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8 MySQL Table Types

As of MySQL Version 3.23.6, you can choose between three basic table formats (ISAM, HEAP and MyISAM. Newer MySQL may support additional table type (BDB, GEMINI or InnoDB), depending on how you compile it. When you create a new table, you can tell MySQL which table type it should use for the table. MySQL will always create a .frm file to hold the table and column definitions. Depending on the table type, the index and data will be stored in other files.

Note that to use InnoDB tables you have to use at least the innodb_data_file_path startup option. See section 8.7.2 InnoDB startup options.

The default table type in MySQL is MyISAM. If you are trying to use a table type that is not compiled-in or activated, MySQL will instead create a table of type MyISAM. This is a very useful feature when you want to copy tables between different SQL servers that supports different table types (like copying tables to a slave that is optimized for speed by not having transactional tables). This automatic table changing can however also be very confusing for new MySQL users. We plan to fix this by introducing warnings in MySQL 4.0 and giving a warning when a table type is automatically changed.

You can convert tables between different types with the ALTER TABLE statement. See section 7.8 ALTER TABLE Syntax.

Note that MySQL supports two different kinds of tables. Transaction-safe tables (BDB, InnoDB or GEMINI) and not transaction-safe tables (HEAP, ISAM, MERGE, and MyISAM).

Advantages of transaction-safe tables (TST):

Advantages of not transaction-safe tables (NTST):

You can combine TST and NTST tables in the same statements to get the best of both worlds.

8.1 MyISAM Tables

MyISAM is the default table type in MySQL Version 3.23. It's based on the ISAM code and has a lot of useful extensions.

The index is stored in a file with the .MYI (MYIndex) extension, and the data is stored in a file with the .MYD (MYData) extension. You can check/repair MyISAM tables with the myisamchk utility. See section 16.5 Using myisamchk for Crash Recovery. You can compress MyISAM tables with myisampack to take up much less space. See section 15.12 The MySQL Compressed Read-only Table Generator.

The following is new in MyISAM:

MyISAM also supports the following things, which MySQL will be able to use in the near future:

Note that index files are usually much smaller with MyISAM than with ISAM. This means that MyISAM will normally use less system resources than ISAM, but will need more CPU when inserting data into a compressed index.

The following options to mysqld can be used to change the behavior of MyISAM tables. See section 7.28.4 SHOW VARIABLES.

Option Meaning
--myisam-recover=# Automatic recover of crashed tables.
-O myisam_sort_buffer_size=# Buffer used when recovering tables.
--delay-key-write-for-all-tables Don't flush key buffers between writes for any MyISAM table
-O myisam_max_extra_sort_file_size=# Used to help MySQL to decide when to use the slow but safe key cache index create method. NOTE that this parameter is given in megabytes!
-O myisam_max_sort_file_size=# Don't use the fast sort index method to created index if the temporary file would get bigger than this. NOTE that this paramter is given in megabytes!

The automatic recovery is activated if you start mysqld with --myisam-recover=#. See section 4.16.4 mysqld Command-line Options. On open, the table is checked if it's marked as crashed or if the open count variable for the table is not 0 and you are running with --skip-locking. If either of the above is true the following happens.

If the recover wouldn't be able to recover all rows from a previous completed statement and you didn't specify FORCE as an option to myisam-recover, then the automatic repair will abort with an error message in the error file:

Error: Couldn't repair table: test.g00pages

If you in this case had used the FORCE option you would instead have got a warning in the error file:

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

Note that if you run automatic recover with the BACKUP option, you should have a cron script that automatically moves file with names like `tablename-datetime.BAK' from the database directories to a backup media.

See section 4.16.4 mysqld Command-line Options.

8.1.1 Space Needed for Keys

MySQL can support different index types, but the normal type is ISAM or MyISAM. These use a B-tree index, and you can roughly calculate the size for the index file as (key_length+4)/0.67, summed over all keys. (This is for the worst case when all keys are inserted in sorted order and we don't have any compressed keys.)

String indexes are space compressed. If the first index part is a string, it will also be prefix compressed. Space compression makes the index file smaller than the above figures if the string column has a lot of trailing space or is a VARCHAR column that is not always used to the full length. Prefix compression is used on keys that start with a string. Prefix compression helps if there are many strings with an identical prefix.

In MyISAM tables, you can also prefix compress numbers by specifying PACK_KEYS=1 when you create the table. This helps when you have many integer keys that have an identical prefix when the numbers are stored high-byte first.

8.1.2 MyISAM Table Formats

MyISAM supports 3 different table types. Two of them are chosen automatically depending on the type of columns you are using. The third, compressed tables, can only be created with the myisampack tool. Static (Fixed-length) Table Characteristics

This is the default format. It's used when the table contains no VARCHAR, BLOB, or TEXT columns.

This format is the simplest and most secure format. It is also the fastest of the on-disk formats. The speed comes from the easy way data can be found on disk. When looking up something with an index and static format it is very simple. Just multiply the row number by the row length.

Also, when scanning a table it is very easy to read a constant number of records with each disk read.

The security is evidenced if your computer crashes when writing to a fixed-size MyISAM file, in which case myisamchk can easily figure out where each row starts and ends. So it can usually reclaim all records except the partially written one. Note that in MySQL all indexes can always be reconstructed: Dynamic Table Characteristics

This format is used if the table contains any VARCHAR, BLOB, or TEXT columns or if the table was created with ROW_FORMAT=dynamic.

This format is a little more complex because each row has to have a header that says how long it is. One record can also end up at more than one location when it is made longer at an update.

You can use OPTIMIZE table or myisamchk to defragment a table. If you have static data that you access/change a lot in the same table as some VARCHAR or BLOB columns, it might be a good idea to move the dynamic columns to other tables just to avoid fragmentation: Compressed Table Characteristics

This is a read-only type that is generated with the optional myisampack tool (pack_isam for ISAM tables):

8.1.3 MyISAM table problems.

The file format that MySQL uses to store data has been extensively tested, but there are always circumstances that may cause database tables to become corrupted. Corrupted MyISAM tables.

Even if the MyISAM table format is very reliable (all changes to a table is written before the SQL statements returns) , you can still get corrupted tables if some of the following things happens:

Typial typical symptoms for a corrupt table is:

You can check if a table is ok with the command CHECK TABLE. See section 7.12 CHECK TABLE Syntax.

You can repair a corrupted table with REPAIR TABLE. See section 7.16 REPAIR TABLE Syntax. You can also repair a table, when mysqld is not running with the myisamchk command. myisamchk syntax.

If your tables get corrupted a lot you should try to find the reason for this! See section 21.2 What to Do if MySQL Keeps Crashing.

In this case the most important thing to know is if the table got corrupted if the mysqld died (one can easily verify this by checking if there is a recent row restarted mysqld in the mysqld error file). If this isn't the case, then you should try to make a test case of this. See section I.1.6 Making a test case when you experience table corruption. Clients is using or hasn't closed the table properly

Each MyISAM .MYI file has in the header a counter that can be used to check if a table has been closed properly.

If you get the following warning from CHECK TABLE or myisamchk:

# clients is using or hasn't closed the table properly

this means that this counter has come out of sync. This doesn't mean that the table is corrupted, but means that you should at least do a check on the table to verify that it's ok.

The counter works as follows:

In other words, the only ways this can go out of sync are:

8.2 MERGE Tables

MERGE tables are new in MySQL Version 3.23.25. The code is still in gamma, but should be resonable stable.

A MERGE table is a collection of identical MyISAM tables that can be used as one. You can only SELECT, DELETE, and UPDATE from the collection of tables. If you DROP the MERGE table, you are only dropping the MERGE specification.

Note that DELETE FROM merge_table used without a WHERE will only clear the mapping for the table, not delete everything in the mapped tables. (We plan to fix this in 4.0).

With identical tables we mean that all tables are created with identical column and key information. You can't put a MERGE over tables where the columns are packed differently or doesn't have exactly the same columns. Some of the tables can however be compressed with myisampack. See section 15.12 The MySQL Compressed Read-only Table Generator.

When you create a MERGE table, you will get a .frm table definition file and a .MRG table list file. The .MRG just contains a list of the index files (.MYI files) that should be used as one.

For the moment you need to have SELECT, UPDATE, and DELETE privileges on the tables you map to a MERGE table.

MERGE tables can help you solve the following problems:

The disadvantages with MERGE tables are:

The following example shows you how to use MERGE tables:

INSERT INTO t1 (message) VALUES ("Testing"),("table"),("t1");
INSERT INTO t2 (message) VALUES ("Testing"),("table"),("t2");
CREATE TABLE total (a INT NOT NULL, message CHAR(20), KEY(a)) TYPE=MERGE UNION=(t1,t2);

Note that we didn't create a UNIQUE or PRIMARY KEY in the total table as the key isn't going to be unique in the total table.

Note that you can also manipulate the .MRG file directly from the outside of the MySQL server:

shell> cd /mysql-data-directory/current-database
shell> ls -1 t1.MYI t2.MYI > total.MRG
shell> mysqladmin flush-tables

Now you can do things like:

mysql> select * from total;
| a | message |
| 1 | Testing |
| 2 | table   |
| 3 | t1      |
| 1 | Testing |
| 2 | table   |
| 3 | t2      |

To remap a MERGE table you can do one of the following:

8.3 ISAM Tables

You can also use the deprecated ISAM table type. This will disappear rather soon because MyISAM is a better implementation of the same thing. ISAM uses a B-tree index. The index is stored in a file with the .ISM extension, and the data is stored in a file with the .ISD extension. You can check/repair ISAM tables with the isamchk utility. See section 16.5 Using myisamchk for Crash Recovery.

ISAM has the following features/properties:

Most of the things true for MyISAM tables are also true for ISAM tables. See section 8.1 MyISAM Tables. The major differences compared to MyISAM tables are:

If you want to convert an ISAM table to a MyISAM table so that you can use utilities such as mysqlcheck, use an ALTER TABLE statement:

mysql> ALTER TABLE tbl_name TYPE = MYISAM;

8.4 HEAP Tables

HEAP tables use a hashed index and are stored in memory. This makes them very fast, but if MySQL crashes you will lose all data stored in them. HEAP is very useful for temporary tables!

The MySQL internal HEAP tables use 100% dynamic hashing without overflow areas. There is no extra space needed for free lists. HEAP tables also don't have problems with delete + inserts, which normally is common with hashed tables:

mysql> CREATE TABLE test TYPE=HEAP SELECT ip,SUM(downloads) as down
        FROM log_table GROUP BY ip;
mysql> SELECT COUNT(ip),AVG(down) FROM test;
mysql> DROP TABLE test;

Here are some things you should consider when you use HEAP tables:

The memory needed for one row in a HEAP table is:

SUM_OVER_ALL_KEYS(max_length_of_key + sizeof(char*) * 2)
+ ALIGN(length_of_row+1, sizeof(char*))

sizeof(char*) is 4 on 32-bit machines and 8 on 64-bit machines.

8.5 BDB or Berkeley_DB Tables

8.5.1 Overview of BDB Tables

Support for BDB tables is included in the MySQL source distribution starting from Version 3.23.34 and is activated in the MySQL-Max binary.

BerkeleyDB, available at http://www.sleepycat.com/ has provided MySQL with a transactional table handler. By using BerkeleyDB tables, your tables may have a greater chance of surviving crashes, and also provides COMMIT and ROLLBACK on transactions. The MySQL source distribution comes with a BDB distribution that has a couple of small patches to make it work more smoothly with MySQL. You can't use a non-patched BDB version with MySQL.

We at MySQL AB are working in close cooperation with Sleepycat to keep the quality of the MySQL/BDB interface high.

When it comes to supporting BDB tables, we are committed to help our users to locate the problem and help creating a reproducable test case for any problems involving BDB tables. Any such test case will be forwarded to Sleepycat who in turn will help us find and fix the problem. As this is a two stage operation, any problems with BDB tables may take a little longer for us to fix than for other table handlers. However, as the BerkeleyDB code itself has been used by many other applications than MySQL, we don't envision any big problems with this. See section 3.5.6 Support for other table handlers.

8.5.2 Installing BDB

If you have downloaded a binary version of MySQL that includes support for BerkeleyDB, simply follow the instructions for installing a binary version of MySQL. See section 4.6 Installing a MySQL Binary Distribution. See section 15.2 mysqld-max, An extended mysqld server.

To compile MySQL with Berkeley DB support, download MySQL Version 3.23.34 or newer and configure MySQL with the --with-berkeley-db option. See section 4.7 Installing a MySQL Source Distribution.

cd /path/to/source/of/mysql-3.23.34
./configure --with-berkeley-db

Please refer to the manual provided with the BDB distribution for more updated information.

Even though Berkeley DB is in itself very tested and reliable, the MySQL interface is still considered beta quality. We are actively improving and optimizing it to get it stable very soon.

8.5.3 BDB startup options

If you are running with AUTOCOMMIT=0 then your changes in BDB tables will not be updated until you execute COMMIT. Instead of commit you can execute ROLLBACK to forget your changes. See section 7.31 BEGIN/COMMIT/ROLLBACK Syntax.

If you are running with AUTOCOMMIT=1 (the default), your changes will be committed immediately. You can start an extended transaction with the BEGIN WORK SQL command, after which your changes will not be committed until you execute COMMIT (or decide to ROLLBACK the changes).

The following options to mysqld can be used to change the behavior of BDB tables:

Option Meaning
--bdb-home=directory Base directory for BDB tables. This should be the same directory you use for --datadir.
--bdb-lock-detect=# Berkeley lock detect. One of (DEFAULT, OLDEST, RANDOM, or YOUNGEST).
--bdb-logdir=directory Berkeley DB log file directory.
--bdb-no-sync Don't synchronously flush logs.
--bdb-no-recover Don't start Berkeley DB in recover mode.
--bdb-shared-data Start Berkeley DB in multi-process mode (Don't use DB_PRIVATE when initializing Berkeley DB)
--bdb-tmpdir=directory Berkeley DB tempfile name.
--skip-bdb Don't use berkeley db.
-O bdb_max_lock=1000 Set the maximum number of locks possible. See section 7.28.4 SHOW VARIABLES.

If you use --skip-bdb, MySQL will not initialize the Berkeley DB library and this will save a lot of memory. Of course, you cannot use BDB tables if you are using this option.

Normally you should start mysqld without --bdb-no-recover if you intend to use BDB tables. This may, however, give you problems when you try to start mysqld if the BDB log files are corrupted. See section 4.16.2 Problems Starting the MySQL Server.

With bdb_max_lock you can specify the maximum number of locks (10000 by default) you can have active on a BDB table. You should increase this if you get errors of type bdb: Lock table is out of available locks or Got error 12 from ... when you have do long transactions or when mysqld has to examine a lot of rows to calculate the query.

You may also want to change binlog_cache_size and max_binlog_cache_size if you are using big multi-line transactions. See section 7.31 BEGIN/COMMIT/ROLLBACK Syntax.

8.5.4 Some characteristic of BDB tables:

8.5.5 Some things we need to fix for BDB in the near future:

8.5.6 Operating systems supported by BDB

If you after having built MySQL with support for BDB tables get the following error in the log file when you start mysqld:

bdb: architecture lacks fast mutexes: applications cannot be threaded
Can't init dtabases

This means that BDB tables are not supported for your architecture. In this case you have to rebuild MySQL without BDB table support.

NOTE: The following list is not complete; We will update this as we get more information about this.

Currently we know that BDB tables works with the following operating system.

It doesn't work with the following operating systems:

8.5.7 Errors You May Get When Using BDB Tables

8.6 GEMINI Tables

8.6.1 GEMINI Overview

GEMINI is a transaction-safe table handler for MySQL. It provides row-level locking, robust transaction support and reliable crash recovery. It is targeted for databases that need to handle heavy multi-user updates typical of transaction processing applications while still providing excellent performance for read-intensive operations. The GEMINI table type is developed and supported by NuSphere Corporation (see http://www.nusphere.com).

GEMINI provides full ACID transaction properties (Atomic, Consistent, Independent, and Durable) with a programming model that includes support for statement atomicity and all four standard isolation levels (Read Uncommitted, Read Committed, Repeatable Read, and Serializable) defined in the SQL standard.

The GEMINI tables support row-level and table-level locking to increase concurrency in applications and allow reading of tables without locking for maximum concurrency in a heavy update environment. The transaction, locking, and recovery mechanisms are tightly integrated to eliminate unnecessary administration overhead.

In general, if GEMINI tables are selected for an application, it is recommended that all tables updated in the application be GEMINI tables to provide well-defined system behavior. If non-GEMINI tables are mixed into the application then, ACID transaction properties cannot be maintained. While there are clearly cases where mixing table types is appropriate, it should always be done with careful consideration of the impact on transaction consistency and recoverability needs of the application and underlying database.

The GEMINI table type is derived from a successful commercial database and uses the storage kernel technology tightly integrated with MySQL server. The basic GEMINI technology is in use by millions of users worldwide in production environments today. This maturity allows GEMINI tables to provide a solution for those users who require transaction-based behavior as part of their applications.

The GEMINI table handler supports a configurable data cache that allows a significant portion of any database to be maintained in memory while still allowing durable updates. GEMINI Features

The following summarizes the major features provided by GEMINI tables. GEMINI Concepts

This section highlights some of the important concepts behind GEMINI and the GEMINI programming model, including:

These features are described below.

ACID Transactions

ACID in the context of transactions is an acronym which stands for Atomicity, Consistency, Isolation, Durability.

Atomicity @tab A transaction allows for the grouping of one or more changes to tables and rows in the database to form an atomic or indivisible operation. That is, either all of the changes occur or none of them do. If for any reason the transaction cannot be completed, everything this transaction changed can be restored to the state it was in prior to the start of the transaction via a rollback operation.
Consistency @tab Transactions always operate on a consistent view of the data and when they end always leave the data in a consistent state. Data may be said to be consistent as long as it conforms to a set of invariants, such as no two rows in the customer table have the same customer ID and all orders have an associated customer row. While a transaction executes, these invariants may be violated, but no other transaction will be allowed to see these inconsistencies, and all such inconsistencies will have been eliminated by the time the transaction ends.
Isolation @tab To a given transaction, it should appear as though it is running all by itself on the database. The effects of concurrently running transactions are invisible to this transaction, and the effects of this transaction are invisible to others until the transaction is committed.
Durability @tab Once a transaction is committed, its effects are guaranteed to persist even in the event of subsequent system failures. Until the transaction commits, not only are any changes made by that transaction not durable, but are guaranteed not to persist in the face of a system failures, as crash recovery will rollback their effects.


As stated above, a transaction is a group of work being done to data. Unless otherwise directed, MySQL considers each statement a transaction in itself. Multiple updates can be accomplished by placing them in a single statement, however they are limited to a single table.

Applications tend to require more robust use of transaction concepts. Take, for example, a system that processes an order: A row may be inserted in an order table, additional rows may be added to an order-line table, updates may be made to inventory tables, etc. It is important that if the order completes, all the changes are made to all the tables involved; likewise if the order fails, none of the changes to the tables must occur. To facilitate this requirement, MySQL has syntax to start a transaction called BEGIN WORK. All statements that occur after the BEGIN WORK statement are grouped into a single transaction. The end of this transaction occurs when a COMMIT or ROLLBACK statement is encountered. After the COMMIT or ROLLBACK the system returns back to the behavior before the BEGIN WORK statement was encountered where every statement is a transaction.

To permanently turn off the behavior where every statement is a transaction, MySQL added a variable called AUTOCOMMIT. The AUTOCOMMIT variable can have two values, 1 and 0. The mode where every statement is a transaction is when AUTOCOMMIT is set to 1 (AUTOCOMMIT=1). When AUTOCOMMIT is set to 0 (AUTOCOMMIT=0), then every statement is part of the same transaction until the transaction end by either COMMIT or ROLLBACK. Once a transaction completes, a new transaction is immediately started and the process repeats.

Here is an example of the SQL statements that you may find in a typical order:

     INSERT INTO order VALUES ...;
     INSERT INTO order-lines VALUES ...;
     INSERT INTO order-lines VALUES ...;
     INSERT INTO order-lines VALUES ...;
     UPDATE inventory WHERE ...;

This example shows how to use the BEGIN WORK statement to start a transaction. If the variable AUTOCOMMIT is set to 0, then a transaction would have been started already. In this case, the BEGIN WORK commits the current transaction and starts a new one.

Statement Atomicity

As mentioned above, when running with AUTOCOMMIT set to 1, each statement executes as a single transaction. When a statement has an error, then all changes make by the statement must be undone. Transactions support this behavior. Non-transaction safe table handlers would have a partial statement update where some of the changes from the statement would be contained in the database and other changes from the statement would not. Work would need to be done to manually recover from the error.


Transactions are the basis for database recovery. Recovery is what supports the Durability attribute of the ACID transaction.

GEMINI uses a separate file called the Recovery Log located in the $DATADIR directory named gemini.rl. This file maintains the integrity of all the GEMINI tables. GEMINI can not recover any data from non-GEMINI tables. In addition, the gemini.rl file is used to rollback transactions in support of the ROLLBACK statement.

In the event of a system failure, the next time the MySQL server is started, GEMINI will automatically go through its crash recovery process. The result of crash recovery is that all the GEMINI tables will contain the latest changes made to them, and all transactions that were open at the time of the crash will have been rolled back.

The GEMINI Recovery Log reuses space when it can. Space can be reused when information in the Recovery Log is no longer needed for crash recovery or rollback.

Isolation Levels

There are four isolation levels supported by GEMINI:

These isolation levels apply only to shared locks obtained by select statements, excluding select for update. Statements that get exclusive locks always retain those locks until the transaction commits or rolls back.

By default, GEMINI operates at the READ COMMITTED level. You can override the default using the following command:


If the SESSION qualifier used, the specified isolation level persists for the entire session. If the GLOBAL qualifier is used, the specified isolation level is applied to all new connections from this point forward. Note that the specified isolation level will not change the behavior for existing connections including the connection that exectues the SET GLOBAL TRANSACTION ISOLATION LEVEL statement.

READ UNCOMMITTED @tab Does not obtain any locks when reading rows. This means that if a row is locked by another process in a transaction that has a more strict isolation level, the READ UNCOMMITTED query will not wait until the locks are released before reading the row. You will get an error if attempt any updates while running at this isolation level.
READ COMMITTED @tab Locks the requested rows long enough to copy the row from the database block to the client row buffer. If a READ COMMITTED query finds that a row is locked exclusively by another process, it will wait until either the row has been released, or the lock timeout value has expired.
REPEATABLE READ @tab Locks all the rows needed to satisfy the query. These locks are held until the transaction ends (commits or rolls back). If a REPEATABLE READ query finds that a row is locked exclusively by another process, it will wait until either the row has been released, or the lock timeout value has expired.
SERIALIZABLE @tab Locks the table that contains the rows needed to satisfy the query. This lock is held until the transaction ends (commits or rolls back). If a SERIALIZABLE query finds that a row is exclusively locked by another process, it will wait until either the row has been released, or the lock timeout value has expired.

The statements that get exclusive locks are INSERT, UPDATE, DELETE and SELECT ... FOR UPDATE. Select statements without the FOR UPDATE qualifier get shared locks which allow other not ''for update'' select statements to read the same rows but block anyone trying to update the row from accessing it. Rows or tables with exclusive locks block all access to the row from other transactions until the transaction ends.

In general terms, the higher the Isolation level the more likelihood of having concurrent locks and therefore lock conflicts. In such cases, adjust the -O gemini_lock_table_size accordingly.

Row-Level Locking

GEMINI uses row locks, which allows high concurrency for requests on the same table.

In order to avoid lock table overflow, SQL statements that require applying locks to a large number of rows should either be run at the serializable isolation level or should be covered by a lock table statement.

Memory must be pre-allocated for the lock table. The mysqld server startup option -0 gemini_lock_table_size can be used to adjust the number of concurrent locks. GEMINI Limitations

The following limitations are in effect for the current version of GEMINI:

8.6.2 Using GEMINI Tables

This section explains the various startup options you can use with GEMINI tables, how to backup GEMINI tables, some performance considerations and sample configurations, and a brief discussion of when to use GEMINI tables.

Specifically, the topics covered in this section are: Startup Options

The table below lists options to mysqld that can be used to change the behavior of GEMINI tables.

--default-table-type=gemini @tab Sets the default table handler to be GEMINI. All create table statements will create GEMINI tables unless otherwise specified with TYPE=table-type. As noted above, there is currently a limitation with TEMPORARY tables using GEMINI.
--gemini-flush-log-at-commit @tab Forces the recovery log buffers to be flushed after every commit. This can have a serious performance penalty, so use with caution.
--gemini-recovery=FULL | NONE | FORCE @tab Sets the recovery mode. Default is FULL. NONE is useful for performing repeatable batch operations because the updates are not recorded in the recovery log. FORCE skips crash recovery upon startup; this corrupts the database, and should be used in emergencies only.
--gemini-unbuffered-io @tab All database writes bypass the OS cache. This can provide a performance boost on heavily updated systems where most of the dataset being worked on is cached in memory with the gemini_buffer_cache parameter.
--O gemini_buffer_cache=size @tab Amount of memory to allocate for database buffers, including Index and Record information. It is recommended that this number be 10% of the total size of all GEMINI tables. Do not exceed amount of memory on the system!
--O gemini_connection_limit=# @tab Maximum number of connections to GEMINI; default is 100. Each connection consumes about 1K of memory.
--O gemini_io_threads=# @tab Number of background I/O threads; default is 2. Increase the number when using --gemini-unbuffered-io
--O gemini_lock_table_size=# @tab Sets the maximum number of concurrent locks; default is 4096. Using SET [ GLOBAL | SESSION ] TRANSACTION ISOLATION = ... will determine how long a program will hold row locks.
--O gemini_lock_wait_timeout=seconds @tab Number of seconds to wait for record locks when performing queries; default is 10 seconds. Using SET [ GLOBAL | SESSION ] TRANSACTION ISOLATION = ... will determine how long a program will hold row locks.
--skip-gemini @tab Do not use GEMINI. If you use --skip-gemini, MySQL will not initialize the GEMINI table handler, saving memory; you cannot use GEMINI tables if you use --skip-gemini.
--transaction-isolation=READ-UNCOMMITTED | READ-COMMITTED | REPEATABLE-READ | SERIALIZABLE @tab Sets the GLOBAL transaction isolation level for all users that connect to the server; can be overridden with the SET ISOLATION LEVEL statement. Creating GEMINI Tables

GEMINI tables can be created by either using the CREATE TABLE syntax or the ALTER TABLE syntax.

See section 9 MySQL Tutorial, for more information on how to create and use MySQL tables. Backing Up GEMINI Tables

GEMINI supports both BACKUP TABLE and RESTORE TABLE syntax. To learn more about how to use BACKUP and RESTORE, see section 7.13 BACKUP TABLE Syntax and section 7.14 RESTORE TABLE Syntax.

To backup GEMINI tables outside of the MySQL environment, you must first shut down the MySQL server. Once the server is shut down, you can copy the files associated with GEMINI to a different location. The files that make up the GEMINI table handler are:

All the GEMINI files must be copied together. You can not copy just the .gmi and .gmd files to a different $DATADIR and have them become part of a new database. You can copy an entire $DATADIR directory to another location and start a MySQL server using the new $DATADIR. Restoring GEMINI Tables

To restore GEMINI tables outside of the MySQL environment, you must first shut down the MySQL server. Once the server is shut down, you can remove all GEMINI files in the target $DATADIR and then copy the files previously backed up into the $DATADIR directory.

As mentioned above, the files that make up the GEMINI table handler are:

When restoring a table, all the GEMINI files must be copied together. You can not restore just the .gmi and .gmd files. Using Auto_Increment Columns With GEMINI Tables

As mentioned previously, GEMINI tables support row-level and table-level locking to increase concurrency in applications and to allow reading of tables without locking for maximum concurrency in heavy update environments. This feature has several implications when working with auto_increment tables.

In MySQL, when a column is defined as an auto_increment column, and a row is inserted into the table with a NULL for the column, the auto_increment column is updated to be 1 higher than the highest value in the column.

With MyISAM tables, the auto_increment function is implemented by looking in the index and finding the highest value and adding 1 to it. This is possible because the entire ISAM table is locked during the update period and the increment value is therefore guaranteed to not be changing.

With GEMINI tables, the auto_increment function is implemented by maintaining a counter in a separate location from the table data. Instead of looking at the highest value in the table index, GEMINI tables look at this separately maintained counter. This means that in a transactional model, unlike the bottleneck inherent in the MyISAM approach, GEMINI users do not have to wait until the transaction that added the last value either commits or rollbacks before looking at the value.

Two side-effects of the GEMINI implementation are:

Note that if you delete the row containing the maximum value for an auto_increment column, the value will be reused with a GEMINI table but not with a MyISAM table.

See section 7.7 CREATE TABLE Syntax for more information about creating auto_increment columns. Performance Considerations

In addition to designing the best possible application, configuration of the data and the server startup parameters need to be considered. How the hardware is being used can have a dramatic affect on how fast the system will respond to queries. Disk Drives and Memory must both be considered.

Disk Drives

For best performance, you want to spread the data out over as many disks as possible. Using RAID 10 stripes work very well. If there are a lot of updates then the recovery log (gemini.rl) should be on a relatively quiet disk drive.

To spread the data out without using RAID 10, you can do the following:


The more data that can be placed in memory the faster the access to the data. Figure out how large the GEMINI data is by adding up the .gmd and .gmi file sizes. If you can, put at least 10% of the data into memory. You allocate memory for the rows and indexes by using the gemini_buffer_cache startup parameter. For example:

mysqld -O gemini_buffer_cache=800M

would allocate 800 MB of memory for the GEMINI buffer cache. Sample Configurations

Based on the performance considerations above, we can look at some examples for how to get the best performance out of the system when using GEMINI tables.

One CPU, 128MB memory, one disk drive @tab Allocate 80MB of memory for reading and updating GEMINI tables by starting the mysqld server with the following option:
-O gemini_buffer_cache=80M
Two CPUs, 512MB memory, four disk drives @tab Use RAID 10 to stripe the data across all available disks, or use the method described in the performance considerations section, above. Allocate 450MB of memory for reading/updating GEMINI tables:
-O gemini_buffer_cache=450M When To Use GEMINI Tables

Because the GEMINI table handler provides crash recovery and transaction support, there is extra overhead that is not found in other non-transaction safe table handlers. Here are some general guidelines for when to employ GEMINI and when to use other non-transaction safe tables (NTST).

Read-only @tab NTST @tab Less overhead and faster
Critical data @tab GEMINI @tab Crash recovery protection
High concurrency @tab GEMINI @tab Row-level locking
Heavy update @tab GEMINI @tab Row-level locking

The table below shows how a typical application schema could be defined.

account @tab Customer account data @tab GEMINI @tab Critical data, heavy update
order @tab Orders for a customer @tab GEMINI @tab Critical data, heavy update
orderline @tab Orderline detail for an order @tab GEMINI @tab Critical data, heavy update
invdesc @tab Inventory description @tab NTST @tab Read-only, frequent access
salesrep @tab Sales rep information @tab NTST @tab Infrequent update
inventory @tab Inventory information @tab GEMINI @tab High concurrency, critical data
config @tab System configuration @tab NTST @tab Read-only

8.7 InnoDB Tables

8.7.1 InnoDB tables overview

InnoDB tables are included in the MySQL source distribution starting from 3.23.34a and are activated in the MySQL -max binary.

If you have downloaded a binary version of MySQL that includes support for InnoDB (mysqld-max), simply follow the instructions for installing a binary version of MySQL. See section 4.6 Installing a MySQL Binary Distribution. See section 15.2 mysqld-max, An extended mysqld server.

To compile MySQL with InnoDB support, download MySQL-3.23.37 or newer and configure MySQL with the --with-innodb option. See section 4.7 Installing a MySQL Source Distribution.

cd /path/to/source/of/mysql-3.23.37
./configure --with-innodb

InnoDB provides MySQL with a transaction-safe table handler with commit, rollback, and crash recovery capabilities. InnoDB does locking on row level, and also provides an Oracle-style consistent non-locking read in SELECTS, which increases transaction concurrency. There is not need for lock escalation in InnoDB, because row level locks in InnoDB fit in very small space.

InnoDB has been designed for maximum performance when processing large data volumes. Its CPU efficiency is probably not matched by any other disk-based relational database engine.

You can find the latest information about InnoDB at http://www.innodb.com. The most up-to-date version of the InnoDB manual is always placed there, and you can also order commercial support for InnoDB.

Technically, InnoDB is a database backend placed under MySQL. InnoDB has its own buffer pool for caching data and indexes in main memory. InnoDB stores its tables and indexes in a tablespace, which may consist of several files. This is different from, for example, MyISAM tables where each table is stored as a separate file.

InnoDB is distributed under the GNU GPL License Version 2 (of June 1991). In the source distribution of MySQL, InnoDB appears as a subdirectory.

8.7.2 InnoDB startup options

Beginning from MySQL-3.23.37 the prefix of the options is changed from innobase_... to innodb_....

To use InnoDB tables you MUST specify configuration parameters in the MySQL configuration file in the [mysqld] section of the configuration file `my.cnf'. See section 4.16.5 Option Files.

The only required parameter to use InnoDB is innodb_data_file_path, but you should set others if you want to get a better performance.

Suppose you have a Windows NT machine with 128 MB RAM and a single 10 GB hard disk. Below is an example of possible configuration parameters in `my.cnf' for InnoDB:

innodb_data_file_path = ibdata1:2000M;ibdata2:2000M
innodb_data_home_dir = c:\ibdata
set-variable = innodb_mirrored_log_groups=1
innodb_log_group_home_dir = c:\iblogs
set-variable = innodb_log_files_in_group=3
set-variable = innodb_log_file_size=30M
set-variable = innodb_log_buffer_size=8M
innodb_log_arch_dir = c:\iblogs
set-variable = innodb_buffer_pool_size=80M
set-variable = innodb_additional_mem_pool_size=10M
set-variable = innodb_file_io_threads=4
set-variable = innodb_lock_wait_timeout=50

Suppose you have a Linux machine with 512 MB RAM and three 20 GB hard disks (at directory paths `/', `/dr2' and `/dr3'). Below is an example of possible configuration parameters in `my.cnf' for InnoDB:

innodb_data_file_path = ibdata/ibdata1:2000M;dr2/ibdata/ibdata2:2000M
innodb_data_home_dir = /
set-variable = innodb_mirrored_log_groups=1
innodb_log_group_home_dir = /dr3
set-variable = innodb_log_files_in_group=3
set-variable = innodb_log_file_size=50M
set-variable = innodb_log_buffer_size=8M
innodb_log_arch_dir = /dr3/iblogs
set-variable = innodb_buffer_pool_size=400M
set-variable = innodb_additional_mem_pool_size=20M
set-variable = innodb_file_io_threads=4
set-variable = innodb_lock_wait_timeout=50

Note that we have placed the two data files on different disks. The reason for the name innodb_data_file_path is that you can also specify paths to your data files, and innodb_data_home_dir is just textually catenated before your data file paths, adding a possible slash or backslash in between. InnoDB will fill the tablespace formed by the data files from bottom up. In some cases it will improve the performance of the database if all data is not placed on the same physical disk. Putting log files on a different disk from data is very often beneficial for performance.

The meanings of the configuration parameters are the following:

innodb_data_home_dir The common part of the directory path for all innobase data files.
innodb_data_file_path Paths to individual data files and their sizes. The full directory path to each data file is acquired by concatenating innodb_data_home_dir to the paths specified here. The file sizes are specified in megabytes, hence the 'M' after the size specification above. Do not set a file size bigger than 4000M, and on most operating systems not bigger than 2000M. InnoDB also understands the abbreviation 'G', 1G meaning 1024M. The sum of the sizes of the files must be at least 10 MB.
innodb_mirrored_log_groups Number of identical copies of log groups we keep for the database. Currently this should be set to 1.
innodb_log_group_home_dir Directory path to InnoDB log files.
innodb_log_files_in_group Number of log files in the log group. InnoDB writes to the files in a circular fashion. Value 3 is recommended here.
innodb_log_file_size Size of each log file in a log group in megabytes. Sensible values range from 1M to the size of the buffer pool specified below. The bigger the value, the less checkpoint flush activity is needed in the buffer pool, saving disk i/o. But bigger log files also mean that recovery will be slower in case of a crash. File size restriction as for a data file.
innodb_log_buffer_size The size of the buffer which InnoDB uses to write log to the log files on disk. Sensible values range from 1M to half the combined size of log files. A big log buffer allows large transactions to run without a need to write the log to disk until the transaction commit. Thus, if you have big transactions, making the log buffer big will save disk i/o.
innodb_flush_log_at_trx_commit Normally this is set to 1, meaning that at a transaction commit the log is flushed to disk, and the modifications made by the transaction become permanent, and survive a database crash. If you are willing to compromise this safety, and you are running small transactions, you may set this to 0 to reduce disk i/o to the logs.
innodb_log_arch_dir The directory where fully written log files would be archived if we used log archiving. The value of this parameter should currently be set the same as innodb_log_group_home_dir.
innodb_log_archive This value should currently be set to 0. As recovery from a backup is done by MySQL using its own log files, there is currently no need to archive InnoDB log files.
innodb_buffer_pool_size The size of the memory buffer InnoDB uses to cache data and indexes of its tables. The bigger you set this the less disk i/o is needed to access data in tables. On a dedicated database server you may set this parameter up to 90 % of the machine physical memory size. Do not set it too large, though, because competition of the physical memory may cause paging in the operating system.
innodb_additional_mem_pool_size Size of a memory pool InnoDB uses to store data dictionary information and other internal data structures. A sensible value for this might be 2M, but the more tables you have in your application the more you will need to allocate here. If InnoDB runs out of memory in this pool, it will start to allocate memory from the operating system, and write warning messages to the MySQL error log.
innodb_file_io_threads Number of file i/o threads in InnoDB. Normally, this should be 4, but on Windows NT disk i/o may benefit from a larger number.
innodb_lock_wait_timeout Timeout in seconds an InnoDB transaction may wait for a lock before being rolled back. InnoDB automatically detects transaction deadlocks in its own lock table and rolls back the transaction. If you use LOCK TABLES command, or other transaction-safe table handlers than InnoDB in the same transaction, then a deadlock may arise which InnoDB cannot notice. In cases like this the timeout is useful to resolve the situation.
innodb_unix_file_flush_method (Available from 3.23.39 up.) The default value for this is fdatasync. Another option is O_DSYNC. Options littlesync and nosync have the risk that in an operating system crash or a power outage you may easily end up with a half-written database page, and you have to do a recovery from a backup. See the section "InnoDB performance tuning", item 6, below for tips on how to set this parameter. If you are happy with your database performance it is wisest not to specify this parameter at all, in which case it will get the default value.

8.7.3 Creating InnoDB table space

Suppose you have installed MySQL and have edited `my.cnf' so that it contains the necessary InnoDB configuration parameters. Before starting MySQL you should check that the directories you have specified for InnoDB data files and log files exist and that you have access rights to those directories. InnoDB cannot create directories, only files. Check also you have enough disk space for the data and log files.

When you now start MySQL, InnoDB will start creating your data files and log files. InnoDB will print something like the following:

~/mysqlm/sql > mysqld
InnoDB: The first specified data file /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: Data file /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 c
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 c
InnoDB: Setting log file /home/heikki/data/logs/ib_logfile1 size to 5242880
InnoDB: Log file /home/heikki/data/logs/ib_logfile2 did not exist: new to be c
InnoDB: Setting log file /home/heikki/data/logs/ib_logfile2 size to 5242880
InnoDB: Started
mysqld: ready for connections

A new InnoDB database has now been created. 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', InnoDB output will be like the following:

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

You can now look at the data files and logs directories and you will see the files created. The log directory will also contain a small file named `ib_arch_log_0000000000'. That file resulted from the database creation, after which InnoDB switched off log archiving. When MySQL is again started, the output will be like the following:

~/mysqlm/sql > mysqld
InnoDB: Started
mysqld: ready for connections If something goes wrong in database creation

If something goes wrong in an InnoDB database creation, you should delete all files created by InnoDB. This means all data files, all log files, the small archived log file, and in the case you already did create some InnoDB tables, delete also the corresponding `.frm' files for these tables from the MySQL database directories. Then you can try the InnoDB database creation again.

8.7.4 Creating InnoDB tables

Suppose you have started the MySQL client with the command mysql test. To create a table in the InnoDB format you must specify TYPE = InnoDB in the table creation SQL command:


This SQL command will create a table and an index on column A into the InnoDB tablespace consisting of the data files you specified in `my.cnf'. In addition MySQL will create a file `CUSTOMER.frm' to the MySQL database directory `test'. Internally, InnoDB will add to its own data dictionary an entry for table 'test/CUSTOMER'. Thus you can create a table of the same name CUSTOMER in another database of MySQL, and the table names will not collide inside InnoDB.

You can query the amount of free space in the InnoDB tablespace by issuing the table status command of MySQL for any table you have created with TYPE = InnoDB. Then the amount of free space in the tablespace appears in the table comment section in the output of SHOW. An example:


Note that the statistics SHOW gives about InnoDB tables are only approximate: they are used in SQL optimization. Table and index reserved sizes in bytes are accurate, though.

NOTE: DROP DATABASE does not currently work for InnoDB tables! You must drop the tables individually. Also take care not to delete or add `.frm' files to your InnoDB database manually: use CREATE TABLE and DROP TABLE commands. InnoDB has its own internal data dictionary, and you will get problems if the MySQL `.frm' files are out of 'sync' with the InnoDB internal data dictionary. Converting MyISAM tables to InnoDB

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

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

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

After all data has been inserted you can rename the tables.

During the conversion of big tables you should set the InnoDB buffer pool size big to reduce disk i/o. Not bigger than 80 % of the physical memory, though. You should set InnoDB log files big, and also the log buffer large.

Make sure you do not run out of tablespace: InnoDB tables take a lot more space than MyISAM tables. If an ALTER TABLE runs out of space, it will start a rollback, and that can take hours if it is disk-bound. In inserts InnoDB uses the insert buffer to merge secondary index records to indexes in batches. That saves a lot of disk i/o. In 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 is better that you kill the database process and delete all InnoDB data and log files and all InnoDB table `.frm' files, and start your job again, rather than wait for millions of disk i/os to complete.

8.7.5 Adding and removing InnoDB data and log files

You cannot increase the size of an InnoDB data file. To add more into your tablespace you have to add a new data file. To do this you have to shut down your MySQL database, edit the `my.cnf' file, adding a new file to innodb_data_file_path, and then start MySQL again.

Currently you cannot remove a data file from InnoDB. To decrease the size of your database you have to use mysqldump to dump all your tables, create a new database, and import your tables to the new database.

If you want to change the number or the size of your InnoDB log files, you have to shut down MySQL and make sure that it shuts down without errors. Then copy the old log files into a safe place just in case something went wrong in the shutdown and you will need them to recover the database. Delete then the old log files from the log file directory, edit `my.cnf', and start MySQL again. InnoDB will tell you at the startup that it is creating new log files.

8.7.6 Backing up and recovering an InnoDB database

The key to safe database management is taking regular backups. To take a 'binary' backup of your database you have to do the following:

There is currently no on-line or incremental backup tool available for InnoDB, though they are in the TODO list.

In addition to taking the binary backups described above, you should also regularly take dumps of your tables with `mysqldump'. The reason to this is that a binary file may be corrupted without you noticing it. Dumped tables are stored into text files which are human-readable and much simpler than database binary files. Seeing table corruption from dumped files is easier, and since their format is simpler, the chance for serious data corruption in them is smaller.

A good idea is to take the dumps at the same time you take a binary backup of your database. You have to shut out all clients from your database to get a consistent snapshot of all your tables into your dumps. Then you can take the binary backup, and you will then have a consistent snapshot of your database in two formats.

To be able to recover your InnoDB database to the present from the binary backup described above, you have to run your MySQL database with the general logging and log archiving of MySQL switched on. Here by the general logging we mean the logging mechanism of the MySQL server which is independent of InnoDB logs.

To recover from a crash of your MySQL server process, the only thing you have to do is to restart it. InnoDB will automatically check the logs and perform a roll-forward of the database to the present. InnoDB will automatically roll back uncommitted transactions which were present at the time of the crash. During recovery, InnoDB will print out something like the following:

~/mysqlm/sql > mysqld
InnoDB: Database was not shut down normally.
InnoDB: Starting recovery from log files...
InnoDB: Starting log scan based on checkpoint at
InnoDB: log sequence number 0 13674004
InnoDB: Doing recovery: scanned up to log sequence number 0 13739520
InnoDB: Doing recovery: scanned up to log sequence number 0 13805056
InnoDB: Doing recovery: scanned up to log sequence number 0 13870592
InnoDB: Doing recovery: scanned up to log sequence number 0 13936128
InnoDB: Doing recovery: scanned up to log sequence number 0 20555264
InnoDB: Doing recovery: scanned up to log sequence number 0 20620800
InnoDB: Doing recovery: scanned up to log sequence number 0 20664692
InnoDB: 1 uncommitted transaction(s) which must be rolled back
InnoDB: Starting rollback of uncommitted transactions
InnoDB: Rolling back trx no 16745
InnoDB: Rolling back of trx no 16745 completed
InnoDB: Rollback of uncommitted transactions completed
InnoDB: Starting an apply batch of log records to the database...
InnoDB: Apply batch completed
InnoDB: Started
mysqld: ready for connections

If your database gets corrupted or your disk fails, you have to do the recovery from a backup. In the case of corruption, you should first find a backup which is not corrupted. From a backup do the recovery from the general log files of MySQL according to instructions in the MySQL manual. Checkpoints

InnoDB implements a checkpoint mechanism called a fuzzy checkpoint. InnoDB will flush 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 for a while.

In 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 already present on the disk image of the database. Then InnoDB scans the log files forward from the place of the checkpoint applying the logged modifications to the database.

InnoDB writes to the log files in a circular fashion. All committed modifications which 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 in the circular fashion, it has to make sure that the database page images on disk already contain the modifications logged in the log file InnoDB is going to reuse. In other words, InnoDB has to make a checkpoint and often this involves flushing of modified database pages to disk.

The above explains why making your log files very big may save disk i/o in checkpointing. It can make sense to set the total size of the log files as big as the buffer pool or even bigger. The drawback in big log files is that crash recovery can last longer because there will be more log to apply to the database.

8.7.7 Moving an InnoDB database to another machine

InnoDB data and log files are binary-compatible on all platforms if the floating point number format on the machines is the same. You can move an InnoDB database simply by copying all the relevant files, which we already listed in the previous section on backing up a database. If the floating point formats on the machines are different but you have not used FLOAT or DOUBLE data types in your tables then the procedure is the same: just copy the relevant files. If the formats are different and your tables contain floating point data, you have to use `mysqldump' and `mysqlimport' to move those tables.

A performance tip is to switch off the auto commit when you import data into your database, assuming your tablespace has enough space for the big rollback segment the big import transaction will generate. Do the commit only after importing a whole table or a segment of a table.

8.7.8 InnoDB transaction model

In the InnoDB transaction model the goal has been to combine the best sides of a multiversioning database to traditional two-phase locking. InnoDB does locking on row level and runs queries by default as non-locking consistent reads, in the style of Oracle. The lock table in InnoDB is stored so space-efficiently that lock escalation is not needed: typically several users are allowed to lock every row in the database, or any random subset of the rows, without InnoDB running out of memory.

In InnoDB all user activity happens inside transactions. If the auto commit mode is used in MySQL, then each SQL statement will form a single transaction. If the auto commit mode is switched off, then we can think that a user always has a transaction open. If he issues the SQL COMMIT or ROLLBACK statement, that ends the current transaction, and a new starts. Both statements will release all InnoDB locks that were set during the current transaction. A COMMIT means that the changes made in the current transaction are made permanent and become visible to other users. A ROLLBACK on the other hand cancels all modifications made by the current transaction. Consistent read

A consistent read means that InnoDB uses its multiversioning to present to a query a snapshot of the database at a point in time. The query will see the changes made by exactly those 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 will see the changes made by the transaction itself which issues the query.

When a transaction issues its first consistent read, InnoDB assigns the snapshot, or the point of time, which all consistent reads in the same transaction will use. In the snapshot are all transactions that committed before assigning the snapshot. Thus the consistent reads within the same transaction will also be consistent with respect to each other. You can get a fresher snapshot for your queries by committing the current transaction and after that issuing new queries.

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

A consistent read is not convenient in some circumstances. Suppose you want to add a new row into your table CHILD, and make sure that the child already has a parent in table PARENT.

Suppose you use a consistent read to read the table PARENT and indeed see the parent of the child in the table. Can you now safely add the child row to table CHILD? No, because it may happen that meanwhile some other user has deleted the parent row from the table PARENT, and you are not aware of that.

The solution is to perform the SELECT in a locking mode, LOCK IN SHARE MODE.


Performing a read in share mode means that we read the latest available data, and set a shared mode lock on the rows we read. If the latest data belongs to a yet uncommitted transaction of another user, we will wait until that transaction commits. A shared mode lock prevents others from updating or deleting the row we have read. After we see that the above query returns the parent 'Jones', we can safely add his child to table CHILD, and commit our transaction. This example shows how to implement referential integrity in your application code.

Let us look at another example: we have an integer counter field in a table CHILD_CODES which we use to assign a unique identifier to each child we add to table CHILD. Obviously, using a consistent read or a shared mode read to read the present value of the counter is not a good idea, since then two users of the database may see the same value for the counter, and we will get a duplicate key error when we add the two children with the same identifier to the table.

In this case there are two good ways to implement the reading and incrementing of the counter: (1) update the counter first by incrementing it by 1 and only after that read it, or (2) read the counter first with a lock mode FOR UPDATE, and increment after that:


A SELECT ... FOR UPDATE will read 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. Next-key locking: avoiding the phantom problem

In row level locking InnoDB uses an algorithm called next-key locking. InnoDB does the row level locking so that when it searches or scans an index of a table, it sets shared or exclusive locks on the index records in encounters. Thus the row level locks are more precisely called index record locks.

The locks InnoDB sets on index records also affect the 'gap' before that index record. If a user has a shared or exclusive lock on record R in an index, then another user cannot insert a new index record immediately before R in the index order. This locking of gaps is done to prevent the so-called phantom problem. Suppose I want to read and lock all children with identifier bigger than 100 from table CHILD, and update some field in the selected rows.


Suppose there is an index on table CHILD on column ID. Our query will scan that index starting from the first record where ID is bigger than 100. Now, if the locks set on the index records would not lock out inserts made in the gaps, a new child might meanwhile be inserted to the table. If now I in my transaction execute


again, I will see a new child in the result set the query returns. This is against the isolation principle of transactions: a transaction should be able to run so that the data it has read does not change during the transaction. If we regard a set of rows as a data item, then the new 'phantom' child would break this isolation principle.

When InnoDB scans an index it can also lock the gap after the last record in the index. Just that happens in the previous example: the locks set by InnoDB will prevent any insert to the table where ID would be bigger than 100.

You can use the 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 will prevent 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. Locks set by different SQL statements in InnoDB Deadlock detection and rollback

InnoDB automatically detects a deadlock of transactions and rolls back the transaction whose lock request was the last one to build a deadlock, that is, a cycle in the waits-for graph of transactions. InnoDB cannot detect deadlocks where a lock set by a MySQL LOCK TABLES statement is involved, or if a lock set in another table handler than InnoDB is involved. You have to resolve these situations using innodb_lock_wait_timeout set in `my.cnf'.

When InnoDB performs a complete rollback of a transaction, all the locks of 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 SQL statement may be preserved. This is because InnoDB stores row locks in a format where it cannot afterwards know which was set by which SQL statement.

8.7.9 Performance tuning tips

1. If the Unix `top' or the Windows `Task Manager' shows that the CPU usage percentage with your workload is less than 70 %, your workload is probably disk-bound. Maybe you are making too many transaction commits, or the buffer pool is too small. Making the buffer pool bigger can help, but do not set it bigger than 80 % of physical memory.

2. Wrap several modifications into one transaction. InnoDB must flush the log to disk at each transaction commit, if that transaction made modifications to the database. Since the rotation speed of a disk is typically at most 167 revolutions/second, that constrains the number of commits to the same 167/second if the disk does not fool the operating system.

3. If you can afford the loss of some latest committed transactions, you can set the `my.cnf' parameter innodb_flush_log_at_trx_commit to zero. InnoDB tries to flush the log anyway once in a second, though the flush is not guaranteed.

4. Make your log files big, even as big as the buffer pool. When InnoDB has written the log files full, it has to write the modified contents of the buffer pool to disk in a checkpoint. Small log files will cause many unnecessary disk writes. The drawback in big log files is that recovery time will be longer.

5. Also the log buffer should be quite big, say 8 MB.

6. (Relevant from 3.23.39 up.) In some versions of Linux and Unix, flushing files to disk with the Unix fdatasync and other similar methods is surprisingly slow. The default method InnoDB uses is the fdatasync function. If you are not satisfied with the database write performance, you may try setting innodb_unix_file_flush_method in `my.cnf' to O_DSYNC, though O_DSYNC seems to be slower on most systems. You can also try setting it to littlesync, which means that InnoDB does not call the file flush for every write it does to a file, but only in log flush at transaction commits and data file flush at a checkpoint. The drawback in littlesync is that if the operating system crashes, you can easily end up with a half-written database page, and you have to do a recovery from a backup. With nosync you have even less safety: InnoDB will only flush the database files to disk at database shutdown

7. In importing data to InnoDB, make sure that MySQL does not have autocommit=1 on. Then every insert requires a log flush to disk. Put before your plain SQL import file line

set autocommit=0;

and after it


If you use the `mysqldump' option --opt, you will get dump files which are fast to import also to an InnoDB table, even without wrapping them to the above set autocommit=0; ... commit; wrappers.

8. Beware of big rollbacks of mass inserts: InnoDB uses the insert buffer to save disk i/o in inserts, but in a corresponding rollback no such mechanism is used. A disk-bound rollback can take 30 times the time of the corresponding insert. Killing the database process will not help because the rollback will start again at the database startup. The only way to get rid of a runaway rollback is to increase the buffer pool so that the rollback becomes CPU-bound and runs fast, or delete the whole InnoDB database.

9. Beware also of other big disk-bound operations. Use DROP TABLE or TRUNCATE (from MySQL-4.0 up) to empty a table, not DELETE FROM yourtable.

10. Use the multi-line INSERT to reduce communication overhead between the client and the server if you need to insert many rows:

INSERT INTO yourtable VALUES (1, 2), (5, 5);

This tip is of course valid for inserts into any table type, not just InnoDB.

8.7.10 Implementation of multiversioning

Since InnoDB is a multiversioned database, it must keep information of old versions of rows in the tablespace. This information is stored in a data structure we call a rollback segment after an analogous data structure in Oracle.

InnoDB internally adds two fields to each row stored in the database. A 6-byte field tells the transaction identifier for the last transaction which inserted or updated the row. Also a deletion is internally treated as an update where a special bit in the row is set to mark it as deleted. Each row also contains a 7-byte field called the roll pointer. The roll pointer points to an undo log record written to the rollback segment. If the row was updated, then the undo log record contains the information necessary to rebuild the content of the row before it was updated.

InnoDB uses the information in the rollback segment to perform the undo operations needed in a transaction rollback. It also uses the information to build earlier versions of a row for a consistent read.

Undo logs in the rollback segment are divided into insert and update undo logs. Insert undo logs are only needed in transaction rollback and can be discarded as soon as the transaction commits. Update undo logs are used also in consistent reads, and they can be discarded only after there is no transaction present for which InnoDB has assigned a snapshot that in a consistent read could need the information in the update undo log to build an earlier version of a database row.

You must remember to commit your transactions regularly. Otherwise InnoDB cannot discard data from the update undo logs, and the rollback segment may grow too big, filling up your tablespace.

The physical size of an undo log record in the rollback segment is typically smaller than the corresponding inserted or updated row. You can use this information to calculate the space need for your rollback segment.

In our multiversioning scheme a row is not physically removed from the database immediately when you delete it with an SQL statement. Only when InnoDB can discard the update undo log record written for the deletion, it can also physically remove the corresponding row and its index records from the database. This removal operation is called a purge, and it is quite fast, usually taking the same order of time as the SQL statement which did the deletion.

8.7.11 Table and index structures

Every InnoDB table has a special index called the clustered index where the data of the rows is stored. If you define a PRIMARY KEY on your table, then the index of the primary key will be the clustered index.

If you do not define a primary key for your table, InnoDB will internally generate a clustered index where the rows are ordered by the row id InnoDB assigns to the rows in such a table. The row id is a 6-byte field which monotonically increases as new rows are inserted. Thus the rows ordered by the row id will be physically in the insertion order.

Accessing a row through the clustered index is fast, because the row data will be on the same page where the index search leads us. In many databases the data is traditionally stored on a different page from the index record. If a table is large, the clustered index architecture often saves a disk i/o when compared to the traditional solution.

The records in non-clustered indexes (we also call them secondary indexes), in InnoDB contain the primary key value for the row. InnoDB uses this primary key value to search for the row from the clustered index. Note that if the primary key is long, the secondary indexes will use more space. Physical structure of an index

All indexes in InnoDB are B-trees where the index records are stored in the leaf pages of the tree. The default size of an index page is 16 kB. 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 (ascending or descending) order, the resulting index pages will be about 15/16 full. If records are inserted in a random order, then the pages will be 1/2 - 15/16 full. If the fillfactor of an index page drops below 1/2, InnoDB will try to contract the index tree to free the page. Insert buffering

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

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

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

The insert buffer is periodically merged to the secondary index trees in the database. Often we can merge several insertions on the same page in of the index tree, and hence save disk i/o's. It has been measured that the insert buffer can speed up insertions to a table up to 15 times. Adaptive hash indexes

If a database fits almost entirely in main memory, then the fastest way to perform queries on it is to use hash indexes. InnoDB has an automatic mechanism which monitors index searches made to the indexes defined for a table, and if InnoDB notices that queries could benefit from building of a hash index, such an index is automatically built.

But note that 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 what search pattern InnoDB observes on 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 will build hash indexes on demand to those pages of the index which are often accessed.

In a sense, through the adaptive hash index mechanism InnoDB adapts itself to ample main memory, coming closer to the architecture of main memory databases. Physical record structure How an auto-increment column works in InnoDB

After a database startup, when a user first does an insert to a table T where an auto-increment column has been defined, and the user does not provide an explicit value for the column, then InnoDB executes SELECT MAX(auto-inc-column) FROM T, and assigns that value incremented by one to the the column and the auto-increment counter of the table. We say that the auto-increment counter for table T has been initialized.

InnoDB follows the same procedure in initializing the auto-increment counter for a freshly created table.

Note that if the user specifies in an insert the value 0 to the auto-increment column, then InnoDB treats the row like the value would not have been specified.

After the auto-increment counter has been initialized, if a user inserts a row where he explicitly specifies the column value, and the value is bigger than the current counter value, then the counter is set to the specified column value. If the user does not explicitly specify a value, then InnoDB increments the counter by one and assigns its new value to the column.

The auto-increment mechanism, when assigning values from the counter, bypasses locking and transaction handling. Therefore you may also get gaps in the number sequence if you roll back transactions which have got numbers from the counter.

The behavior of auto-increment is not defined if a user gives a negative value to the column or if the value becomes bigger than the maximum integer that can be stored in the specified integer type.

8.7.12 File space management and disk i/o Disk i/o

In disk i/o InnoDB uses asynchronous i/o. On Windows NT it uses the native asynchronous i/o provided by the operating system. On Unix, InnoDB uses simulated asynchronous i/o built into InnoDB: InnoDB creates a number of i/o threads to take care of i/o operations, such as read-ahead. In a future version we will add support for simulated aio on Windows NT and native aio on those versions of Unix which have one.

On Windows NT InnoDB uses non-buffered i/o. That means that the disk pages InnoDB reads or writes are not buffered in the operating system file cache. This saves some memory bandwidth.

You can also use a raw disk in InnoDB, though this has not been tested yet: just define the raw disk in place of a data file in `my.cnf'. You must give the exact size in bytes of the raw disk in `my.cnf', because at startup InnoDB checks that the size of the file is the same as specified in the configuration file. Using a raw disk you can on some versions of Unix perform non-buffered i/o.

There are two read-ahead heuristics in InnoDB: sequential read-ahead and random read-ahead. In sequential read-ahead InnoDB notices that the access pattern to a segment in the tablespace is sequential. Then InnoDB will post in advance a batch of reads of database pages to the i/o system. In random read-ahead InnoDB notices that some area in a tablespace seems to be in the process of being fully read into the buffer pool. Then InnoDB posts the remaining reads to the i/o system. File space management

The data files you define in the configuration file form the tablespace of InnoDB. The files are simply catenated to form the tablespace, there is no striping in use. Currently you cannot directly instruct where the space is allocated for your tables, except by using the following fact: from a newly created tablespace InnoDB will allocate space starting from the low end.

The tablespace consists of database pages whose default size is 16 kB. The pages are grouped into extents of 64 consecutive pages. The 'files' inside a tablespace are called segments in InnoDB. The name of the rollback segment is somewhat misleading because it actually contains many segments in the tablespace.

For each index in InnoDB we allocate two segments: one is for non-leaf nodes of the B-tree, the other is for the leaf nodes. The idea here is to achieve better sequentiality for the leaf nodes, which contain the data.

When a segment grows inside the tablespace, InnoDB allocates the first 32 pages to it individually. After that InnoDB starts to allocate whole extents to the segment. InnoDB can add to a large segment up to 4 extents at a time to ensure good sequentiality of data.

Some pages in the tablespace contain bitmaps of other pages, and therefore a few extents in an InnoDB tablespace cannot be allocated to segments as a whole, but only as individual pages.

When you issue a query SHOW TABLE STATUS FROM ... LIKE ... to ask for available free space in the tablespace, InnoDB will report you the space which is certainly usable in totally free extents of the tablespace. InnoDB always reserves some extents for clean-up and other internal purposes; these reserved extents are not included in the free space.

When you delete data from a table, InnoDB will contract the corresponding B-tree indexes. It depends on the pattern of deletes if that frees individual pages or extents to the tablespace, so that the freed space is available for other users. Dropping a table or deleting all rows from it is guaranteed to release the space to other users, but remember that deleted rows can be physically removed only in a purge operation after they are no longer needed in transaction rollback or consistent read. Defragmenting a table

If there are random insertions or deletions in the indexes of a table, the indexes may become fragmented. By fragmentation we mean that the physical ordering of the index pages on the disk is not close to the alphabetical ordering of the records on the pages, or that there are many unused pages in the 64-page blocks which were allocated to the index.

It can speed up index scans if you periodically use mysqldump to dump the table to a text file, drop the table, and reload it from the dump. Another way to do the defragmenting is to ALTER the table type to MyISAM and back to InnoDB again. Note that a MyISAM table must fit in a single file on your operating system.

If the insertions to and index are always ascending and records are deleted only from the end, then the the file space management algorithm of InnoDB guarantees that fragmentation in the index will not occur.

8.7.13 Error handling

The error handling in InnoDB is not always the same as specified in the ANSI SQL standards. According to the ANSI standard, any error during an SQL statement should cause the rollback of that statement. InnoDB sometimes rolls back only part of the statement. The following list specifies the error handling of InnoDB.

8.7.14 Some restrictions on InnoDB tables

8.7.15 InnoDB contact information

Contact information of Innobase Oy, producer of the InnoDB engine. Website: http://www.innodb.com. Email: Heikki.Tuuri@innodb.com

phone: 358-9-6969 3250 (office) 358-40-5617367 (mobile)
InnoDB Oy Inc.
World Trade Center Helsinki
Aleksanterinkatu 17
P.O.Box 800
00101 Helsinki

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