value of 6 is more drastic because database pages are left in an obsolete state, which in turn may introduce more corruption into B-trees and other database structures.

The database must not otherwise be used with any non-zero value of innodb_force_recovery. As a safety measure, InnoDB prevents users from performing INSERT, UPDATE, or DELETE operations when innodb_force_recovery is greater than 0.

You can SELECT from tables to dump them, or DROP or CREATE tables even if forced recovery is used. If you know that a given table is causing a crash on rollback, you can drop it. You can also use this to stop a runaway rollback caused by a failing mass import or ALTER TABLE. You can kill the mysqld process and set innodb_force_recovery to 3 to bring the database up without the rollback, then DROP the table that is causing the runaway rollback.

InnoDB implements a checkpoint mechanism known as “fuzzy” checkpointing. InnoDB flushes modified database pages from the buffer pool in small batches. There is no need to flush the buffer pool in one single batch, which would in practice stop processing of user SQL statements during the checkpointing process.

During crash recovery, InnoDB looks for a checkpoint label written to the log files. It knows that all modifications to the database before the label are present in the disk image of the database. Then InnoDB scans the log files forward from the checkpoint, applying the logged modifications to the database.

InnoDB writes to its log files on a rotating basis. All committed modifications that make the database pages in the buffer pool different from the images on disk must be available in the log files in case InnoDB has to do a recovery. This means that when InnoDB starts to reuse a log file, it has to make sure that the database page images on disk contain the modifications logged in the log file that InnoDB is going to reuse. In other words, InnoDB must create a checkpoint and this often involves flushing of modified database pages to disk.

The preceding description explains why making your log files very large may reduce disk I/O in checkpointing. It often makes sense to set the total size of the log files as large as the buffer pool or even larger. The disadvantage of using large log files is that crash recovery can take longer because there is more logged information to apply to the database.

InnoDB implements standard row-level locking where there are two types of locks:

If transaction T1 holds a shared (S) lock on row r, then requests from some distinct transaction T2 for a lock on row r are handled as follows:

If a transaction T1 holds an exclusive (X) lock on row r, a request from some distinct transaction T2 for a lock of either type on r cannot be granted immediately. Instead, transaction T2 has to wait for transaction T1 to release its lock on row r.

Additionally, InnoDB supports multiple granularity locking which allows coexistence of record locks and locks on entire tables. To make locking at multiple granularity levels practical, additional types of locks called intention locks are used. Intention locks are table locks in InnoDB. The idea behind intention locks is for a transaction to indicate which type of lock (shared or exclusive) it will require later for a row in that table. There are two types of intention locks used in InnoDB (assume that transaction T has requested a lock of the indicated type on table t):

The intention locking protocol is as follows:

These rules can be conveniently summarized by means of the following lock type compatibility matrix.

A lock is granted to a requesting transaction if it is compatible with existing locks, but not if it conflicts with existing locks. A transaction waits until the conflicting existing lock is released. If a lock request conflicts with an existing lock and cannot be granted because it would cause deadlock, an error occurs.

Thus, intention locks do not block anything except full table requests (for example, LOCK TABLES ... WRITE). The main purpose of IX and IS locks is to show that someone is locking a row, or going to lock a row in the table.

The following example illustrates how an error can occur when a lock request would cause a deadlock. The example involves two clients, A and B.

First, client A creates a table containing one row, and then begins a transaction. Within the transaction, A obtains an S lock on the row by selecting it in share mode:

mysql> CREATE TABLE t (i INT) ENGINE = InnoDB;
Query OK, 0 rows affected (1.07 sec)

mysql> INSERT INTO t (i) VALUES(1);
Query OK, 1 row affected (0.09 sec)

mysql> START TRANSACTION;
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT * FROM t WHERE i = 1 LOCK IN SHARE MODE;
+------+
| i    |
+------+
|    1 |
+------+
1 row in set (0.10 sec)

Next, client B begins a transaction and attempts to delete the row from the table:

mysql> START TRANSACTION;
Query OK, 0 rows affected (0.00 sec)

mysql> DELETE FROM t WHERE i = 1;

The delete operation requires an X lock. The lock cannot be granted because it is incompatible with the S lock that client A holds, so the request goes on the queue of lock requests for the row and client B blocks.

Finally, client A also attempts to delete the row from the table:

mysql> DELETE FROM t WHERE i = 1;
ERROR 1213 (40001): Deadlock found when trying to get lock;
try restarting transaction

Deadlock occurs here because client A needs an X lock to delete the row. However, that lock request cannot be granted because client B already has a request for an X lock and is waiting for client A to release its S lock. Nor can the S lock held by A be upgraded to an X lock because of the prior request by B for an X lock. As a result, InnoDB generates an error for client A and releases its locks. At that point, the lock request for client B can be granted and B deletes the row from the table.

A consistent read means that InnoDB uses multi-versioning to present to a query a snapshot of the database at a point in time. The query sees the changes made by transactions that committed before that point of time, and no changes made by later or uncommitted transactions. The exception to this rule is that the query sees the changes made by earlier statements within the same transaction. This exception causes the following anomaly: If you update some rows in a table, a SELECT will see the latest version of the updated rows, but it might also see older versions of any rows. If other sessions simultaneously update the same table, the anomaly means that you may see the table in a state that never existed in the database.

If the transaction isolation level is REPEATABLE READ (the default level), all consistent reads within the same transaction read the snapshot established by the first such read in that transaction. You can get a fresher snapshot for your queries by committing the current transaction and after that issuing new queries.

With READ COMMITTED isolation level, each consistent read within a transaction sets and reads its own fresh snapshot.

Consistent read is the default mode in which InnoDB processes SELECT statements in READ COMMITTED and REPEATABLE READ isolation levels. A consistent read does not set any locks on the tables it accesses, and therefore other sessions are free to modify those tables at the same time a consistent read is being performed on the table.

Suppose that you are running in the default REPEATABLE READ isolation level. When you issue a consistent read (that is, an ordinary SELECT statement), InnoDB gives your transaction a timepoint according to which your query sees the database. If another transaction deletes a row and commits after your timepoint was assigned, you do not see the row as having been deleted. Inserts and updates are treated similarly.

You can advance your timepoint by committing your transaction and then doing another SELECT.

This is called multi-versioned concurrency control.

In the following example, session A sees the row inserted by B only when B has committed the insert and A has committed as well, so that the timepoint is advanced past the commit of B.

             Session A              Session B

           SET autocommit=0;      SET autocommit=0;
time
|          SELECT * FROM t;
|          empty set
|                                 INSERT INTO t VALUES (1, 2);
|
v          SELECT * FROM t;
           empty set
                                  COMMIT;

           SELECT * FROM t;
           empty set

           COMMIT;

           SELECT * FROM t;
           ---------------------
           |    1    |    2    |
           ---------------------
           1 row in set

If you want to see the “freshest” state of the database, you should use either the READ COMMITTED isolation level or a locking read:

SELECT * FROM t LOCK IN SHARE MODE;

With READ COMMITTED isolation level, each consistent read within a transaction sets and reads its own fresh snapshot. With LOCK IN SHARE MODE, a locking read occurs instead: A SELECT blocks until the transaction containing the freshest rows ends (see Section 13.7.8.3, “SELECT ... FOR UPDATE and SELECT ... LOCK IN SHARE MODE Locking Reads”).

Consistent read does not work over DROP TABLE or over ALTER TABLE:

InnoDB uses a consistent read for select in clauses like INSERT INTO ... SELECT, UPDATE ... (SELECT), and CREATE TABLE ... SELECT that do not specify FOR UPDATE or IN SHARE MODE if the innodb_locks_unsafe_for_binlog option is set and the isolation level of the transaction is not set to SERIALIZABLE. Thus, no locks are set on rows read from the selected table. Otherwise, InnoDB uses stronger locks and the SELECT part acts like READ COMMITTED, where each consistent read, even within the same transaction, sets and reads its own fresh snapshot.

In some circumstances, a consistent (non-locking) read is not convenient and a locking read is required instead. InnoDB supports two types of locking reads:

Locks set by IN SHARE MODE and FOR UPDATE reads are released when the transaction is committed or rolled back.

As an example of a situation in which a locking read is useful, suppose that you want to insert a new row into a table child, and make sure that the child row has a parent row in table parent. The following discussion describes how to implement referential integrity in application code.

Suppose that you use a consistent read to read the table parent and indeed see the parent row of the to-be-inserted child row in the table. Can you safely insert the child row to table child? No, because it is possible for some other session to delete the parent row from the table parent in the meantime without you being aware of it.

The solution is to perform the SELECT in a locking mode using LOCK IN SHARE MODE:

SELECT * FROM parent WHERE NAME = 'Jones' LOCK IN SHARE MODE;

A read performed with LOCK IN SHARE MODE reads the latest available data and sets a shared mode lock on the rows read. A shared mode lock prevents others from updating or deleting the row read. Also, if the latest data belongs to a yet uncommitted transaction of another session, we wait until that transaction ends. After we see that the LOCK IN SHARE MODE query returns the parent 'Jones', we can safely add the child record to the child table and commit our transaction.

Let us look at another example: We have an integer counter field in a table child_codes that we use to assign a unique identifier to each child added to table child. It is not a good idea to use either consistent read or a shared mode read to read the present value of the counter because two users of the database may then see the same value for the counter, and a duplicate-key error occurs if two users attempt to add children with the same identifier to the table.

Here, LOCK IN SHARE MODE is not a good solution because if two users read the counter at the same time, at least one of them ends up in deadlock when it attempts to update the counter.

In this case, there are two good ways to implement reading and incrementing the counter:

The latter approach can be implemented as follows:

SELECT counter_field FROM child_codes FOR UPDATE;
UPDATE child_codes SET counter_field = counter_field + 1;

A SELECT ... FOR UPDATE reads the latest available data, setting exclusive locks on each row it reads. Thus, it sets the same locks a searched SQL UPDATE would set on the rows.

The preceding description is merely an example of how SELECT ... FOR UPDATE works. In MySQL, the specific task of generating a unique identifier actually can be accomplished using only a single access to the table:

UPDATE child_codes SET counter_field = LAST_INSERT_ID(counter_field + 1);
SELECT LAST_INSERT_ID();

The SELECT statement merely retrieves the identifier information (specific to the current connection). It does not access any table.

InnoDB has several types of record-level locks:

Record locks always lock index records, even if a table is defined with no indexes. For such cases, InnoDB creates a hidden clustered index and uses this index for record locking. See Section 13.7.10.1, “Clustered and Secondary Indexes”.

By default, InnoDB operates in REPEATABLE READ transaction isolation level and with the innodb_locks_unsafe_for_binlog system variable disabled. In this case, InnoDB uses next-key locks for searches and index scans, which prevents phantom rows (see Section 13.7.8.5, “Avoiding the Phantom Problem Using Next-Key Locking”).

Next-key locking combines index-row locking with gap locking. InnoDB performs row-level locking in such a way that when it searches or scans a table index, it sets shared or exclusive locks on the index records it encounters. Thus, the row-level locks are actually index-record locks. In addition, a next-key lock on an index record also affects the “gap” before that index record. That is, a next-key lock is an index-record lock plus a gap lock on the gap preceding the index record. If one session has a shared or exclusive lock on record R in an index, another session cannot insert a new index record in the gap immediately before R in the index order.

Suppose that an index contains the values 10, 11, 13, and 20. The possible next-key locks for this index cover the following intervals, where ( or ) denote exclusion of the interval endpoint and [ or ] denote inclusion of the endpoint:

(negative infinity, 10]
(10, 11]
(11, 13]
(13, 20]
(20, positive infinity)

For the last interval, the next-key lock locks the gap above the largest value in the index and the “supremum” pseudo-record having a value higher than any value actually in the index. The supremum is not a real index record, so, in effect, this next-key lock locks only the gap following the largest index value.

The preceding example shows that a gap might span a single index value, multiple index values, or even be empty.

Gap locking is not needed for statements that lock rows using a unique index to search for a unique row. For example, if the id column has a unique index, the following statement uses only an index-record lock for the row having id value 100 and it does not matter whether other sessions insert rows in the preceding gap:

SELECT * FROM child WHERE id = 100;

If id is not indexed or has a non-unique index, the statement does lock the preceding gap.

Gap locking can be disabled explicitly. This occurs if you change the transaction isolation level to READ COMMITTED or enable the innodb_locks_unsafe_for_binlog system variable. Under these circumstances, gap locking is disabled for searches and index scans and is used only for foreign-key constraint checking and duplicate-key checking.

There are also other effects of using the READ COMMITTED isolation level or enabling innodb_locks_unsafe_for_binlog: Record locks for non-matching rows are released after MySQL has evaluated the WHERE condition. For UPDATE statements, InnoDB does a “semi-consistent” read, such that it returns the latest committed version to MySQL so that MySQL can determine whether the row matches the WHERE condition of the UPDATE.

The so-called phantom problem occurs within a transaction when the same query produces different sets of rows at different times. For example, if a SELECT is executed twice, but returns a row the second time that was not returned the first time, the row is a “phantom” row.

Suppose that there is an index on the id column of the child table and that you want to read and lock all rows from the table having an identifier value larger than 100, with the intention of updating some column in the selected rows later:

SELECT * FROM child WHERE id > 100 FOR UPDATE;

The query scans the index starting from the first record where id is bigger than 100. Let the table contain rows having id values of 90 and 102. If the locks set on the index records in the scanned range do not lock out inserts made in the gaps (in this case, the gap between 90 and 102), another session can insert a new row into the table with an id of 101. If you were to execute the same SELECT within the same transaction, you would see a new row with an id of 101 (a “phantom”) in the result set returned by the query. If we regard a set of rows as a data item, the new phantom child would violate the isolation principle of transactions that a transaction should be able to run so that the data it has read does not change during the transaction.

To prevent phantoms, InnoDB uses an algorithm called next-key locking that combines index-row locking with gap locking. InnoDB performs row-level locking in such a way that when it searches or scans a table index, it sets shared or exclusive locks on the index records it encounters. Thus, the row-level locks are actually index-record locks. In addition, a next-key lock on an index record also affects the “gap” before that index record. That is, a next-key lock is an index-record lock plus a gap lock on the gap preceding the index record. If one session has a shared or exclusive lock on record R in an index, another session cannot insert a new index record in the gap immediately before R in the index order.

When InnoDB scans an index, it can also lock the gap after the last record in the index. Just that happens in the preceding example: To prevent any insert into the table where id would be bigger than 100, the locks set by InnoDB include a lock on the gap following id value 102.

You can use next-key locking to implement a uniqueness check in your application: If you read your data in share mode and do not see a duplicate for a row you are going to insert, then you can safely insert your row and know that the next-key lock set on the successor of your row during the read prevents anyone meanwhile inserting a duplicate for your row. Thus, the next-key locking allows you to “lock” the non-existence of something in your table.

Gap locking can be disabled as discussed in Section 13.7.8.4, “InnoDB Record, Gap, and Next-Key Locks”. This may cause phantom problems because other sessions can insert new rows into the gaps when gap locking is disabled.

A locking read, an UPDATE, or a DELETE generally set record locks on every index record that is scanned in the processing of the SQL statement. It does not matter whether there are WHERE conditions in the statement that would exclude the row. InnoDB does not remember the exact WHERE condition, but only knows which index ranges were scanned. The locks are normally next-key locks that also block inserts into the “gap” immediately before the record. However, gap locking can be disabled explicitly, which causes next-key locking not to be used. For more information, see Section 13.7.8.4, “InnoDB Record, Gap, and Next-Key Locks”.

If the index record locks to be set are exclusive, InnoDB also retrieves the clustered index record and sets a lock on it.

Differences between shared and exclusive locks are described in Section 13.7.8.1, “InnoDB Lock Modes”.

If you have no indexes suitable for your statement and MySQL must scan the entire table to process the statement, every row of the table becomes locked, which in turn blocks all inserts by other users to the table. It is important to create good indexes so that your queries do not unnecessarily scan many rows.

For SELECT ... FOR UPDATE or SELECT ... IN SHARE MODE, locks are acquired for scanned rows, and expected to be released for rows that do not qualify for inclusion in the result set (for example, if they do not meet the criteria given in the WHERE clause). However, in some cases, rows might not be unlocked immediately because the relationship between a result row and its original source is lost during query execution. For example, in a UNION, scanned (and locked) rows from a table might be inserted into a temporary table before evaluation whether they qualify for the result set. In this circumstance, the relationship of the rows in the temporary table to the rows in the original table is lost and the latter rows are not unlocked until the end of query execution.

InnoDB sets specific types of locks as follows:

By default, MySQL starts the session for each new connection with autocommit mode enabled, so MySQL does a commit after each SQL statement if that statement did not return an error. If a statement returns an error, the commit or rollback behavior depends on the error. See Section 13.7.12, “InnoDB Error Handling”.

If a session that has autocommit disabled ends without explicitly committing the final transaction, MySQL rolls back that transaction.

Some statements implicitly end a transaction, as if you had done a COMMIT before executing the statement. For details, see Section 12.4.3, “Statements That Cause an Implicit Commit”.

InnoDB automatically detects a deadlock of transactions and rolls back a transaction or transactions to break the deadlock. InnoDB tries to pick small transactions to roll back, where the size of a transaction is determined by the number of rows inserted, updated, or deleted.

InnoDB is aware of table locks if innodb_table_locks = 1 (the default) and autocommit = 0, and the MySQL layer above it knows about row-level locks. Otherwise, InnoDB cannot detect deadlocks where a table lock set by a MySQL LOCK TABLES statement or a lock set by a storage engine other than InnoDB is involved. You must resolve these situations by setting the value of the innodb_lock_wait_timeout system variable.

When InnoDB performs a complete rollback of a transaction, all locks set by the transaction are released. However, if just a single SQL statement is rolled back as a result of an error, some of the locks set by the statement may be preserved. This happens because InnoDB stores row locks in a format such that it cannot know afterward which lock was set by which statement.

As of MySQL 6.0.5, if a SELECT calls a stored function in a transaction, and a statement within the function fails, that statement rolls back. Furthermore, if ROLLBACK is executed after that, the entire transaction rolls back. Before 6.0.5, the failed statement did not roll back when it failed (even though it might ultimately get rolled back by a ROLLBACK later that rolls back the entire transaction).

Deadlocks are a classic problem in transactional databases, but they are not dangerous unless they are so frequent that you cannot run certain transactions at all. Normally, you must write your applications so that they are always prepared to re-issue a transaction if it gets rolled back because of a deadlock.

InnoDB uses automatic row-level locking. You can get deadlocks even in the case of transactions that just insert or delete a single row. That is because these operations are not really “atomic”; they automatically set locks on the (possibly several) index records of the row inserted or deleted.

You can cope with deadlocks and reduce the likelihood of their occurrence with the following techniques:

Every InnoDB table has a special index called the clustered index where the data for the rows is stored:

Accessing a row through the clustered index is fast because the row data is on the same page where the index search leads. If a table is large, the clustered index architecture often saves a disk I/O operation when compared to storage organizations that store row data using a different page from the index record. (For example, MyISAM uses one file for data rows and another for index records.)

In InnoDB, the records in non-clustered indexes (also called secondary indexes) contain the primary key columns for the row that are not in the secondary index. InnoDB uses this primary key value to search for the row in the clustered index. If the primary key is long, the secondary indexes use more space, so it is advantageous to have a short primary key.

All InnoDB indexes are B-trees where the index records are stored in the leaf pages of the tree. The default size of an index page is 16KB. When new records are inserted, InnoDB tries to leave 1/16 of the page free for future insertions and updates of the index records.

If index records are inserted in a sequential order (ascending or descending), the resulting index pages are about 15/16 full. If records are inserted in a random order, the pages are from 1/2 to 15/16 full. If the fill factor of an index page drops below 1/2, InnoDB tries to contract the index tree to free the page.

It is a common situation in database applications that the primary key is a unique identifier and new rows are inserted in the ascending order of the primary key. Thus, insertions into the clustered index do not require random reads from a disk.

On the other hand, secondary indexes are usually non-unique, and insertions into secondary indexes happen in a relatively random order. This would cause a lot of random disk I/O operations without a special mechanism used in InnoDB.

If an index record should be inserted into a non-unique secondary index, InnoDB checks whether the secondary index page is in the buffer pool. If that is the case, InnoDB does the insertion directly to the index page. If the index page is not found in the buffer pool, InnoDB inserts the record to a special insert buffer structure. The insert buffer is kept so small that it fits entirely in the buffer pool, and insertions can be done very fast.

Periodically, the insert buffer is merged into the secondary index trees in the database. Often it is possible to merge several insertions into the same page of the index tree, saving disk I/O operations. It has been measured that the insert buffer can speed up insertions into a table up to 15 times.

The insert buffer merging may continue to happen after the inserting transaction has been committed. In fact, it may continue to happen after a server shutdown and restart (see Section 13.7.6.1, “Forcing InnoDB Recovery”).

Insert buffer merging may take many hours when many secondary indexes must be updated and many rows have been inserted. During this time, disk I/O will be increased, which can cause significant slowdown on disk-bound queries. Another significant background I/O operation is the purge thread (see Section 13.7.9, “InnoDB Multi-Versioning”).

If a table fits almost entirely in main memory, the fastest way to perform queries on it is to use hash indexes. InnoDB has a mechanism that monitors index searches made to the indexes defined for a table. If InnoDB notices that queries could benefit from building a hash index, it does so automatically.

The hash index is always built based on an existing B-tree index on the table. InnoDB can build a hash index on a prefix of any length of the key defined for the B-tree, depending on the pattern of searches that InnoDB observes for the B-tree index. A hash index can be partial: It is not required that the whole B-tree index is cached in the buffer pool. InnoDB builds hash indexes on demand for those pages of the index that are often accessed.

In a sense, InnoDB tailors itself through the adaptive hash index mechanism to ample main memory, coming closer to the architecture of main-memory databases.

The physical row structure for an InnoDB table depends on the row format specified when the table was created. InnoDB uses the COMPACT format by default, but the REDUNDANT format is available to retain compatibility with older versions of MySQL. To check the row format of an InnoDB table, use SHOW TABLE STATUS.

The compact row format decreases row storage space by about 20% at the cost of increasing CPU use for some operations. If your workload is a typical one that is limited by cache hit rates and disk speed, compact format is likely to be faster. If the workload is a rare case that is limited by CPU speed, compact format might be slower.

Rows in InnoDB tables that use REDUNDANT row format have the following characteristics:

Rows in InnoDB tables that use COMPACT row format have the following characteristics: