Table of Contents
MyISAM
Storage EngineInnoDB
Storage EngineInnoDB
OverviewInnoDB
Contact InformationInnoDB
ConfigurationInnoDB
Startup Options and System VariablesInnoDB
TablespaceInnoDB
TablesInnoDB
Data and Log FilesInnoDB
DatabaseInnoDB
Database to Another MachineInnoDB
Transaction Model and LockingInnoDB
Performance Tuning TipsInnoDB
Table and Index StructuresInnoDB
File Space Management and Disk I/OInnoDB
Error HandlingInnoDB
TablesInnoDB
TroubleshootingMERGE
Storage EngineMEMORY
(HEAP
) Storage EngineBDB
(BerkeleyDB
) Storage
EngineEXAMPLE
Storage EngineFEDERATED
Storage EngineARCHIVE
Storage EngineCSV
Storage EngineBLACKHOLE
Storage EngineMySQL supports several storage engines that act as handlers for different table types. MySQL storage engines include both those that handle transaction-safe tables and those that handle non-transaction-safe tables:
MyISAM
manages non-transactional tables. It
provides high-speed storage and retrieval, as well as fulltext
searching capabilities. MyISAM
is supported
in all MySQL configurations, and is the default storage engine
unless you have configured MySQL to use a different one by
default.
The MEMORY
storage engine provides in-memory
tables. The MERGE
storage engine allows a
collection of identical MyISAM
tables to be
handled as a single table. Like MyISAM
, the
MEMORY
and MERGE
storage
engines handle non-transactional tables, and both are also
included in MySQL by default.
The MEMORY
storage engine formerly was
known as the HEAP
engine.
The InnoDB
and BDB
storage
engines provide transaction-safe tables.
InnoDB
is included by default in all MySQL
5.0 binary distributions. In source distributions,
you can enable or disable either engine by configuring MySQL as
you like.
The EXAMPLE
storage engine is a
“stub” engine that does nothing. You can create
tables with this engine, but no data can be stored in them or
retrieved from them. The purpose of this engine is to serve as
an example in the MySQL source code that illustrates how to
begin writing new storage engines. As such, it is primarily of
interest to developers.
NDB Cluster
is the storage engine used by
MySQL Cluster to implement tables that are partitioned over many
computers. It is available in MySQL 5.0 binary
distributions. This storage engine is currently supported on a
number of Unix platforms. We intend to add support for this
engine on other platforms, including Windows, in future MySQL
releases.
MySQL Cluster is covered in a separate chapter of this Manual. See Chapter 16, MySQL Cluster, for more information.
The ARCHIVE
storage engine is used for
storing large amounts of data without indexes with a very small
footprint.
The CSV
storage engine stores data in text
files using comma-separated values format.
The BLACKHOLE
storage engine accepts but does
not store data and retrievals always return an empty set.
The FEDERATED
storage engine was added in
MySQL 5.0.3. This engine stores data in a remote database.
Currently, it works with MySQL only, using the MySQL C Client
API. In future releases, we intend to enable it to connect to
other data sources using other drivers or client connection
methods.
This chapter describes each of the MySQL storage engines except for
NDB Cluster
, which is covered in
Chapter 16, MySQL Cluster.
For answers to some commonly asked questions about MySQL storage engines, see Section A.2, “MySQL 5.0 FAQ — Storage Engines”.
When you create a new table, you can specify which storage engine to
use by adding an ENGINE
or
TYPE
table option to the CREATE
TABLE
statement:
CREATE TABLE t (i INT) ENGINE = INNODB; CREATE TABLE t (i INT) TYPE = MEMORY;
The older term TYPE
is supported as a synonym for
ENGINE
for backward compatibility, but
ENGINE
is the preferred term and
TYPE
is deprecated.
If you omit the ENGINE
or TYPE
option, the default storage engine is used. Normally, this is
MyISAM
, but you can change it by using the
--default-storage-engine
or
--default-table-type
server startup option, or by
setting the default-storage-engine
or
default-table-type
option in the
my.cnf
configuration file.
You can set the default storage engine to be used during the current
session by setting the storage_engine
or
table_type
variable:
SET storage_engine=MYISAM; SET table_type=BDB;
When MySQL is installed on Windows using the MySQL Configuration
Wizard, the InnoDB
storage engine can be selected
as the default instead of MyISAM
. See
Section 2.4.8.4.5, “The Database Usage Dialog”.
To convert a table from one storage engine to another, use an
ALTER TABLE
statement that indicates the new
engine:
ALTER TABLE t ENGINE = MYISAM; ALTER TABLE t TYPE = BDB;
See Section 12.1.5, “CREATE TABLE
Syntax”, and
Section 12.1.2, “ALTER TABLE
Syntax”.
If you try to use a storage engine that is not compiled in or that
is compiled in but deactivated, MySQL instead creates a table using
the default storage engine, usually MyISAM
. This
behavior is convenient when you want to copy tables between MySQL
servers that support different storage engines. (For example, in a
replication setup, perhaps your master server supports transactional
storage engines for increased safety, but the slave servers use only
non-transactional storage engines for greater speed.)
This automatic substitution of the default storage engine for unavailable engines can be confusing for new MySQL users. A warning is generated whenever a storage engine is automatically changed.
For new tables, MySQL always creates an .frm
file to hold the table and column definitions. The table's index and
data may be stored in one or more other files, depending on the
storage engine. The server creates the .frm
file above the storage engine level. Individual storage engines
create any additional files required for the tables that they
manage.
A database may contain tables of different types. That is, tables need not all be created with the same storage engine.
Transaction-safe tables (TSTs) have several advantages over non-transaction-safe tables (NTSTs):
They are safer. Even if MySQL crashes or you get hardware problems, you can get your data back, either by automatic recovery or from a backup plus the transaction log.
You can combine many statements and accept them all at the same
time with the COMMIT
statement (if autocommit
is disabled).
You can execute ROLLBACK
to ignore your
changes (if autocommit is disabled).
If an update fails, all of your changes are reverted. (With non-transaction-safe tables, all changes that have taken place are permanent.)
Transaction-safe storage engines can provide better concurrency for tables that get many updates concurrently with reads.
You can combine transaction-safe and non-transaction-safe tables in
the same statements to get the best of both worlds. However,
although MySQL supports several transaction-safe storage engines,
for best results, you should not mix different storage engines
within a transaction with autocommit disabled. For example, if you
do this, changes to non-transaction-safe tables still are committed
immediately and cannot be rolled back. For information about this
and other problems that can occur in transactions that use mixed
storage engines, see Section 12.4.1, “START TRANSACTION
, COMMIT
, and
ROLLBACK
Syntax”.
Non-transaction-safe tables have several advantages of their own, all of which occur because there is no transaction overhead:
Much faster
Lower disk space requirements
Less memory required to perform updates
MyISAM
is the default storage engine. It is based
on the older ISAM
code but has many useful
extensions. (Note that MySQL 5.0 does
not support ISAM
.)
Each MyISAM
table is stored on disk in three
files. The files have names that begin with the table name and have
an extension to indicate the file type. An .frm
file stores the table format. The data file has an
.MYD
(MYData
) extension. The
index file has an .MYI
(MYIndex
) extension.
To specify explicitly that you want a MyISAM
table, indicate that with an ENGINE
table option:
CREATE TABLE t (i INT) ENGINE = MYISAM;
The older term TYPE
is supported as a synonym for
ENGINE
for backward compatibility, but
ENGINE
is the preferred term and
TYPE
is deprecated.
Normally, it is unnecesary to use ENGINE
to
specify the MyISAM
storage engine.
MyISAM
is the default engine unless the default
has been changed. To ensure that MyISAM
is used
in situations where the default might have been changed, include the
ENGINE
option explicitly.
You can check or repair MyISAM
tables with the
mysqlcheck client or myisamchk
utility. You can also compress MyISAM
tables with
myisampack to take up much less space. See
Section 4.5.3, “mysqlcheck — A Table Maintenance and Repair Program”, Section 6.4.1, “Using myisamchk for Crash Recovery”, and
Section 4.6.5, “myisampack — Generate Compressed, Read-Only MyISAM Tables”.
MyISAM
tables have the following characteristics:
All data values are stored with the low byte first. This makes the data machine and operating system independent. The only requirements for binary portability are that the machine uses two's-complement signed integers and IEEE floating-point format. These requirements are widely used among mainstream machines. Binary compatibility might not be applicable to embedded systems, which sometimes have peculiar processors.
There is no significant speed penalty for storing data low byte first; the bytes in a table row normally are unaligned and it takes little more processing to read an unaligned byte in order than in reverse order. Also, the code in the server that fetches column values is not time critical compared to other code.
All numeric key values are stored with the high byte first to allow better index compression.
Large files (up to 63-bit file length) are supported on filesystems and operating systems that support large files.
There is a limit of 232 (~4.295E+09)
rows in a MyISAM
table. If you build MySQL
with the --with-big-tables
option, the row
limitation is increased to
(232)2
(1.844E+19) rows. See Section 2.4.15.2, “Typical configure Options”.
Binary distributions for Unix and Linux are built with this
option.
The maximum number of indexes per MyISAM
table is 64. This can be changed by recompiling. Beginning with
MySQL 5.0.18, you can configure the build by invoking
configure with the
--with-max-indexes=
option, where N
N
is the maximum number
of indexes to permit per MyISAM
table.
N
must be less than or equal to 128.
Before MySQL 5.0.18, you must change the source.
The maximum number of columns per index is 16.
The maximum key length is 1000 bytes. This can also be changed by changing the source and recompiling. For the case of a key longer than 250 bytes, a larger key block size than the default of 1024 bytes is used.
When rows are inserted in sorted order (as when you are using an
AUTO_INCREMENT
column), the index tree is
split so that the high node only contains one key. This improves
space utilization in the index tree.
Internal handling of one AUTO_INCREMENT
column per table is supported. MyISAM
automatically updates this column for INSERT
and UPDATE
operations. This makes
AUTO_INCREMENT
columns faster (at least 10%).
Values at the top of the sequence are not reused after being
deleted. (When an AUTO_INCREMENT
column is
defined as the last column of a multiple-column index, reuse of
values deleted from the top of a sequence does occur.) The
AUTO_INCREMENT
value can be reset with
ALTER TABLE
or myisamchk.
Dynamic-sized rows are much less fragmented when mixing deletes with updates and inserts. This is done by automatically combining adjacent deleted blocks and by extending blocks if the next block is deleted.
MyISAM
supports concurrent inserts: If a
table has no free blocks in the middle of the data file, you can
INSERT
new rows into it at the same time that
other threads are reading from the table. A free block can occur
as a result of deleting rows or an update of a dynamic length
row with more data than its current contents. When all free
blocks are used up (filled in), future inserts become concurrent
again. See Section 7.3.3, “Concurrent Inserts”.
You can put the data file and index file on different
directories to get more speed with the DATA
DIRECTORY
and INDEX DIRECTORY
table
options to CREATE TABLE
. See
Section 12.1.5, “CREATE TABLE
Syntax”.
BLOB
and TEXT
columns can
be indexed.
NULL
values are allowed in indexed columns.
This takes 0–1 bytes per key.
Each character column can have a different character set. See Section 9.1, “Character Set Support”.
There is a flag in the MyISAM
index file that
indicates whether the table was closed correctly. If
mysqld is started with the
--myisam-recover
option,
MyISAM
tables are automatically checked when
opened, and are repaired if the table wasn't closed properly.
myisamchk marks tables as checked if you run
it with the --update-state
option.
myisamchk --fast checks only those tables
that don't have this mark.
myisamchk --analyze stores statistics for portions of keys, as well as for entire keys.
myisampack can pack BLOB
and VARCHAR
columns.
MyISAM
also supports the following features:
Support for a true VARCHAR
type; a
VARCHAR
column starts with a length stored in
one or two bytes.
Tables with VARCHAR
columns may have fixed or
dynamic row length.
The sum of the lengths of the VARCHAR
and
CHAR
columns in a table may be up to 64KB.
Arbitrary length UNIQUE
constraints.
Additional resources
A forum dedicated to the MyISAM
storage
engine is available at http://forums.mysql.com/list.php?21.
The following options to mysqld can be used to
change the behavior of MyISAM
tables. For
additional information, see Section 5.1.2, “Command Options”.
Name | Cmd-line | Option file | System Var | Status Var | Var Scope | Dynamic |
---|---|---|---|---|---|---|
bulk_insert_buffer_size | Y | Y | Y | both | yes | |
concurrent_insert | Y | Y | Y | global | yes | |
delay-key-write | Y | Y | global | yes | ||
- Variable: delay_key_write | Y | global | yes | |||
have_rtree_keys | Y | global | no | |||
key_buffer_size | Y | Y | Y | global | yes | |
log-isam | Y | Y | ||||
myisam_block_size | Y | Y | Y | both | yes | |
myisam_data_pointer_size | Y | Y | Y | global | yes | |
myisam_max_extra_sort_file_size | Y | Y | Y | global | no | |
myisam_max_sort_file_size | Y | Y | Y | global | yes | |
myisam-recover | Y | Y | ||||
myisam_recover_options | Y | global | no | |||
myisam_repair_threads | Y | Y | Y | both | yes | |
myisam_sort_buffer_size | Y | Y | Y | both | yes | |
myisam_stats_method | Y | Y | Y | both | yes | |
skip-concurrent-insert | Y | Y | ||||
- Variable: skip-concurrent_insert | ||||||
tmp_table_size | Y | Y | Y | both | yes |
Set the mode for automatic recovery of crashed
MyISAM
tables.
Don't flush key buffers between writes for any
MyISAM
table.
If you do this, you should not access
MyISAM
tables from another program (such
as from another MySQL server or with
myisamchk) when the tables are in use.
Doing so risks index corruption. Using
--external-locking
does not eliminate this
risk.
The following system variables affect the behavior of
MyISAM
tables. For additional information, see
Section 5.1.3, “System Variables”.
bulk_insert_buffer_size
The size of the tree cache used in bulk insert optimization.
This is a limit per thread!
myisam_max_sort_file_size
The maximum size of the temporary file that MySQL is allowed
to use while re-creating a MyISAM
index
(during REPAIR TABLE
, ALTER
TABLE
, or LOAD DATA INFILE
). If
the file size would be larger than this value, the index is
created using the key cache instead, which is slower. The
value is given in bytes.
myisam_sort_buffer_size
Set the size of the buffer used when recovering tables.
Automatic recovery is activated if you start
mysqld with the
--myisam-recover
option. In this case, when the
server opens a MyISAM
table, it checks whether
the table is marked as crashed or whether the open count variable
for the table is not 0 and you are running the server with
external locking disabled. If either of these conditions is true,
the following happens:
MySQL Enterprise
Subscribers to MySQL Enterprise Monitor receive notification if
the --myisam-recover
option has not been set.
For more information see
http://www.mysql.com/products/enterprise/advisors.html.
The server checks the table for errors.
If the server finds an error, it tries to do a fast table repair (with sorting and without re-creating the data file).
If the repair fails because of an error in the data file (for example, a duplicate-key error), the server tries again, this time re-creating the data file.
If the repair still fails, the server tries once more with the old repair option method (write row by row without sorting). This method should be able to repair any type of error and has low disk space requirements.
If the recovery wouldn't be able to recover all rows from
previously completed statements and you didn't specify
FORCE
in the value of the
--myisam-recover
option, automatic repair aborts
with an error message in the error log:
Error: Couldn't repair table: test.g00pages
If you specify FORCE
, a warning like this is
written instead:
Warning: Found 344 of 354 rows when repairing ./test/g00pages
Note that if the automatic recovery value includes
BACKUP
, the recovery process creates files with
names of the form
.
You should have a cron script that
automatically moves these files from the database directories to
backup media.
tbl_name-datetime
.BAK
MyISAM
tables use B-tree indexes. 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 the table doesn't have any compressed keys.
String indexes are space compressed. If the first index part is a
string, it is also prefix compressed. Space compression makes the
index file smaller than the worst-case figure if a 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 the PACK_KEYS=1
table
option when you create the table. Numbers are stored with the high
byte first, so this helps when you have many integer keys that
have an identical prefix.
MyISAM
supports three different storage
formats. Two of them, fixed and dynamic format, are chosen
automatically depending on the type of columns you are using. The
third, compressed format, can be created only with the
myisampack utility (see
Section 4.6.5, “myisampack — Generate Compressed, Read-Only MyISAM Tables”).
When you use CREATE TABLE
or ALTER
TABLE
for a table that has no BLOB
or
TEXT
columns, you can force the table format to
FIXED
or DYNAMIC
with the
ROW_FORMAT
table option.
See Section 12.1.5, “CREATE TABLE
Syntax”, for information about
ROW_FORMAT
.
You can decompress (unpack) compressed MyISAM
tables using myisamchk
--unpack
; see
Section 4.6.3, “myisamchk — MyISAM Table-Maintenance Utility”, for more information.
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.
Fixed-length row format is only available for tables without
BLOB
or TEXT
columns.
Creating a table with these columns with an explicit
ROW_FORMAT
clause will not raise an error
or warning; the format specification will be ignored.
Static-format tables have these characteristics:
CHAR
and VARCHAR
columns are space-padded to the specified column width,
although the column type is not altered. This is also true
for NUMERIC
and
DECIMAL
columns created before MySQL
5.0.3. BINARY
and
VARBINARY
columns are space-padded to the
column width before MySQL 5.0.15. As of 5.0.15,
BINARY
and VARBINARY
columns are padded with 0x00
bytes.
Very quick.
Easy to cache.
Easy to reconstruct after a crash, because rows are located in fixed positions.
Reorganization is unnecessary unless you delete a huge
number of rows and want to return free disk space to the
operating system. To do this, use OPTIMIZE
TABLE
or myisamchk -r.
Usually require more disk space than dynamic-format tables.
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:
All string columns are dynamic except those with a length less than four.
Each row is preceded by a bitmap that indicates which
columns contain the empty string (for string columns) or
zero (for numeric columns). Note that this does not include
columns that contain NULL
values. If a
string column has a length of zero after trailing space
removal, or a numeric column has a value of zero, it is
marked in the bitmap and not saved to disk. Non-empty
strings are saved as a length byte plus the string contents.
Much less disk space usually is required than for fixed-length tables.
Each row uses only as much space as is required. However, if
a row becomes larger, it is split into as many pieces as are
required, resulting in row fragmentation. For example, if
you update a row with information that extends the row
length, the row becomes fragmented. In this case, you may
have to run OPTIMIZE TABLE
or
myisamchk -r from time to time to improve
performance. Use myisamchk -ei to obtain
table statistics.
More difficult than static-format tables to reconstruct after a crash, because rows may be fragmented into many pieces and links (fragments) may be missing.
The expected row length for dynamic-sized rows is calculated using the following expression:
3 + (number of columns
+ 7) / 8 + (number of char columns
) + (packed size of numeric columns
) + (length of strings
) + (number of NULL columns
+ 7) / 8
There is a penalty of 6 bytes for each link. A dynamic row
is linked whenever an update causes an enlargement of the
row. Each new link is at least 20 bytes, so the next
enlargement probably goes in the same link. If not, another
link is created. You can find the number of links using
myisamchk -ed. All links may be removed
with OPTIMIZE TABLE
or myisamchk
-r.
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:
Compressed tables take very little disk space. This minimizes disk usage, which is helpful when using slow disks (such as CD-ROMs).
Each row is compressed separately, so there is very little access overhead. The header for a row takes up one to three bytes depending on the biggest row in the table. Each column is compressed differently. There is usually a different Huffman tree for each column. Some of the compression types are:
Suffix space compression.
Prefix space compression.
Numbers with a value of zero are stored using one bit.
If values in an integer column have a small range, the
column is stored using the smallest possible type. For
example, a BIGINT
column (eight
bytes) can be stored as a TINYINT
column (one byte) if all its values are in the range
from -128
to 127
.
If a column has only a small set of possible values, the
data type is converted to ENUM
.
A column may use any combination of the preceding compression types.
Can be used for fixed-length or dynamic-length rows.
While a compressed table is read only, and you cannot
therefore update or add rows in the table, DDL (Data
Definition Language) operations are still valid. For example,
you may still use DROP
to drop the table,
and TRUNCATE
to empty the table.
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. The following discussion describes how this can happen and how to handle it.
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:
The mysqld process is killed in the middle of a write.
An unexpected computer shutdown occurs (for example, the computer is turned off).
Hardware failures.
You are using an external program (such as myisamchk) to modify a table that is being modified by the server at the same time.
A software bug in the MySQL or MyISAM
code.
Typical symptoms of a corrupt table are:
You get the following error while selecting data from the table:
Incorrect key file for table: '...'. Try to repair it
Queries don't find rows in the table or return incomplete results.
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 12.5.2.3, “CHECK TABLE
Syntax”, Section 12.5.2.6, “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:
The first time a table is updated in MySQL, a counter in the header of the index files is incremented.
The counter is not changed during further updates.
When the last instance of a table is closed (because a
FLUSH TABLES
operation was performed or
because there is no room in the table cache), the counter is
decremented if the table has been updated at any point.
When you repair the table or check the table and it is found to be okay, the counter is reset to zero.
To avoid problems with interaction with other processes that might check the table, the counter is not decremented on close if it was zero.
In other words, the counter can become incorrect only under these conditions:
A MyISAM
table is copied without first
issuing LOCK TABLES
and FLUSH
TABLES
.
MySQL has crashed between an update and the final close. (Note that the table may still be okay, because MySQL always issues writes for everything between each statement.)
A table was modified by myisamchk --recover or myisamchk --update-state at the same time that it was in use by mysqld.
Multiple mysqld servers are using the
table and one server performed a REPAIR
TABLE
or CHECK TABLE
on the
table while it was in use by another server. In this setup,
it is safe to use CHECK TABLE
, although
you might get the warning from other servers. However,
REPAIR TABLE
should be avoided because
when one server replaces the data file with a new one, this
is not known to the other servers.
In general, it is a bad idea to share a data directory among multiple servers. See Section 5.6, “Running Multiple MySQL Servers on the Same Machine”, for additional discussion.
InnoDB
OverviewInnoDB
Contact InformationInnoDB
ConfigurationInnoDB
Startup Options and System VariablesInnoDB
TablespaceInnoDB
TablesInnoDB
Data and Log FilesInnoDB
DatabaseInnoDB
Database to Another MachineInnoDB
Transaction Model and LockingInnoDB
Performance Tuning TipsInnoDB
Table and Index StructuresInnoDB
File Space Management and Disk I/OInnoDB
Error HandlingInnoDB
TablesInnoDB
Troubleshooting
InnoDB
provides MySQL with a transaction-safe
(ACID
compliant) storage engine that has
commit, rollback, and crash recovery capabilities.
InnoDB
does locking on the row level and also
provides an Oracle-style consistent non-locking read in
SELECT
statements. These features increase
multi-user concurrency and performance. There is no need for lock
escalation in InnoDB
because row-level locks
fit in very little space. InnoDB
also supports
FOREIGN KEY
constraints. You can freely mix
InnoDB
tables with tables from other MySQL
storage engines, even within the same statement.
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.
Fully integrated with MySQL Server, the InnoDB
storage engine maintains 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 (or raw disk partitions). This is different from, for
example, MyISAM
tables where each table is
stored using separate files. InnoDB
tables can
be of any size even on operating systems where file size is
limited to 2GB.
InnoDB
is included in binary distributions by
default. The Windows Essentials installer makes
InnoDB
the MySQL default storage engine on
Windows.
InnoDB
is used in production at numerous large
database sites requiring high performance. The famous Internet
news site Slashdot.org runs on InnoDB
. Mytrix,
Inc. stores over 1TB of data in InnoDB
, and
another site handles an average load of 800 inserts/updates per
second in InnoDB
.
InnoDB
is published under the same GNU GPL
License Version 2 (of June 1991) as MySQL. For more information on
MySQL licensing, see
http://www.mysql.com/company/legal/licensing/.
Additional resources
A forum dedicated to the InnoDB
storage
engine is available at
http://forums.mysql.com/list.php?22.
Contact information for Innobase Oy, producer of the
InnoDB
engine:
Web site: http://www.innodb.com/
Email: innodb_sales_ww at oracle.com
or use
this contact form:
http://www.innodb.com/contact-form
Phone:
+358-9-6969 3250 (office, Heikki Tuuri) +358-40-5617367 (mobile, Heikki Tuuri) +358-40-5939732 (mobile, Satu Sirén)
Address:
Innobase Oy Inc. World Trade Center Helsinki Aleksanterinkatu 17 P.O.Box 800 00101 Helsinki Finland
The InnoDB
storage engine is enabled by
default. If you don't want to use InnoDB
tables, you can add the skip-innodb
option to
your MySQL option file.
InnoDB
provides MySQL with a transaction-safe
(ACID
compliant) storage engine that has
commit, rollback, and crash recovery capabilities.
However, it cannot do so if the
underlying operating system or hardware does not work as
advertised. Many operating systems or disk subsystems may delay
or reorder write operations to improve performance. On some
operating systems, the very system call that should wait until
all unwritten data for a file has been flushed —
fsync()
— might actually return before
the data has been flushed to stable storage. Because of this, an
operating system crash or a power outage may destroy recently
committed data, or in the worst case, even corrupt the database
because of write operations having been reordered. If data
integrity is important to you, you should perform some
“pull-the-plug” tests before using anything in
production. On Mac OS X 10.3 and up, InnoDB
uses a special fcntl()
file flush method.
Under Linux, it is advisable to disable
the write-back cache.
On ATAPI hard disks, a command such hdparm -W0
/dev/hda
may work to disable the write-back cache.
Beware that some drives or disk controllers
may be unable to disable the write-back cache.
Two important disk-based resources managed by the
InnoDB
storage engine are its tablespace data
files and its log files.
If you specify no InnoDB
configuration
options, MySQL creates an auto-extending 10MB data file named
ibdata1
and two 5MB log files named
ib_logfile0
and
ib_logfile1
in the MySQL data directory. To
get good performance, you should explicitly provide
InnoDB
parameters as discussed in the
following examples. Naturally, you should edit the settings to
suit your hardware and requirements.
It is not a good idea to configure InnoDB
to
use datafiles or logfiles on NFS volumes. Otherwise, the files
might be locked by other processes and become unavailable for
use by MySQL.
MySQL Enterprise For advice on settings suitable to your specific circumstances, subscribe to the MySQL Enterprise Monitor. For more information see http://www.mysql.com/products/enterprise/advisors.html.
The examples shown here are representative. See
Section 13.2.4, “InnoDB
Startup Options and System Variables” for additional information
about InnoDB
-related configuration parameters.
To set up the InnoDB
tablespace files, use the
innodb_data_file_path
option in the
[mysqld]
section of the
my.cnf
option file. On Windows, you can use
my.ini
instead. The value of
innodb_data_file_path
should be a list of one
or more data file specifications. If you name more than one data
file, separate them by semicolon
(“;
”) characters:
innodb_data_file_path=datafile_spec1
[;datafile_spec2
]...
For example, a setting that explicitly creates a tablespace having the same characteristics as the default is as follows:
[mysqld] innodb_data_file_path=ibdata1:10M:autoextend
This setting configures a single 10MB data file named
ibdata1
that is auto-extending. No location
for the file is given, so by default, InnoDB
creates it in the MySQL data directory.
Sizes are specified using M
or
G
suffix letters to indicate units of MB or GB.
A tablespace containing a fixed-size 50MB data file named
ibdata1
and a 50MB auto-extending file named
ibdata2
in the data directory can be
configured like this:
[mysqld] innodb_data_file_path=ibdata1:50M;ibdata2:50M:autoextend
The full syntax for a data file specification includes the filename, its size, and several optional attributes:
file_name
:file_size
[:autoextend[:max:max_file_size
]]
The autoextend
attribute and those following
can be used only for the last data file in the
innodb_data_file_path
line.
If you specify the autoextend
option for the
last data file, InnoDB
extends the data file if
it runs out of free space in the tablespace. The increment is 8MB
at a time by default. It can be modified by changing the
innodb_autoextend_increment
system variable.
If the disk becomes full, you might want to add another data file
on another disk. Instructions for reconfiguring an existing
tablespace are given in Section 13.2.7, “Adding and Removing InnoDB
Data and Log Files”.
InnoDB
is not aware of the filesystem maximum
file size, so be cautious on filesystems where the maximum file
size is a small value such as 2GB. To specify a maximum size for
an auto-extending data file, use the max
attribute. The following configuration allows
ibdata1
to grow up to a limit of 500MB:
[mysqld] innodb_data_file_path=ibdata1:10M:autoextend:max:500M
InnoDB
creates tablespace files in the MySQL
data directory by default. To specify a location explicitly, use
the innodb_data_home_dir
option. For example,
to use two files named ibdata1
and
ibdata2
but create them in the
/ibdata
directory, configure
InnoDB
like this:
[mysqld] innodb_data_home_dir = /ibdata innodb_data_file_path=ibdata1:50M;ibdata2:50M:autoextend
InnoDB
does not create directories, so make
sure that the /ibdata
directory exists
before you start the server. This is also true of any log file
directories that you configure. Use the Unix or DOS
mkdir
command to create any necessary
directories.
InnoDB
forms the directory path for each data
file by textually concatenating the value of
innodb_data_home_dir
to the data file name,
adding a pathname separator (slash or backslash) between values if
necessary. If the innodb_data_home_dir
option
is not mentioned in my.cnf
at all, the
default value is the “dot” directory
./
, which means the MySQL data directory.
(The MySQL server changes its current working directory to its
data directory when it begins executing.)
If you specify innodb_data_home_dir
as an empty
string, you can specify absolute paths for the data files listed
in the innodb_data_file_path
value. The
following example is equivalent to the preceding one:
[mysqld] innodb_data_home_dir = innodb_data_file_path=/ibdata/ibdata1:50M;/ibdata/ibdata2:50M:autoextend
A simple my.cnf
example. Suppose that you have a computer with 128MB
RAM and one hard disk. The following example shows possible
configuration parameters in my.cnf
or
my.ini
for InnoDB
,
including the autoextend
attribute. The example
suits most users, both on Unix and Windows, who do not want to
distribute InnoDB
data files and log files onto
several disks. It creates an auto-extending data file
ibdata1
and two InnoDB
log
files ib_logfile0
and
ib_logfile1
in the MySQL data directory.
[mysqld] # You can write your other MySQL server options here # ... # Data files must be able to hold your data and indexes. # Make sure that you have enough free disk space. innodb_data_file_path = ibdata1:10M:autoextend # # Set buffer pool size to 50-80% of your computer's memory innodb_buffer_pool_size=70M innodb_additional_mem_pool_size=10M # # Set the log file size to about 25% of the buffer pool size innodb_log_file_size=20M innodb_log_buffer_size=8M # innodb_flush_log_at_trx_commit=1
Make sure that the MySQL server has the proper access rights to create files in the data directory. More generally, the server must have access rights in any directory where it needs to create data files or log files.
Note that data files must be less than 2GB in some filesystems. The combined size of the log files must be less than 4GB. The combined size of data files must be at least 10MB.
When you create an InnoDB
tablespace for the
first time, it is best that you start the MySQL server from the
command prompt. InnoDB
then prints the
information about the database creation to the screen, so you can
see what is happening. For example, on Windows, if
mysqld is located in C:\Program
Files\MySQL\MySQL Server 5.0\bin
, you can
start it like this:
C:\> "C:\Program Files\MySQL\MySQL Server 5.0\bin\mysqld" --console
If you do not send server output to the screen, check the server's
error log to see what InnoDB
prints during the
startup process.
See Section 13.2.5, “Creating the InnoDB
Tablespace”, for an example of what the
information displayed by InnoDB
should look
like.
You can place InnoDB
options in the
[mysqld]
group of any option file that your
server reads when it starts. The locations for option files are
described in Section 4.2.2.2, “Using Option Files”.
If you installed MySQL on Windows using the installation and
configuration wizards, the option file will be the
my.ini
file located in your MySQL
installation directory. See
Section 2.4.8.4.1.1, “The MySQL Server Configuration Wizard on Windows”.
If your PC uses a boot loader where the C:
drive is not the boot drive, your only option is to use the
my.ini
file in your Windows directory
(typically C:\WINDOWS
). You can use the
SET
command at the command prompt in a console
window to print the value of WINDIR
:
C:\> SET WINDIR
windir=C:\WINDOWS
If you want to make sure that mysqld reads
options only from a specific file, you can use the
--defaults-file
option as the first option on the
command line when starting the server:
mysqld --defaults-file=your_path_to_my_cnf
An advanced my.cnf
example. Suppose that you have a Linux computer with
2GB RAM and three 60GB hard disks at directory paths
/
, /dr2
and
/dr3
. The following example shows possible
configuration parameters in my.cnf
for
InnoDB
.
[mysqld] # You can write your other MySQL server options here # ... innodb_data_home_dir = # # Data files must be able to hold your data and indexes innodb_data_file_path = /ibdata/ibdata1:2000M;/dr2/ibdata/ibdata2:2000M:autoextend # # Set buffer pool size to 50-80% of your computer's memory, # but make sure on Linux x86 total memory usage is < 2GB innodb_buffer_pool_size=1G innodb_additional_mem_pool_size=20M innodb_log_group_home_dir = /dr3/iblogs # innodb_log_files_in_group = 2 # # Set the log file size to about 25% of the buffer pool size innodb_log_file_size=250M innodb_log_buffer_size=8M # innodb_flush_log_at_trx_commit=1 innodb_lock_wait_timeout=50 # # Uncomment the next lines if you want to use them #innodb_thread_concurrency=5
In some cases, database performance improves if all the 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 example illustrates how to do this. It places the two data
files on different disks and places the log files on the third
disk. InnoDB
fills the tablespace beginning
with the first data file. You can also use raw disk partitions
(raw devices) as InnoDB
data files, which may
speed up I/O. See Section 13.2.3.2, “Using Raw Devices for the Shared Tablespace”.
On 32-bit GNU/Linux x86, you must be careful not to set memory
usage too high. glibc
may allow the process
heap to grow over thread stacks, which crashes your server. It
is a risk if the value of the following expression is close to
or exceeds 2GB:
innodb_buffer_pool_size + key_buffer_size + max_connections*(sort_buffer_size+read_buffer_size+binlog_cache_size) + max_connections*2MB
Each thread uses a stack (often 2MB, but only 256KB in MySQL AB
binaries) and in the worst case also uses
sort_buffer_size + read_buffer_size
additional
memory.
By compiling MySQL yourself, you can use up to 64GB of physical
memory in 32-bit Windows. See the description for
innodb_buffer_pool_awe_mem_mb
in
Section 13.2.4, “InnoDB
Startup Options and System Variables”.
How to tune other mysqld server parameters? The following values are typical and suit most users:
[mysqld]
skip-external-locking
max_connections=200
read_buffer_size=1M
sort_buffer_size=1M
#
# Set key_buffer to 5 - 50% of your RAM depending on how much
# you use MyISAM tables, but keep key_buffer_size + InnoDB
# buffer pool size < 80% of your RAM
key_buffer_size=value
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 the remaining InnoDB
tables.
You can enable multiple tablespaces by adding this line to the
[mysqld]
section of
my.cnf
:
[mysqld] innodb_file_per_table
After restarting the server, InnoDB
stores
each newly created table into its own file
in
the database directory where the table belongs. This is similar
to what the tbl_name
.ibdMyISAM
storage engine does, but
MyISAM
divides the table into a data file
and
the index file
tbl_name
.MYD
.
For tbl_name
.MYIInnoDB
, the data and the indexes are
stored together in the .ibd
file. The
file is still created as usual.
tbl_name
.frm
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.
innodb_file_per_table
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 remove the option
and restart the server, new tables are created in the shared
tablespace, but you can still access any tables that were
created using multiple tablespaces.
InnoDB
always needs the shared tablespace
because it puts its internal data dictionary and undo logs
there. The .ibd
files are not sufficient
for InnoDB
to operate.
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.
To move an .ibd
file and the associated
table from one database to another, use a RENAME
TABLE
statement:
RENAME TABLEdb1.tbl_name
TOdb2.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:
Issue this ALTER TABLE
statement:
ALTER TABLE tbl_name
DISCARD TABLESPACE;
This statement deletes the current
.ibd
file.
Put the backup .ibd
file back in the
proper database directory.
Issue this ALTER TABLE
statement:
ALTER TABLE tbl_name
IMPORT TABLESPACE;
In this context, a “clean”
.ibd
file backup means:
There are no uncommitted modifications by transactions in
the .ibd
file.
There are no unmerged insert buffer entries in the
.ibd
file.
Purge has removed all delete-marked index records from the
.ibd
file.
mysqld has flushed all modified pages of
the .ibd
file from the buffer pool to
the file.
You can make a clean backup .ibd
file using
the following method:
Stop all activity from the mysqld server and commit all transactions.
Wait until SHOW ENGINE INNODB STATUS
shows that there are no active transactions in the database,
and the main thread status of InnoDB
is
Waiting for server activity
. Then you can
make a copy of the .ibd
file.
Another method for making a clean copy of an
.ibd
file is to use the commercial
InnoDB Hot Backup tool:
Use InnoDB Hot Backup to back up the
InnoDB
installation.
Start a second mysqld server on the
backup and let it clean up the .ibd
files in the backup.
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 filesystem overhead, which may improve performance.
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 raw disk partitions, be sure that they have permissions that allow read and write access by the account used for running the MySQL server.
This section describes the InnoDB
-related
command options and system variables. System variables that are
true or false can be enabled at server startup by naming them, or
disabled by using a skip-
prefix. For example,
to enable or disable InnoDB
checksums, you can
use --innodb_checksums
or
--skip-innodb_checksums
on the command line, or
innodb_checksums
or
skip-innodb_checksums
in an option file. System
variables that take a numeric value can be specified as
--
on the command line or as
var_name
=value
in option files. For more information on specifying options and
system variables, see Section 4.2.2, “Specifying Program Options”. Many of
the system variables can be changed at runtime (see
Section 5.1.4.2, “Dynamic System Variables”).
var_name
=value
MySQL Enterprise The MySQL Enterprise Monitor provides expert advice on InnoDB start-up options and related system variables. For more information see http://www.mysql.com/products/enterprise/advisors.html.
InnoDB
command options:
Enables the InnoDB
storage engine, if the
server was compiled with InnoDB
support.
Use --skip-innodb
to disable
InnoDB
.
Causes InnoDB
to create a file named
in the MySQL data directory. <datadir>
/innodb_status.<pid>
InnoDB
periodically writes the output of SHOW ENGINE INNODB
STATUS
to this file.
InnoDB
system variables:
Whether InnoDB adaptive hash indexes are enabled or disabled.
By default, this variable is enabled. Use
--skip-innodb_adaptive_hash_index
at server
startup to disable it. See
Section 13.2.13.3, “Adaptive Hash Indexes” This variable was added
in MySQL 5.0.52.
innodb_additional_mem_pool_size
The size in bytes of a memory pool InnoDB
uses to store data dictionary information and other internal
data structures. The more tables you have in your application,
the more memory you need to allocate here. If
InnoDB
runs out of memory in this pool, it
starts to allocate memory from the operating system and writes
warning messages to the MySQL error log. The default value is
1MB.
The increment size (in MB) for extending the size of an auto-extending tablespace when it becomes full. The default value is 8.
The size of the buffer pool (in MB), if it is placed in the
AWE memory. This is relevant only in 32-bit Windows. If your
32-bit Windows operating system supports more than 4GB memory,
using so-called “Address Windowing Extensions,”
you can allocate the InnoDB
buffer pool
into the AWE physical memory using this variable. The maximum
possible value for this variable is 63000. If it is greater
than 0, innodb_buffer_pool_size
is the
window in the 32-bit address space of
mysqld where InnoDB
maps
that AWE memory. A good value for
innodb_buffer_pool_size
is 500MB.
To take advantage of AWE memory, you will need to recompile
MySQL yourself. The current project settings needed for doing
this can be found in the
innobase/os/os0proj.c
source file.
The size in bytes of the memory buffer
InnoDB
uses to cache data and indexes of
its tables. The larger you set this value, the less disk I/O
is needed to access data in tables. On a dedicated database
server, you may set this to up to 80% of the machine physical
memory size. However, do not set it too large because
competition for physical memory might cause paging in the
operating system.
InnoDB
can use checksum validation on all
pages read from the disk to ensure extra fault tolerance
against broken hardware or data files. This validation is
enabled by default. However, under some rare circumstances
(such as when running benchmarks) this extra safety feature is
unneeded and can be disabled with
--skip-innodb_checksums
. This variable was
added in MySQL 5.0.3.
The number of threads that can commit at the same time. Setting this parameter to 0 allows any number of transactions to commit simultaneously. This variable was added in MySQL 5.0.12.
The number of threads that can enter InnoDB
concurrently is determined by the
innodb_thread_concurrency
variable. A
thread is placed in a queue when it tries to enter
InnoDB
if the number of threads has already
reached the concurrency limit. When a thread is allowed to
enter InnoDB
, it is given a number of
“free tickets” equal to the value of
innodb_concurrency_tickets
, and the thread
can enter and leave InnoDB
freely until it
has used up its tickets. After that point, the thread again
becomes subject to the concurrency check (and possible
queuing) the next time it tries to enter
InnoDB
. This variable was added in MySQL
5.0.3.
The paths to individual data files and their sizes. The full
directory path to each data file is formed by concatenating
innodb_data_home_dir
to each path specified
here. The file sizes are specified in MB or GB (1024MB) by
appending M
or G
to the
size value. The sum of the sizes of the files must be at least
10MB. If you do not specify
innodb_data_file_path
, the default behavior
is to create a single 10MB auto-extending data file named
ibdata1
. The size limit of individual
files is determined by your operating system. You can set the
file size to more than 4GB on those operating systems that
support big files. You can also use raw disk partitions as
data files. See Section 13.2.3.2, “Using Raw Devices for the Shared Tablespace”.
The common part of the directory path for all
InnoDB
data files. If you do not set this
value, the default is the MySQL data directory. You can
specify the value as an empty string, in which case you can
use absolute file paths in
innodb_data_file_path
.
By default, InnoDB
stores all data twice,
first to the doublewrite buffer, and then to the actual data
files. This variable is enabled by default. It can be turned
off with --skip-innodb_doublewrite
for
benchmarks or cases when top performance is needed rather than
concern for data integrity or possible failures. This variable
was added in MySQL 5.0.3.
If you set this variable to 0, InnoDB
does
a full purge and an insert buffer merge before a shutdown.
These operations can take minutes, or even hours in extreme
cases. If you set this variable to 1,
InnoDB
skips these operations at shutdown.
The default value is 1. If you set it to 2,
InnoDB
will just flush its logs and then
shut down cold, as if MySQL had crashed; no committed
transaction will be lost, but crash recovery will be done at
the next startup. The value of 2 can be used as of MySQL
5.0.5, except that it cannot be used on NetWare.
The number of file I/O threads in InnoDB
.
Normally, this should be left at the default value of 4, but
disk I/O on Windows may benefit from a larger number. On Unix,
increasing the number has no effect; InnoDB
always uses the default value.
If this variable is enabled, InnoDB
creates
each new table using its own .ibd
file
for storing data and indexes, rather than in the shared
tablespace. The default is to create tables in the shared
tablespace. See Section 13.2.3.1, “Using Per-Table Tablespaces”.
innodb_flush_log_at_trx_commit
When innodb_flush_log_at_trx_commit
is set
to 0, the log buffer is written out to the log file once per
second and the flush to disk operation is performed on the log
file, but nothing is done at a transaction commit. When this
value is 1 (the default), the log buffer is written out to the
log file at each transaction commit and the flush to disk
operation is performed on the log file. When set to 2, the log
buffer is written out to the file at each commit, but the
flush to disk operation is not performed on it. However, the
flushing on the log file takes place once per second also when
the value is 2. Note that the once-per-second flushing is not
100% guaranteed to happen every second, due to process
scheduling issues.
The default value of this variable is 1, which is the value
that is required for ACID compliance. You can achieve better
performance by setting the value different from 1, but then
you can lose at most one second worth of transactions in a
crash. If you set the value to 0, then any
mysqld process crash can erase the last
second of transactions. If you set the value to 2, then only
an operating system crash or a power outage can erase the last
second of transactions. However, InnoDB
's
crash recovery is not affected and thus crash recovery does
work regardless of the value. Note that many operating systems
and some disk hardware fool the flush-to-disk operation. They
may tell mysqld that the flush has taken
place, even though it has not. Then the durability of
transactions is not guaranteed even with the setting 1, and in
the worst case a power outage can even corrupt the
InnoDB
database. Using a battery-backed
disk cache in the SCSI disk controller or in the disk itself
speeds up file flushes, and makes the operation safer. You can
also try using the Unix command hdparm to
disable the caching of disk writes in hardware caches, or use
some other command specific to the hardware vendor.
Note: For the greatest possible durability and consistency in
a replication setup using InnoDB
with
transactions, you should use
innodb_flush_log_at_trx_commit=1
,
sync_binlog=1
, and, before MySQL 5.0.3,
innodb_safe_binlog
in your master server
my.cnf
file.
(innodb_safe_binlog
is not needed from
5.0.3 on.)
If set to fdatasync
(the default),
InnoDB
uses fsync()
to
flush both the data and log files. If set to
O_DSYNC
, InnoDB
uses
O_SYNC
to open and flush the log files, but
uses fsync()
to flush the data files. If
O_DIRECT
is specified (available on some
GNU/Linux versions, FreeBSD and Solaris),
InnoDB
uses O_DIRECT
(or
directio()
on Solaris) to open the data
files, and uses fsync()
to flush both the
data and log files. Note that InnoDB
uses
fsync()
instead of
fdatasync()
, and it does not use
O_DSYNC
by default because there have been
problems with it on many varieties of Unix. This variable is
relevant only for Unix. On Windows, the flush method is always
async_unbuffered
and cannot be changed.
Different values of this variable can have a marked effect on
InnoDB performance
. For example, on some
systems where InnoDB
data and log files are
located on a SAN, it has been found that setting
innodb_flush_method
to
O_DIRECT
can degrade performance of simple
SELECT
statements by a factor of three.
The crash recovery mode.
This variable should be set greater than 0 only in an
emergency situation when you want to dump your tables from a
corrupt database! Possible values are from 1 to 6. The
meanings of these values are described in
Section 13.2.8.1, “Forcing InnoDB
Recovery”. As a safety measure,
InnoDB
prevents any changes to its data
when this variable is greater than 0.
The 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. The default is 50 seconds. A lock wait for a
MySQL table lock does not happen inside
InnoDB
, and this timeout does not apply to
that wait.
innodb_locks_unsafe_for_binlog
This variable controls next-key locking in
InnoDB
searches and index scans. By
default, this variable is 0 (disabled), which means that
next-key locking is enabled.
Normally, InnoDB
uses an algorithm called
next-key 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 any index records it encounters.
Thus, the row-level locks are actually index record locks. The
locks that InnoDB
sets on index records
also affect the “gap” preceding that index
record. If a user has a shared or exclusive lock on record
R in an index, another user cannot insert
a new index record immediately before R
in the order of the index. Enabling this variable causes
InnoDB
not to use next-key locking in
searches or index scans. Next-key locking is still used to
ensure foreign key constraints and duplicate key checking.
Note that enabling this variable may cause phantom problems:
Suppose that you want to read and lock all children from the
child
table with 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;
Suppose that there is an index on the id
column. The query scans that index starting from the first
record where id
is greater than 100. If the
locks set on the index records do not lock out inserts made in
the gaps, another client can insert a new row into the table.
If you execute the same SELECT
within the
same transaction, you see a new row in the result set returned
by the query. This also means that if new items are added to
the database, InnoDB
does not guarantee
serializability. Therefore, if this variable is enabled
InnoDB
guarantees at most isolation level
READ COMMITTED
. (Conflict serializability
is still guaranteed.)
Starting from MySQL 5.0.2, this option is even more unsafe.
InnoDB
in an UPDATE
or a
DELETE
only locks rows that it updates or
deletes. This greatly reduces the probability of deadlocks,
but they can happen. Note that enabling this variable still
does not allow operations such as UPDATE
to
overtake other similar operations (such as another
UPDATE
) even in the case when they affect
different rows. Consider the following example, beginning with
this table:
CREATE TABLE A(A INT NOT NULL, B INT) ENGINE = InnoDB; INSERT INTO A VALUES (1,2),(2,3),(3,2),(4,3),(5,2); COMMIT;
Suppose that one client executes these statements:
SET AUTOCOMMIT = 0; UPDATE A SET B = 5 WHERE B = 3;
Then suppose that another client executes these statements following those of the first client:
SET AUTOCOMMIT = 0; UPDATE A SET B = 4 WHERE B = 2;
In this case, the second UPDATE
must wait
for a commit or rollback of the first
UPDATE
. The first UPDATE
has an exclusive lock on row (2,3), and the second
UPDATE
while scanning rows also tries to
acquire an exclusive lock for the same row, which it cannot
have. This is because UPDATE
two first
acquires an exclusive lock on a row and then determines
whether the row belongs to the result set. If not, it releases
the unnecessary lock, when the
innodb_locks_unsafe_for_binlog
variable is
enabled.
Therefore, InnoDB
executes
UPDATE
one as follows:
x-lock(1,2) unlock(1,2) x-lock(2,3) update(2,3) to (2,5) x-lock(3,2) unlock(3,2) x-lock(4,3) update(4,3) to (4,5) x-lock(5,2) unlock(5,2)
InnoDB
executes UPDATE
two as follows:
x-lock(1,2) update(1,2) to (1,4) x-lock(2,3) - wait for query one to commit or rollback
Whether to log InnoDB
archive files. This
variable is present for historical reasons, but is unused.
Recovery from a backup is done by MySQL using its own log
files, so there is no need to archive
InnoDB
log files. The default for this
variable is 0.
The size in bytes of the buffer that InnoDB
uses to write to the log files on disk. Sensible values range
from 1MB to 8MB. The default is 1MB. A large log buffer allows
large transactions to run without a need to write the log to
disk before the transactions commit. Thus, if you have big
transactions, making the log buffer larger saves disk I/O.
The size in bytes of each log file in a log group. The
combined size of log files must be less than 4GB on 32-bit
computers. The default is 5MB. Sensible values range from 1MB
to 1/N
-th of the size of the buffer
pool, where N
is the number of log
files in the group. The larger the value, the less checkpoint
flush activity is needed in the buffer pool, saving disk I/O.
But larger log files also mean that recovery is slower in case
of a crash.
The number of log files in the log group.
InnoDB
writes to the files in a circular
fashion. The default (and recommended) is 2.
The directory path to the InnoDB
log files.
If you do not specify any InnoDB
log
variables, the default is to create two 5MB files names
ib_logfile0
and
ib_logfile1
in the MySQL data directory.
This is an integer in the range from 0 to 100. The default is
90. The main thread in InnoDB
tries to
write pages from the buffer pool so that the percentage of
dirty (not yet written) pages will not exceed this value.
This variable controls how to delay INSERT
,
UPDATE
and DELETE
operations when the purge operations are lagging (see
Section 13.2.12, “Implementation of Multi-Versioning”). The default value
of this variable is 0, meaning that there are no delays.
The InnoDB
transaction system maintains a
list of transactions that have delete-marked index records by
UPDATE
or DELETE
operations. Let the length of this list be
purge_lag
. When
purge_lag
exceeds
innodb_max_purge_lag
, each
INSERT
, UPDATE
and
DELETE
operation is delayed by
((purge_lag
/innodb_max_purge_lag
)×10)–5
milliseconds. The delay is computed in the beginning of a
purge batch, every ten seconds. The operations are not delayed
if purge cannot run because of an old consistent read view
that could see the rows to be purged.
A typical setting for a problematic workload might be 1 million, assuming that our transactions are small, only 100 bytes in size, and we can allow 100MB of unpurged rows in our tables.
The number of identical copies of log groups to keep for the database. Currently, this should be set to 1.
This variable is relevant only if you use multiple tablespaces
in InnoDB
. It specifies the maximum number
of .ibd
files that
InnoDB
can keep open at one time. The
minimum value is 10. The default is 300.
The file descriptors used for .ibd
files
are for InnoDB
only. They are independent
of those specified by the --open-files-limit
server option, and do not affect the operation of the table
cache.
In MySQL 5.0.13 and up, InnoDB
rolls back
only the last statement on a transaction timeout. If this
option is given, a transaction timeout causes
InnoDB
to abort and roll back the entire
transaction (the same behavior as before MySQL 5.0.13). This
variable was added in MySQL 5.0.32.
innodb_safe_binlog
Adds consistency guarantees between the content of
InnoDB
tables and the binary log. See
Section 5.2.3, “The Binary Log”. This variable was removed in
MySQL 5.0.3, having been made obsolete by the introduction of
XA transaction support. You should set
innodb_support_xa
to ON
or 1 to ensure consistency. See
innodb_support_xa
.
When set to ON
or 1 (the default), this
variable enables InnoDB
support for
two-phase commit in XA transactions. Enabling
innodb_support_xa
causes an extra disk
flush for transaction preparation.
If you don't care about using XA, you can disable this
variable by setting it to OFF
or 0 to
reduce the number of disk flushes and get better
InnoDB
performance. If you are using
replication and/or the binary log then you should set this
variable to ON
or 1 to ensure that the
binary log does not get out of sync compared to the table
data.
This variable was added in MySQL 5.0.3.
The number of times a thread waits for an
InnoDB
mutex to be freed before the thread
is suspended. This variable was added in MySQL 5.0.3.
If AUTOCOMMIT=0
, InnoDB
honors LOCK TABLES
; MySQL does not return
from LOCK TABLE .. WRITE
until all other
threads have released all their locks to the table. The
default value of innodb_table_locks
is 1,
which means that LOCK TABLES
causes InnoDB
to lock a table internally if AUTOCOMMIT=0
.
InnoDB
tries to keep the number of
operating system threads concurrently inside
InnoDB
less than or equal to the limit
given by this variable. Once the number of threads reaches
this limit, additional threads are placed into a wait state
within a FIFO queue for execution. Threads waiting for locks
are not counted in the number of concurrently executing
threads.
The correct value for this variable is dependent on environment and workload. You will need to try a range of different values to determine what value works for your application.
The range of this variable is 0 to 1000. A value of 20 or higher is interpreted as infinite concurrency before MySQL 5.0.19. From 5.0.19 on, you can disable thread concurrency checking by setting the value to 0, which allows InnoDB to create as many threads as it needs.
The default value has changed several times: 8 before MySQL 5.0.8, 20 (infinite) from 5.0.8 through 5.0.18, 0 (infinite) from 5.0.19 to 5.0.20, and 8 (finite) from 5.0.21 on.
How long InnoDB
threads sleep before
joining the InnoDB
queue, in microseconds.
The default value is 10,000. A value of 0 disables sleep. This
variable was added in MySQL 5.0.3.
sync_binlog
If the value of this variable is positive, the MySQL server
synchronizes its binary log to disk
(fdatasync()
) after every
sync_binlog
writes to this binary log. Note
that there is one write to the binary log per statement if in
autocommit mode, and otherwise one write per transaction. The
default value is 0 which does no synchronizing to disk. A
value of 1 is the safest choice, because in the event of a
crash you lose at most one statement/transaction from the
binary log; however, it is also the slowest choice (unless the
disk has a battery-backed cache, which makes synchronization
very fast).
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 the
mysqld_safe wrapper 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, use the
--console
option.
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 13.2.3.1, “Using Per-Table Tablespaces”.
If InnoDB
prints an operating system error
during a file operation, usually the problem has one of the
following causes:
You did not create the InnoDB
data file
directory or the InnoDB
log directory.
mysqld does not have access rights to create files in those directories.
mysqld cannot read the proper
my.cnf
or my.ini
option file, and consequently does not see the options that
you specified.
The disk is full or a disk quota is exceeded.
You have created a subdirectory whose name is equal to a data file that you specified, so the name cannot be used as a filename.
There is a syntax error in the
innodb_data_home_dir
or
innodb_data_file_path
value.
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.
To create an InnoDB
table, specify an
ENGINE = InnoDB
option in the CREATE
TABLE
statement:
CREATE TABLE customers (a INT, b CHAR (20), INDEX (a)) ENGINE=InnoDB;
The older term TYPE
is supported as a synonym
for ENGINE
for backward compatibility, but
ENGINE
is the preferred term and
TYPE
is deprecated.
The statement creates a table and an index on column
a
in the InnoDB
tablespace
that consists of the data files that you specified in
my.cnf
. In addition, MySQL creates a file
customers.frm
in the
test
directory under the MySQL database
directory. Internally, InnoDB
adds an entry for
the table to its own data dictionary. The entry includes the
database name. For example, if test
is the
database in which the customers
table is
created, the entry is for 'test/customers'
.
This means you can create a table of the same name
customers
in some other database, and the table
names do not collide inside InnoDB
.
You can query the amount of free space in the
InnoDB
tablespace by issuing a SHOW
TABLE STATUS
statement for any InnoDB
table. The amount of free space in the tablespace appears in the
Comment
section in the output of SHOW
TABLE STATUS
. For example:
SHOW TABLE STATUS FROM test LIKE 'customers'
Note that the statistics SHOW
displays for
InnoDB
tables are only approximate. They are
used in SQL optimization. Table and index reserved sizes in bytes
are accurate, though.
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 use
COMMIT
and ROLLBACK
to
commit or roll back your transaction. If you want to leave
autocommit on, you can enclose your transactions within
START TRANSACTION
and either
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.
Important: Do not convert MySQL system tables in the
mysql
database (such as
user
or host
) to the
InnoDB
type. This is an unsupported
operation. The system tables must always be of the
MyISAM
type.
If you want all your (non-system) tables to be created as
InnoDB
tables, you can simply add the line
default-storage-engine=innodb
to the
[mysqld]
section of your server option file.
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 13.2.8.1, “Forcing InnoDB
Recovery”.
If you specify an AUTO_INCREMENT
column for
an InnoDB
table, the table handle in the
InnoDB
data dictionary contains a special
counter called the auto-increment counter that is used in
assigning new values for the column. This counter is stored only
in main memory, not on disk.
InnoDB
uses the following algorithm to
initialize the auto-increment counter for a table
t
that contains an
AUTO_INCREMENT
column named
ai_col
: After a server startup, for the first
insert into a table t
,
InnoDB
executes the equivalent of this
statement:
SELECT MAX(ai_col) FROM t FOR UPDATE;
InnoDB
increments by one the value retrieved
by the statement and assigns it to the column and to the
auto-increment counter for the table. If the table is empty,
InnoDB
uses the value 1
.
If a user invokes a SHOW TABLE STATUS
statement that displays output for the table
t
and the auto-increment counter has not been
initialized, InnoDB
initializes but does not
increment the value and stores it for use by later inserts. This
initialization uses a normal exclusive-locking read on the table
and the lock lasts to the end of the transaction.
InnoDB
follows the same procedure for
initializing the auto-increment counter for a freshly created
table.
After the auto-increment counter has been initialized, if a user
does not explicitly specify a value for an
AUTO_INCREMENT
column,
InnoDB
increments the counter by one and
assigns the new value to the column. If the user inserts a row
that explicitly specifies the column value, and the value is
bigger than the current counter value, the counter is set to the
specified column value.
When accessing the auto-increment counter,
InnoDB
uses a special table-level
AUTO-INC
lock that it keeps to the end of the
current SQL statement, not to the end of the transaction. The
special lock release strategy was introduced to improve
concurrency for inserts into a table containing an
AUTO_INCREMENT
column. Nevertheless, two
transactions cannot have the AUTO-INC
lock on
the same table simultaneously, which can have a performance
impact if the AUTO-INC
lock is held for a
long time. That might be the case for a statement such as
INSERT INTO t1 ... SELECT ... FROM t2
that
inserts all rows from one table into another.
InnoDB
uses the in-memory auto-increment
counter as long as the server runs. When the server is stopped
and restarted, InnoDB
reinitializes the
counter for each table for the first INSERT
to the table, as described earlier.
You may see gaps in the sequence of values assigned to the
AUTO_INCREMENT
column if you roll back
transactions that have generated numbers using the counter.
If a user specifies NULL
or
0
for the AUTO_INCREMENT
column in an INSERT
,
InnoDB
treats the row as if the value had not
been specified and generates a new value for it.
The behavior of the auto-increment mechanism is not defined if a user assigns 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.
An AUTO_INCREMENT
column must be the first
column listed if it is part of a multiple-column index in an
InnoDB
table.
Beginning with MySQL 5.0.3, InnoDB
supports
the AUTO_INCREMENT =
table option in
N
CREATE TABLE
and ALTER
TABLE
statements, to set the initial counter value or
alter the current counter value. The effect of this option is
canceled by a server restart, for reasons discussed earlier in
this section.
InnoDB
also supports foreign key constraints.
The syntax for a foreign key constraint definition in
InnoDB
looks like this:
[CONSTRAINTsymbol
] FOREIGN KEY [id
] (index_col_name
, ...) REFERENCEStbl_name
(index_col_name
, ...) [ON DELETE {RESTRICT | CASCADE | SET NULL | NO ACTION}] [ON UPDATE {RESTRICT | CASCADE | SET NULL | NO ACTION}]
Foreign keys definitions are subject to the following conditions:
Both tables must be InnoDB
tables and
they must not be TEMPORARY
tables.
Corresponding columns in the foreign key and the referenced
key must have similar internal data types inside
InnoDB
so that they can be compared
without a type conversion. The size and sign of
integer types must be the same. The length of
string types need not be the same. For non-binary
(character) string columns, the character set and collation
must be the same.
In the referencing table, there must be an index where the foreign key columns are listed as the first columns in the same order. Such an index is created on the referencing table automatically if it does not exist.
In the referenced table, there must be an index where the referenced columns are listed as the first columns in the same order.
Index prefixes on foreign key columns are not supported. One
consequence of this is that BLOB
and
TEXT
columns cannot be included in a
foreign key, because indexes on those columns must always
include a prefix length.
If the CONSTRAINT
clause is given,
the symbol
symbol
value must be unique
in the database. If the clause is not given,
InnoDB
creates the name automatically.
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:
CASCADE
: Delete or update the row from
the parent table and automatically delete or update the
matching rows in the child table. Both ON DELETE
CASCADE
and ON UPDATE CASCADE
are supported. Between two tables, you should not define
several ON UPDATE CASCADE
clauses that
act on the same column in the parent table or in the child
table.
SET NULL
: Delete or update the row from
the parent table and set the foreign key column or columns
in the child table to NULL
. This is valid
only if the foreign key columns do not have the NOT
NULL
qualifier specified. Both ON DELETE
SET NULL
and ON UPDATE SET NULL
clauses are supported.
If you specify a SET NULL
action,
make sure that you have not declared the columns
in the child table as NOT
NULL
.
NO ACTION
: In standard SQL, NO
ACTION
means no action in the
sense that an attempt to delete or update a primary key
value is not allowed to proceed if there is a related
foreign key value in the referenced table.
InnoDB
rejects the delete or update
operation for the parent table.
RESTRICT
: Rejects the delete or update
operation for the parent table. NO ACTION
and RESTRICT
are the same as omitting the
ON DELETE
or ON UPDATE
clause. (Some database systems have deferred checks, and
NO ACTION
is a deferred check. In MySQL,
foreign key constraints are checked immediately, so
NO ACTION
and RESTRICT
are the same.)
SET DEFAULT
: This action is recognized by
the parser, but InnoDB
rejects table
definitions containing ON DELETE SET
DEFAULT
or ON UPDATE SET
DEFAULT
clauses.
Note that InnoDB
supports foreign key
references within a table. In these cases, “child table
records” really refers to dependent records within the
same table.
InnoDB
requires indexes on foreign keys and
referenced keys so that foreign key checks can be fast and not
require a table scan. The index on the foreign key is created
automatically. This is in contrast to some older versions, in
which indexes had to be created explicitly or the creation of
foreign key constraints would fail.
If MySQL reports an error number 1005 from a CREATE
TABLE
statement, and the error message refers to errno
150, table creation failed because a foreign key constraint was
not correctly formed. Similarly, if an ALTER
TABLE
fails and it refers to errno 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.
InnoDB
does not check foreign key
constraints on those foreign key or referenced key values that
contain a NULL
column.
Currently, triggers are not activated by cascaded foreign key actions.
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.
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 TABLEtbl_name
ADD [CONSTRAINTsymbol
] FOREIGN KEY [id
] (index_col_name
, ...) REFERENCEStbl_name
(index_col_name
, ...) [ON DELETE {RESTRICT | CASCADE | SET NULL | NO ACTION}] [ON UPDATE {RESTRICT | CASCADE | SET NULL | NO ACTION}]
Remember to create the required indexes
first. You can also add a self-referential foreign
key constraint to a table using ALTER TABLE
.
InnoDB
also supports the use of
ALTER TABLE
to drop foreign keys:
ALTER TABLEtbl_name
DROP FOREIGN KEYfk_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 to 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 FROMdb_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
mysql>dump_file_name
;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 errno 150 in the error message.
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 13.2.8, “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.
You cannot set up replication for InnoDB
using the LOAD TABLE FROM MASTER
statement,
which works only for MyISAM
tables. There are
two possible workarounds:
Dump the table on the master and import the dump file into the slave.
Use ALTER TABLE
on the master before setting up
replication with tbl_name
ENGINE=MyISAMLOAD TABLE
,
and then use tbl_name
FROM MASTERALTER TABLE
to convert the
master table back to InnoDB
afterward.
However, this should not be done for tables that have
foreign key definitions because the definitions will be
lost.
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 to the slave only
if both the master's and slave' versions of the
tables sharing the foreign key relation use
InnoDB
. 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 to the slave. 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.
This section describes what you can do when your
InnoDB
tablespace runs out of room or when you
want to change the size of the log files.
The easiest way to increase the size of the
InnoDB
tablespace is to configure it from the
beginning to be auto-extending. Specify the
autoextend
attribute for the last data file in
the tablespace definition. Then InnoDB
increases the size of that file automatically in 8MB increments
when it runs out of space. The increment size can be changed by
setting the value of the
innodb_autoextend_increment
system variable,
which is measured in MB.
Alternatively, you can increase the size of your tablespace by
adding another data file. To do this, you have to shut down the
MySQL server, change the tablespace configuration to add a new
data file to the end of innodb_data_file_path
,
and start the server again.
If your last data file was defined with the keyword
autoextend
, the procedure for reconfiguring the
tablespace must take into account the size to which the last data
file has grown. Obtain the size of the data file, round it down to
the closest multiple of 1024 × 1024 bytes (= 1MB), and
specify the rounded size explicitly in
innodb_data_file_path
. Then you can add another
data file. Remember that only the last data file in the
innodb_data_file_path
can be specified as
auto-extending.
As an example, assume that the tablespace has just one
auto-extending data file ibdata1
:
innodb_data_home_dir = innodb_data_file_path = /ibdata/ibdata1:10M:autoextend
Suppose that this data file, over time, has grown to 988MB. Here is the configuration line after modifying the original data file to not be auto-extending and adding another auto-extending data file:
innodb_data_home_dir = innodb_data_file_path = /ibdata/ibdata1:988M;/disk2/ibdata2:50M:autoextend
When you add a new file to the tablespace configuration, make sure
that it does not exist. InnoDB
will create and
initialize the file when you restart the server.
Currently, you cannot remove a data file from the tablespace. To decrease the size of your tablespace, use this procedure:
Use mysqldump to dump all your
InnoDB
tables.
Stop the server.
Remove all the existing tablespace files, including the
ibdata
and ib_log
files. If you want to keep a backup copy of the information,
then copy all the ib*
files to another
location before the removing the files in your MySQL
installation.
Remove any .frm
files for
InnoDB
tables.
Configure a new tablespace.
Restart the server.
Import the dump files.
If you want to change the number or the size of your
InnoDB
log files, use the following
instructions. The procedure to use depends on the value of
innodb_fast_shutdown
:
If innodb_fast_shutdown
is not set to 2:
You must stop the MySQL server and make sure that it shuts
down without errors (to ensure that there is no information
for outstanding transactions in the logs). Then copy the old
log files into a safe place just in case something went wrong
in the shutdown and you need them to recover the tablespace.
Delete the old log files from the log file directory, edit
my.cnf
to change the log file
configuration, and start the MySQL server again.
mysqld sees that no log files exist at
startup and tells you that it is creating new ones.
If innodb_fast_shutdown
is set to 2: You
should shut down the server, set
innodb_fast_shutdown
to 1, and restart the
server. The server should be allowed to recover. Then you
should shut down the server again and follow the procedure
described in the preceding item to change
InnoDB
log file size. Set
innodb_fast_shutdown
back to 2 and restart
the server.
The key to safe database management is making regular backups.
InnoDB Hot Backup is an online backup tool you
can use to backup your InnoDB
database while it
is running. InnoDB Hot Backup does not require
you to shut down your database and it does not set any locks or
disturb your normal database processing. InnoDB Hot
Backup is a non-free (commercial) add-on tool with an
annual license fee of €390 per computer on which the MySQL
server is run. See the
InnoDB Hot
Backup home page for detailed information and
screenshots.
If you are able to shut down your MySQL server, you can make a
binary backup that consists of all files used by
InnoDB
to manage its tables. Use the following
procedure:
Shut down your MySQL server and make sure that it shuts down without errors.
Copy all your data files (ibdata
files
and .ibd
files) into a safe place.
Copy all your ib_logfile
files to a safe
place.
Copy your my.cnf
configuration file or
files to a safe place.
Copy all the .frm
files for your
InnoDB
tables to a safe place.
Replication works with InnoDB
tables, so you
can use MySQL replication capabilities to keep a copy of your
database at database sites requiring high availability.
In addition to making binary backups as just described, you should
also regularly make dumps of your tables with
mysqldump. The reason for this is that a binary
file might be corrupted without you noticing it. Dumped tables are
stored into text files that are human-readable, so spotting table
corruption becomes easier. Also, because the format is simpler,
the chance for serious data corruption is smaller.
mysqldump also has a
--single-transaction
option that you can use to
make a consistent snapshot without locking out other clients.
To be able to recover your InnoDB
database to
the present from the binary backup just described, you have to run
your MySQL server with binary logging turned on. Then you can
apply the binary log to the backup database to achieve
point-in-time recovery:
mysqlbinlog yourhostname
-bin.123 | mysql
To recover from a crash of your MySQL server, the only requirement
is to restart it. InnoDB
automatically checks
the logs and performs a roll-forward of the database to the
present. InnoDB
automatically rolls back
uncommitted transactions that were present at the time of the
crash. During recovery, mysqld displays output
something like this:
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 that is not corrupted. After restoring the base backup, do the recovery from the binary log files using mysqlbinlog and mysql to restore the changes performed after the backup was made.
In some cases of database corruption it is enough just to dump,
drop, and re-create one or a few corrupt tables. You can use the
CHECK TABLE
SQL statement to check whether a
table is corrupt, although CHECK TABLE
naturally cannot detect every possible kind of corruption. You can
use innodb_tablespace_monitor
to check the
integrity of the file space management inside the tablespace
files.
In some cases, apparent database page corruption is actually due to the operating system corrupting its own file cache, and the data on disk may be okay. It is best first to try restarting your computer. Doing so may eliminate errors that appeared to be database page corruption.
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. Even so, the corruption may cause SELECT
* FROM
statements
or tbl_name
InnoDB
background operations to crash or
assert, or even to cause InnoDB
roll-forward
recovery to crash. However, you can 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
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.
1
(SRV_FORCE_IGNORE_CORRUPT
)
Let the server run even if it detects a corrupt page. Try to
make SELECT * FROM
jump over
corrupt index records and pages, which helps in dumping
tables.
tbl_name
2
(SRV_FORCE_NO_BACKGROUND
)
Prevent the main thread from running. If a crash would occur during the purge operation, this recovery value prevents it.
3
(SRV_FORCE_NO_TRX_UNDO
)
Do not run transaction rollbacks after recovery.
4
(SRV_FORCE_NO_IBUF_MERGE
)
Prevent also insert buffer merge operations. If they would cause a crash, do not do them. Do not calculate table statistics.
5
(SRV_FORCE_NO_UNDO_LOG_SCAN
)
Do not look at undo logs when starting the database:
InnoDB
treats even incomplete
transactions as committed.
6
(SRV_FORCE_NO_LOG_REDO
)
Do not do the log roll-forward in connection with recovery.
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.
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.
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 save disk I/O in checkpointing. It often makes sense to set the total size of the log files as big as the buffer pool or even bigger. The drawback of using large log files is that crash recovery can take longer because there is more logged information to apply to the database.
On Windows, InnoDB
always stores database and
table names internally in lowercase. To move databases in a binary
format from Unix to Windows or from Windows to Unix, you should
have all table and database names in lowercase. A convenient way
to accomplish this is to add the following line to the
[mysqld]
section of your
my.cnf
or my.ini
file
before creating any databases or tables:
[mysqld] lower_case_table_names=1
Like MyISAM
data files,
InnoDB
data and log files are binary-compatible
on all platforms having the same floating-point number format. You
can move an InnoDB
database simply by copying
all the relevant files listed in Section 13.2.8, “Backing Up and Recovering an InnoDB
Database”.
If the floating-point formats differ but you have not used
FLOAT
or DOUBLE
data types
in your tables, then the procedure is the same: simply copy the
relevant files. If the formats differ and your tables contain
floating-point data, you must use mysqldump to
dump your tables on one machine and then import the dump files on
the other machine.
One way to increase performance is to switch off autocommit mode when importing data, assuming that the tablespace has enough space for the big rollback segment that the import transactions generate. Do the commit only after importing a whole table or a segment of a table.
InnoDB
Lock ModesInnoDB
and AUTOCOMMIT
InnoDB
and TRANSACTION ISOLATION
LEVEL
SELECT ... FOR UPDATE
and SELECT ... LOCK IN
SHARE MODE
Locking ReadsInnoDB
InnoDB
In the InnoDB
transaction model, the goal is to
combine the best properties of a multi-versioning database with
traditional two-phase locking. InnoDB
does
locking on the row level and runs queries as non-locking
consistent reads by default, 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.
InnoDB
implements standard row-level locking
where there are two types of locks:
A shared (S
) lock allows a
transaction to read a row (tuple).
An exclusive (X
) lock allows a
transaction to update or delete a row.
If transaction T1
holds a shared
(S
) lock on tuple
t
, then
A request from some distinct transaction
T2
for an S
lock on t
can be granted immediately. As
a result, both T1
and
T2
hold an S
lock on t
.
A request from some distinct transaction
T2
for an X
lock on t
cannot be granted immediately.
If a transaction T1
holds an exclusive
(X
) lock on tuple
t
, then a request from some distinct
transaction T2
for a lock of either type on
t
cannot be granted immediately. Instead,
transaction T2
has to wait for transaction
T1
to release its lock on tuple
t
.
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 R
):
Intention shared (IS
):
Transaction T
intends to set
S
locks on individual rows in
table R
.
Intention exclusive (IX
):
Transaction T
intends to set
X
locks on those rows.
The intention locking protocol is as follows:
Before a given transaction can acquire an
S
lock on a given row, it must
first acquire an IS
or stronger
lock on the table containing that row.
Before a given transaction can acquire an
X
lock on a given row, it must
first acquire an IX
lock on the
table containing that row.
These rules can be conveniently summarized by means of a lock type compatibility matrix:
X | IX | S | IS | |
X | Conflict | Conflict | Conflict | Conflict |
IX | Conflict | Compatible | Conflict | Compatible |
S | Conflict | Conflict | Compatible | Compatible |
IS | Conflict | Compatible | Compatible | Compatible |
A lock is granted to a requesting transaction if it is compatible with existing locks. A lock is not granted to a requesting transaction 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.
In InnoDB
, all user activity occurs inside a
transaction. If the autocommit mode is enabled, each SQL
statement forms a single transaction on its own. By default,
MySQL starts new connections with autocommit enabled.
If the autocommit mode is switched off with SET
AUTOCOMMIT = 0
, then we can consider that a user
always has a transaction open. An SQL COMMIT
or ROLLBACK
statement ends the current
transaction and a new one starts. A COMMIT
means that the changes made in the current transaction are made
permanent and become visible to other users. A
ROLLBACK
statement, on the other hand,
cancels all modifications made by the current transaction. Both
statements release all InnoDB
locks that were
set during the current transaction.
If the connection has autocommit enabled, the user can still
perform a multiple-statement transaction by starting it with an
explicit START TRANSACTION
or
BEGIN
statement and ending it with
COMMIT
or ROLLBACK
.
In terms of the SQL:1992 transaction isolation levels, the
InnoDB
default is REPEATABLE
READ
. InnoDB
offers all four
transaction isolation levels described by the SQL standard. You
can set the default isolation level for all connections by using
the --transaction-isolation
option on the
command line or in an option file. For example, you can set the
option in the [mysqld]
section of an option
file like this:
[mysqld] transaction-isolation = {READ-UNCOMMITTED | READ-COMMITTED | REPEATABLE-READ | SERIALIZABLE}
A user can change the isolation level for a single session or
for all new incoming connections with the SET
TRANSACTION
statement. Its syntax is as follows:
SET [SESSION | GLOBAL] TRANSACTION ISOLATION LEVEL {READ UNCOMMITTED | READ COMMITTED | REPEATABLE READ | SERIALIZABLE}
Note that there are hyphens in the level names for the
--transaction-isolation
option, but not for the
SET TRANSACTION
statement.
The default behavior is to set the isolation level for the next
(not started) transaction. If you use the
GLOBAL
keyword, the statement sets the
default transaction level globally for all new connections
created from that point on (but not for existing connections).
You need the SUPER
privilege to do this.
Using the SESSION
keyword sets the default
transaction level for all future transactions performed on the
current connection.
Any client is free to change the session isolation level (even in the middle of a transaction), or the isolation level for the next transaction.
You can determine the global and session transaction isolation
levels by checking the value of the
tx_isolation
system variable with these
statements:
SELECT @@global.tx_isolation; SELECT @@tx_isolation;
In row-level locking, InnoDB
uses next-key
locking. That means that besides index records,
InnoDB
can also lock the “gap”
preceding an index record to block insertions by other users
immediately before the index record. A next-key lock refers to a
lock that locks an index record and the gap before it. A gap
lock refers to a lock that only locks a gap before some index
record. Next-key locking for searches or index scans can be
disabled by enabling the
innodb_locks_unsafe_for_binlog
system
variable.
A detailed description of each isolation level in
InnoDB
follows:
READ UNCOMMITTED
SELECT
statements are performed in a
non-locking fashion, but a possible earlier version of a
record might be used. Thus, using this isolation level, such
reads are not consistent. This is also called a “dirty
read.” Otherwise, this isolation level works like
READ COMMITTED
.
READ COMMITTED
A somewhat Oracle-like isolation level. All SELECT
... FOR UPDATE
and SELECT ... LOCK IN
SHARE MODE
statements lock only the index records,
not the gaps before them, and thus allow the free insertion
of new records next to locked records.
UPDATE
and DELETE
statements using a unique index with a unique search
condition lock only the index record found, not the gap
before it. In range-type UPDATE
and
DELETE
statements,
InnoDB
must set next-key or gap locks and
block insertions by other users to the gaps covered by the
range. This is necessary because “phantom rows”
must be blocked for MySQL replication and recovery to work.
Consistent reads behave as in Oracle: Each consistent read, even within the same transaction, sets and reads its own fresh snapshot. See Section 13.2.10.4, “Consistent Non-Locking Read”.
REPEATABLE READ
This is the default isolation level of
InnoDB
. SELECT ... FOR
UPDATE
, SELECT ... LOCK IN SHARE
MODE
, UPDATE
, and
DELETE
statements that use a unique index
with a unique search condition lock only the index record
found, not the gap before it. With other search conditions,
these operations employ next-key locking, locking the index
range scanned with next-key or gap locks, and block new
insertions by other users.
In consistent reads, there is an important difference from
the READ COMMITTED
isolation level: All
consistent reads within the same transaction read the same
snapshot established by the first read. This convention
means that if you issue several plain
SELECT
statements within the same
transaction, these SELECT
statements are
consistent also with respect to each other. See
Section 13.2.10.4, “Consistent Non-Locking Read”.
SERIALIZABLE
This level is like REPEATABLE READ
, but
InnoDB
implicitly converts all plain
SELECT
statements to SELECT ...
LOCK IN SHARE MODE
.
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
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 sees the changes made
by earlier statements within the same transaction. Note that the
exception to the rule 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 users simultaneously
update the same table, the anomaly means that you may see the
table in a state that never existed in the database.
If you are running with the default REPEATABLE
READ
isolation 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.
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 users are free to modify those
tables at the same time a consistent read is being performed on
the table.
Note that consistent read does not work over DROP
TABLE
and over ALTER TABLE
.
Consistent read does not work over DROP TABLE
because MySQL can't use a table that has been dropped and
InnoDB
destroys the table. Consistent read
does not work over ALTER TABLE
because
ALTER TABLE
works by making a temporary copy
of the original table and deleting the original table when the
temporary copy is built. When you reissue a consistent read
within a transaction, rows in the new table are not visible
because those rows did not exist when the transaction's snapshot
was taken.
InnoDB
uses a consistent read for select in
clauses like INSERT INTO ... SELECT
and
UPDATE ... (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 to rows read from 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 read is not convenient. For
example, you might want to add a new row into your table
child
, and make sure that the child has a
parent in table parent
. The following example
shows how to implement referential integrity in your application
code.
Suppose that you use a consistent read to read the table
parent
and indeed see the parent of the child
in the table. Can you safely add the child row to table
child
? No, because it may happen that
meanwhile some other user deletes the parent row from the table
parent
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;
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.
A shared mode lock prevents others from updating or deleting the
row we have read. Also, if the latest data belongs to a yet
uncommitted transaction of another client connection, we wait
until that transaction commits. After we see that the preceding
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
. Obviously, using a consistent read or
a shared mode read to read the present value of the counter is
not a good idea 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 attempting to
update the counter.
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. 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.
Locks set by IN SHARE MODE
and FOR
UPDATE
reads are released when the transaction is
committed or rolled back.
Locking of rows for update using SELECT FOR
UPDATE
only applies when
AUTOCOMMIT
is switched off. If
AUTOCOMMIT
is on, then the rows matching
the specification are not locked.
In row-level locking, InnoDB
uses an
algorithm called next-key locking.
InnoDB
performs the row-level locking in such
a way that when it searches or scans an index of a table, it
sets shared or exclusive locks on the index records it
encounters. Thus, the row-level locks are actually index record
locks.
The next-key locks that 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, another user cannot insert a
new index record immediately before R
in the
index order. (A gap lock refers to a lock that only locks a gap
before some index record.)
This next-key locking of gaps is done to prevent the so-called
“phantom problem.” Suppose that you want to read
and lock all children from the child
table
having an identifier value greater than 100, with the intention
of updating some column in the selected rows later:
SELECT * FROM child WHERE id > 100 FOR UPDATE;
Suppose that there is an index on the id
column. The query scans that index starting from the first
record where id
is bigger than 100. If the
locks set on the index records would not lock out inserts made
in the gaps, a new row might meanwhile be inserted to the table.
If you execute the same SELECT
within the
same transaction, you would see a new row in the result set
returned by the query. This is contrary to 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, the new
“phantom” child would violate 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
prevent any insert to the table where id
would be bigger than 100.
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.
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.
User A User 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
In this example, user 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.
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;
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 if 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 record locks are normally
next-key locks that also block inserts to the “gap”
immediately before the record.
If the locks to be set are exclusive, InnoDB
always retrieves also the clustered index record and sets a lock
on it.
If you do not have indexes suitable for your statement and MySQL has to scan the whole 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 need to 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:
SELECT ... FROM
is a consistent read,
reading a snapshot of the database and setting no locks
unless the transaction isolation level is set to
SERIALIZABLE
. For
SERIALIZABLE
level, this sets shared
next-key locks on the index records it encounters.
SELECT ... FROM ... LOCK IN SHARE MODE
sets shared next-key locks on all index records the read
encounters.
SELECT ... FROM ... FOR UPDATE
sets
exclusive next-key locks on all index records the read
encounters.
UPDATE ... WHERE ...
sets an exclusive
next-key lock on every record the search encounters.
DELETE FROM ... WHERE ...
sets an
exclusive next-key lock on every record the search
encounters.
INSERT INTO ... VALUES (...)
sets an
exclusive lock on the inserted row. Note that this lock is
not a next-key lock and does not prevent other users from
inserting to the gap before the inserted row. If a
duplicate-key error occurs, a shared lock on the duplicate
index record is set.
REPLACE
is done like an
INSERT
if there is no collision on a
unique key. Otherwise, an exclusive next-key lock is placed
on the row that has to be updated.
While initializing a previously specified
AUTO_INCREMENT
column on a table,
InnoDB
sets an exclusive lock on the end
of the index associated with the
AUTO_INCREMENT
column. In accessing the
auto-increment counter, InnoDB
uses a
specific table lock mode AUTO-INC
where
the lock lasts only to the end of the current SQL statement,
not to the end of the entire transaction. Note that other
clients cannot insert into the table while the
AUTO-INC
table lock is held; see
Section 13.2.10.2, “InnoDB
and AUTOCOMMIT
”.
InnoDB
fetches the value of a previously
initialized AUTO_INCREMENT
column without
setting any locks.
INSERT INTO T SELECT ... FROM S WHERE ...
sets an exclusive (non-next-key) lock on each row inserted
into T
. InnoDB
sets
shared next-key locks on S
, unless
innodb_locks_unsafe_for_binlog
is
enabled, in which case it does the search on
S
as a consistent read.
InnoDB
has to set locks in the latter
case: In roll-forward recovery from a backup, every SQL
statement has to be executed in exactly the same way it was
done originally.
CREATE TABLE ... SELECT ...
performs the
SELECT
as a consistent read or with
shared locks, as in the previous item.
If a FOREIGN KEY
constraint is defined on
a table, any insert, update, or delete that requires the
constraint condition to be checked sets shared record-level
locks on the records that it looks at to check the
constraint. InnoDB
also sets these locks
in the case where the constraint fails.
LOCK TABLES
sets table locks, but it is
the higher MySQL layer above the InnoDB
layer that sets these locks. InnoDB
is
aware of table locks if
innodb_table_locks=1
(the default) and
AUTOCOMMIT=0
, and the MySQL layer above
InnoDB
knows about row-level locks.
Otherwise, InnoDB
's automatic deadlock
detection cannot detect deadlocks where such table locks are
involved. Also, because the higher MySQL layer does not know
about row-level locks, it is possible to get a table lock on
a table where another user currently has row-level locks.
However, this does not endanger transaction integrity, as
discussed in Section 13.2.10.10, “Deadlock Detection and Rollback”.
See also Section 13.2.16, “Restrictions on InnoDB
Tables”.
By default, MySQL begins each client connection with autocommit
mode enabled. When autocommit is enabled, MySQL does a commit
after each SQL statement if that statement did not return an
error. If an SQL statement returns an error, the commit or
rollback behavior depends on the error. See
Section 13.2.15, “InnoDB
Error Handling”.
If you have the autocommit mode off and close a connection without explicitly committing the final transaction, MySQL rolls back that transaction.
For details about which statements implicitly end a transaction,
as if you had done a COMMIT
before executing
the statement, 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.
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:
Use SHOW ENGINE INNODB STATUS
to
determine the cause of the latest deadlock. That can help
you to tune your application to avoid deadlocks.
Always be prepared to re-issue a transaction if it fails due to deadlock. Deadlocks are not dangerous. Just try again.
Commit your transactions often. Small transactions are less prone to collision.
If you are using locking reads (SELECT ... FOR
UPDATE
or ... LOCK IN SHARE
MODE
), try using a lower isolation level such as
READ COMMITTED
.
Access your tables and rows in a fixed order. Then transactions form well-defined queues and do not deadlock.
Add well-chosen indexes to your tables. Then your queries
need to scan fewer index records and consequently set fewer
locks. Use EXPLAIN SELECT
to determine
which indexes the MySQL server regards as the most
appropriate for your queries.
Use less locking. If you can afford to allow a
SELECT
to return data from an old
snapshot, do not add the clause FOR
UPDATE
or LOCK IN SHARE MODE
to
it. Using the READ COMMITTED
isolation
level is good here, because each consistent read within the
same transaction reads from its own fresh snapshot. You
should also set the value of
innodb_support_xa
to 0 which will reduce
the number of disk flushes due to synchronizing on disk data
and the binary log.
If nothing else helps, serialize your transactions with
table-level locks. The correct way to use LOCK
TABLES
with transactional tables, such as
InnoDB
tables, is to set
AUTOCOMMIT = 0
and not to call
UNLOCK TABLES
until after you commit the
transaction explicitly. For example, if you need to write to
table t1
and read from table
t2
, you can do this:
SET AUTOCOMMIT=0;
LOCK TABLES t1 WRITE, t2 READ, ...;
... do something with tables t1 and t2 here ...
COMMIT;
UNLOCK TABLES;
Table-level locks make your transactions queue nicely, and deadlocks are avoided.
Another way to serialize transactions is to create an
auxiliary “semaphore” table that contains just
a single row. Have each transaction update that row before
accessing other tables. In that way, all transactions happen
in a serial fashion. Note that the InnoDB
instant deadlock detection algorithm also works in this
case, because the serializing lock is a row-level lock. With
MySQL table-level locks, the timeout method must be used to
resolve deadlocks.
In InnoDB
, having a long PRIMARY
KEY
wastes a lot of disk space because its value
must be stored with every secondary index record. (See
Section 13.2.13, “InnoDB
Table and Index Structures”.) Create an
AUTO_INCREMENT
column as the primary key if
your primary key is long.
If the Unix top
tool 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 equal to more than 80% of physical memory.
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. The rotation speed of a disk is typically at
most 167 revolutions/second, which constrains the number of
commits to the same 167th of a
second if the disk does not “fool” the operating
system.
If you can afford the loss of some of the latest committed
transactions if a crash occurs, you can set the
innodb_flush_log_at_trx_commit
parameter to
0. InnoDB
tries to flush the log once per
second anyway, although the flush is not guaranteed.
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 cause many unnecessary disk
writes. The drawback of big log files is that the recovery
time is longer.
Make the log buffer quite large as well (on the order of 8MB).
Use the VARCHAR
data type instead of
CHAR
if you are storing variable-length
strings or if the column may contain many
NULL
values. A
CHAR(
column
always takes N
)N
characters to store
data, even if the string is shorter or its value is
NULL
. Smaller tables fit better in the
buffer pool and reduce disk I/O.
When using row_format=compact
(the default
InnoDB
record format in MySQL
5.0) and variable-length character sets, such as
utf8
or sjis
,
CHAR(
will
occupy a variable amount of space, at least
N
)N
bytes.
In some versions of GNU/Linux and Unix, flushing files to disk
with the Unix fsync()
call (which
InnoDB
uses by default) and other similar
methods is surprisingly slow. If you are dissatisfied with
database write performance, you might try setting the
innodb_flush_method
parameter to
O_DSYNC
. Although
O_DSYNC
seems to be slower on most systems,
yours might not be one of them.
When using the InnoDB
storage engine on
Solaris 10 for x86_64 architecture (AMD Opteron), it is
important to mount any filesystems used for storing
InnoDB
-related files using the
forcedirectio
option. (The default on
Solaris 10/x86_64 is not to use this
option.) Failure to use forcedirectio
causes a serious degradation of InnoDB
's
speed and performance on this platform.
When using the InnoDB
storage engine with a
large innodb_buffer_pool_size
value on any
release of Solaris 2.6 and up and any platform
(sparc/x86/x64/amd64), a significant performance gain can be
achieved by placing InnoDB
data files and
log files on raw devices or on a separate direct I/O UFS
filesystem (using mount option
forcedirectio
; see
mount_ufs(1M)
). Users of the Veritas
filesystem VxFS should use the mount option
convosync=direct
.
Other MySQL data files, such as those for
MyISAM
tables, should not be placed on a
direct I/O filesystem. Executables or libraries must
not be placed on a direct I/O filesystem.
When importing data into InnoDB
, make sure
that MySQL does not have autocommit mode enabled because that
requires a log flush to disk for every insert. To disable
autocommit during your import operation, surround it with
SET AUTOCOMMIT
and
COMMIT
statements:
SET AUTOCOMMIT=0;
... SQL import statements ...
COMMIT;
If you use the mysqldump option
--opt
, you get dump files that are fast to
import into an InnoDB
table, even without
wrapping them with the SET AUTOCOMMIT
and
COMMIT
statements.
Beware of big rollbacks of mass inserts:
InnoDB
uses the insert buffer to save disk
I/O in inserts, but no such mechanism is used in a
corresponding rollback. A disk-bound rollback can take 30
times as long to perform as the corresponding insert. Killing
the database process does not help because the rollback starts
again on server 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 to use a special
procedure. See Section 13.2.8.1, “Forcing InnoDB
Recovery”.
Beware also of other big disk-bound operations. Use
DROP TABLE
and CREATE
TABLE
to empty a table, not DELETE FROM
.
tbl_name
Use the multiple-row INSERT
syntax 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 valid for inserts into any table, not just
InnoDB
tables.
If you have UNIQUE
constraints on secondary
keys, you can speed up table imports by temporarily turning
off the uniqueness checks during the import session:
SET UNIQUE_CHECKS=0;
... import operation ...
SET UNIQUE_CHECKS=1;
For big tables, this saves a lot of disk I/O because
InnoDB
can use its insert buffer to write
secondary index records in a batch. Be certain that the data
contains no duplicate keys. UNIQUE_CHECKS
allows but does not require storage engines to ignore
duplicate keys.
If you have FOREIGN KEY
constraints in your
tables, you can speed up table imports by turning the foreign
key checks off for the duration of the import session:
SET FOREIGN_KEY_CHECKS=0;
... import operation ...
SET FOREIGN_KEY_CHECKS=1;
For big tables, this can save a lot of disk I/O.
If you often have recurring queries for tables that are not updated frequently, use the query cache:
[mysqld] query_cache_type = ON query_cache_size = 10M
Unlike MyISAM
, InnoDB
does not store an index cardinality value in its tables.
Instead, InnoDB
computes a cardinality for
a table the first time it accesses it after startup. With a
large number of tables, this might take significant time. It
is the initial table open operation that is important, so to
“warm up” a table for later use, you might want
to use it immediately after start up by issuing a statement
such as SELECT 1 FROM
.
tbl_name
LIMIT 1
MySQL Enterprise For optimization recommendations geared to your specific circumstances subscribe to the MySQL Enterprise Monitor. For more information see http://www.mysql.com/products/enterprise/advisors.html.
InnoDB
includes InnoDB
Monitors that print information about the
InnoDB
internal state. You can use the
SHOW ENGINE INNODB STATUS
SQL statement at
any time to fetch the output of the standard
InnoDB
Monitor to your SQL client. This
information is useful in performance tuning. (If you are using
the mysql interactive SQL client, the output
is more readable if you replace the usual semicolon statement
terminator with \G
.) For a discussion of
InnoDB
lock modes, see
Section 13.2.10.1, “InnoDB
Lock Modes”.
mysql> SHOW ENGINE INNODB STATUS\G
Another way to use InnoDB
Monitors is to let
them periodically write data to the standard output of the
mysqld server. In this case, no output is
sent to clients. When switched on, InnoDB
Monitors print data about every 15 seconds. Server output
usually is directed to the .err
log in the
MySQL data directory. This data is useful in performance tuning.
On Windows, you must start the server from a command prompt in a
console window with the --console
option if you
want to direct the output to the window rather than to the error
log.
Monitor output includes the following types of information:
Table and record locks held by each active transaction
Lock waits of a transactions
Semaphore waits of threads
Pending file I/O requests
Buffer pool statistics
Purge and insert buffer merge activity of the main
InnoDB
thread
To cause the standard InnoDB
Monitor to write
to the standard output of mysqld, use the
following SQL statement:
CREATE TABLE innodb_monitor (a INT) ENGINE=INNODB;
The monitor can be stopped by issuing the following statement:
DROP TABLE innodb_monitor;
The CREATE TABLE
syntax is just a way to pass
a command to the InnoDB
engine through
MySQL's SQL parser: The only things that matter are the table
name innodb_monitor
and that it be an
InnoDB
table. The structure of the table is
not relevant at all for the InnoDB
Monitor.
If you shut down the server, the monitor does not restart
automatically when you restart the server. You must drop the
monitor table and issue a new CREATE TABLE
statement to start the monitor. (This syntax may change in a
future release.)
You can use innodb_lock_monitor
in a similar
fashion. This is the same as innodb_monitor
,
except that it also provides a great deal of lock information. A
separate innodb_tablespace_monitor
prints a
list of created file segments existing in the tablespace and
validates the tablespace allocation data structures. In
addition, there is innodb_table_monitor
with
which you can print the contents of the
InnoDB
internal data dictionary.
A sample of InnoDB
Monitor output:
mysql> SHOW ENGINE INNODB STATUS\G
*************************** 1. row ***************************
Status:
=====================================
030709 13:00:59 INNODB MONITOR OUTPUT
=====================================
Per second averages calculated from the last 18 seconds
----------
SEMAPHORES
----------
OS WAIT ARRAY INFO: reservation count 413452, signal count 378357
--Thread 32782 has waited at btr0sea.c line 1477 for 0.00 seconds the
semaphore: X-lock on RW-latch at 41a28668 created in file btr0sea.c line 135
a writer (thread id 32782) has reserved it in mode wait exclusive
number of readers 1, waiters flag 1
Last time read locked in file btr0sea.c line 731
Last time write locked in file btr0sea.c line 1347
Mutex spin waits 0, rounds 0, OS waits 0
RW-shared spins 108462, OS waits 37964; RW-excl spins 681824, OS waits
375485
------------------------
LATEST FOREIGN KEY ERROR
------------------------
030709 13:00:59 Transaction:
TRANSACTION 0 290328284, ACTIVE 0 sec, process no 3195, OS thread id 34831
inserting
15 lock struct(s), heap size 2496, undo log entries 9
MySQL thread id 25, query id 4668733 localhost heikki update
insert into ibtest11a (D, B, C) values (5, 'khDk' ,'khDk')
Foreign key constraint fails for table test/ibtest11a:
,
CONSTRAINT `0_219242` FOREIGN KEY (`A`, `D`) REFERENCES `ibtest11b` (`A`,
`D`) ON DELETE CASCADE ON UPDATE CASCADE
Trying to add in child table, in index PRIMARY tuple:
0: len 4; hex 80000101; asc ....;; 1: len 4; hex 80000005; asc ....;; 2:
len 4; hex 6b68446b; asc khDk;; 3: len 6; hex 0000114e0edc; asc ...N..;; 4:
len 7; hex 00000000c3e0a7; asc .......;; 5: len 4; hex 6b68446b; asc khDk;;
But in parent table test/ibtest11b, in index PRIMARY,
the closest match we can find is record:
RECORD: info bits 0 0: len 4; hex 8000015b; asc ...[;; 1: len 4; hex
80000005; asc ....;; 2: len 3; hex 6b6864; asc khd;; 3: len 6; hex
0000111ef3eb; asc ......;; 4: len 7; hex 800001001e0084; asc .......;; 5:
len 3; hex 6b6864; asc khd;;
------------------------
LATEST DETECTED DEADLOCK
------------------------
030709 12:59:58
*** (1) TRANSACTION:
TRANSACTION 0 290252780, ACTIVE 1 sec, process no 3185, OS thread id 30733
inserting
LOCK WAIT 3 lock struct(s), heap size 320, undo log entries 146
MySQL thread id 21, query id 4553379 localhost heikki update
INSERT INTO alex1 VALUES(86, 86, 794,'aA35818','bb','c79166','d4766t',
'e187358f','g84586','h794',date_format('2001-04-03 12:54:22','%Y-%m-%d
%H:%i'),7
*** (1) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 0 page no 48310 n bits 568 table test/alex1 index
symbole trx id 0 290252780 lock mode S waiting
Record lock, heap no 324 RECORD: info bits 0 0: len 7; hex 61613335383138;
asc aa35818;; 1:
*** (2) TRANSACTION:
TRANSACTION 0 290251546, ACTIVE 2 sec, process no 3190, OS thread id 32782
inserting
130 lock struct(s), heap size 11584, undo log entries 437
MySQL thread id 23, query id 4554396 localhost heikki update
REPLACE INTO alex1 VALUES(NULL, 32, NULL,'aa3572','','c3572','d6012t','',
NULL,'h396', NULL, NULL, 7.31,7.31,7.31,200)
*** (2) HOLDS THE LOCK(S):
RECORD LOCKS space id 0 page no 48310 n bits 568 table test/alex1 index
symbole trx id 0 290251546 lock_mode X locks rec but not gap
Record lock, heap no 324 RECORD: info bits 0 0: len 7; hex 61613335383138;
asc aa35818;; 1:
*** (2) WAITING FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 0 page no 48310 n bits 568 table test/alex1 index
symbole trx id 0 290251546 lock_mode X locks gap before rec insert intention
waiting
Record lock, heap no 82 RECORD: info bits 0 0: len 7; hex 61613335373230;
asc aa35720;; 1:
*** WE ROLL BACK TRANSACTION (1)
------------
TRANSACTIONS
------------
Trx id counter 0 290328385
Purge done for trx's n:o < 0 290315608 undo n:o < 0 17
Total number of lock structs in row lock hash table 70
LIST OF TRANSACTIONS FOR EACH SESSION:
---TRANSACTION 0 0, not started, process no 3491, OS thread id 42002
MySQL thread id 32, query id 4668737 localhost heikki
show innodb status
---TRANSACTION 0 290328384, ACTIVE 0 sec, process no 3205, OS thread id
38929 inserting
1 lock struct(s), heap size 320
MySQL thread id 29, query id 4668736 localhost heikki update
insert into speedc values (1519229,1, 'hgjhjgghggjgjgjgjgjggjgjgjgjgjgggjgjg
jlhhgghggggghhjhghgggggghjhghghghghghhhhghghghjhhjghjghjkghjghjghjghjfhjfh
---TRANSACTION 0 290328383, ACTIVE 0 sec, process no 3180, OS thread id
28684 committing
1 lock struct(s), heap size 320, undo log entries 1
MySQL thread id 19, query id 4668734 localhost heikki update
insert into speedcm values (1603393,1, 'hgjhjgghggjgjgjgjgjggjgjgjgjgjgggjgj
gjlhhgghggggghhjhghgggggghjhghghghghghhhhghghghjhhjghjghjkghjghjghjghjfhjf
---TRANSACTION 0 290328327, ACTIVE 0 sec, process no 3200, OS thread id
36880 starting index read
LOCK WAIT 2 lock struct(s), heap size 320
MySQL thread id 27, query id 4668644 localhost heikki Searching rows for
update
update ibtest11a set B = 'kHdkkkk' where A = 89572
------- TRX HAS BEEN WAITING 0 SEC FOR THIS LOCK TO BE GRANTED:
RECORD LOCKS space id 0 page no 65556 n bits 232 table test/ibtest11a index
PRIMARY trx id 0 290328327 lock_mode X waiting
Record lock, heap no 1 RECORD: info bits 0 0: len 9; hex 73757072656d756d00;
asc supremum.;;
------------------
---TRANSACTION 0 290328284, ACTIVE 0 sec, process no 3195, OS thread id
34831 rollback of SQL statement
ROLLING BACK 14 lock struct(s), heap size 2496, undo log entries 9
MySQL thread id 25, query id 4668733 localhost heikki update
insert into ibtest11a (D, B, C) values (5, 'khDk' ,'khDk')
---TRANSACTION 0 290327208, ACTIVE 1 sec, process no 3190, OS thread id
32782
58 lock struct(s), heap size 5504, undo log entries 159
MySQL thread id 23, query id 4668732 localhost heikki update
REPLACE INTO alex1 VALUES(86, 46, 538,'aa95666','bb','c95666','d9486t',
'e200498f','g86814','h538',date_format('2001-04-03 12:54:22','%Y-%m-%d
%H:%i'),
---TRANSACTION 0 290323325, ACTIVE 3 sec, process no 3185, OS thread id
30733 inserting
4 lock struct(s), heap size 1024, undo log entries 165
MySQL thread id 21, query id 4668735 localhost heikki update
INSERT INTO alex1 VALUES(NULL, 49, NULL,'aa42837','','c56319','d1719t','',
NULL,'h321', NULL, NULL, 7.31,7.31,7.31,200)
--------
FILE I/O
--------
I/O thread 0 state: waiting for i/o request (insert buffer thread)
I/O thread 1 state: waiting for i/o request (log thread)
I/O thread 2 state: waiting for i/o request (read thread)
I/O thread 3 state: waiting for i/o request (write thread)
Pending normal aio reads: 0, aio writes: 0,
ibuf aio reads: 0, log i/o's: 0, sync i/o's: 0
Pending flushes (fsync) log: 0; buffer pool: 0
151671 OS file reads, 94747 OS file writes, 8750 OS fsyncs
25.44 reads/s, 18494 avg bytes/read, 17.55 writes/s, 2.33 fsyncs/s
-------------------------------------
INSERT BUFFER AND ADAPTIVE HASH INDEX
-------------------------------------
Ibuf for space 0: size 1, free list len 19, seg size 21,
85004 inserts, 85004 merged recs, 26669 merges
Hash table size 207619, used cells 14461, node heap has 16 buffer(s)
1877.67 hash searches/s, 5121.10 non-hash searches/s
---
LOG
---
Log sequence number 18 1212842764
Log flushed up to 18 1212665295
Last checkpoint at 18 1135877290
0 pending log writes, 0 pending chkp writes
4341 log i/o's done, 1.22 log i/o's/second
----------------------
BUFFER POOL AND MEMORY
----------------------
Total memory allocated 84966343; in additional pool allocated 1402624
Buffer pool size 3200
Free buffers 110
Database pages 3074
Modified db pages 2674
Pending reads 0
Pending writes: LRU 0, flush list 0, single page 0
Pages read 171380, created 51968, written 194688
28.72 reads/s, 20.72 creates/s, 47.55 writes/s
Buffer pool hit rate 999 / 1000
--------------
ROW OPERATIONS
--------------
0 queries inside InnoDB, 0 queries in queue
Main thread process no. 3004, id 7176, state: purging
Number of rows inserted 3738558, updated 127415, deleted 33707, read 755779
1586.13 inserts/s, 50.89 updates/s, 28.44 deletes/s, 107.88 reads/s
----------------------------
END OF INNODB MONITOR OUTPUT
============================
Some notes on the output:
If the TRANSACTIONS
section reports lock
waits, your applications may have lock contention. The
output can also help to trace the reasons for transaction
deadlocks.
The SEMAPHORES
section reports threads
waiting for a semaphore and statistics on how many times
threads have needed a spin or a wait on a mutex or a rw-lock
semaphore. A large number of threads waiting for semaphores
may be a result of disk I/O, or contention problems inside
InnoDB
. Contention can be due to heavy
parallelism of queries or problems in operating system
thread scheduling. Setting
innodb_thread_concurrency
smaller than
the default value can help in such situations.
The BUFFER POOL AND MEMORY
section gives
you statistics on pages read and written. You can calculate
from these numbers how many data file I/O operations your
queries currently are doing.
The ROW OPERATIONS
section shows what the
main thread is doing.
InnoDB
sends diagnostic output to
stderr
or to files rather than to
stdout
or fixed-size memory buffers, to avoid
potential buffer overflows. As a side effect, the output of
SHOW ENGINE INNODB STATUS
is written to a
status file in the MySQL data directory every fifteen seconds.
The name of the file is
innodb_status.
,
where pid
pid
is the server process ID.
InnoDB
removes the file for a normal
shutdown. If abnormal shutdowns have occurred, instances of
these status files may be present and must be removed manually.
Before removing them, you might want to examine them to see
whether they contain useful information about the cause of
abnormal shutdowns. The
innodb_status.
file is created only if the configuration option
pid
innodb_status_file=1
is set.
Because InnoDB
is a multi-versioned storage
engine, it must keep information about old versions of rows in the
tablespace. This information is stored in a data structure called
a rollback segment (after an analogous data
structure in Oracle).
Internally, InnoDB
adds two fields to each row
stored in the database. A 6-byte field indicates the transaction
identifier for the last transaction that inserted or updated the
row. Also, a deletion is treated internally 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, 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 needed only in transaction
rollback and can be discarded as soon as the transaction commits.
Update undo logs are used also in consistent reads, but 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, including
those transactions that issue only consistent reads. 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 the InnoDB
multi-versioning 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 can it 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 that did the
deletion.
In a scenario where the user inserts and deletes rows in smallish
batches at about the same rate in the table, it is possible that
the purge thread starts to lag behind, and the table grows bigger
and bigger, making everything disk-bound and very slow. Even if
the table carries just 10MB of useful data, it may grow to occupy
10GB with all the “dead” rows. In such a case, it
would be good to throttle new row operations, and allocate more
resources to the purge thread. The
innodb_max_purge_lag
system variable exists for
exactly this purpose. See Section 13.2.4, “InnoDB
Startup Options and System Variables”, for
more information.
MySQL stores its data dictionary information for tables in
.frm
files in database directories. This is
true for all MySQL storage engines. But every
InnoDB
table also has its own entry in the
InnoDB
internal data dictionary inside the
tablespace. When MySQL drops a table or a database, it has to
delete both an .frm
file or files, and the
corresponding entries inside the InnoDB
data
dictionary. This is the reason why you cannot move
InnoDB
tables between databases simply by
moving the .frm
files.
Every InnoDB
table has a special index called
the clustered index where the data for the
rows is stored. If you define a PRIMARY KEY
on
your table, the index of the primary key is the clustered index.
If you do not define a PRIMARY KEY
for your
table, MySQL picks the first UNIQUE
index that
has only NOT NULL
columns as the primary key
and InnoDB
uses it as the clustered index. If
there is no such index in the table, InnoDB
internally generates a clustered index where the rows are ordered
by the row ID that InnoDB
assigns to the rows
in such a table. The row ID is a 6-byte field that increases
monotonically as new rows are inserted. Thus, the rows ordered by
the row ID are physically in insertion order.
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 when compared to the traditional solution. (In many database systems, data storage uses a different page from the index record.)
In InnoDB
, the records in non-clustered indexes
(also called secondary indexes) 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 use more space.
InnoDB
compares CHAR
and
VARCHAR
strings of different lengths such that
the remaining length in the shorter string is treated as if padded
with spaces.
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, 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 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 to 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 to 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 13.2.8.1, “Forcing InnoDB
Recovery”).
The 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 13.2.12, “Implementation of 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.
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 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 record structure for InnoDB tables is dependent on
the MySQL version and the optional ROW_FORMAT
option used when the table was created. For InnoDB tables in
MySQL earlier than 5.0.3, only the REDUNDANT
row format was available. For MySQL 5.0.3 and later, the default
is to use the COMPACT
row format, but you can
use the REDUNDANT
format to retain
compatibility with older versions of InnoDB tables.
Records in InnoDB ROW_FORMAT=REDUNDANT
tables
have the following characteristics:
Each index record contains a six-byte header. The header is used to link together consecutive records, and also in row-level locking.
Records in the clustered index contain fields for all user-defined columns. In addition, there is a six-byte field for the transaction ID and a seven-byte field for the roll pointer.
If no primary key was defined for a table, each clustered index record also contains a six-byte row ID field.
Each secondary index record contains also all the fields defined for the clustered index key.
A record contains also a pointer to each field of the record. If the total length of the fields in a record is less than 128 bytes, the pointer is one byte; otherwise, two bytes. The array of these pointers is called the record directory. The area where these pointers point is called the data part of the record.
Internally, InnoDB stores fixed-length character columns
such as CHAR(10)
in a fixed-length
format. InnoDB truncates trailing spaces from
VARCHAR
columns.
An SQL NULL
value reserves 1 or 2 bytes
in the record directory. Besides that, an SQL
NULL
value reserves zero bytes in the
data part of the record if stored in a variable length
column. In a fixed-length column, it reserves the fixed
length of the column in the data part of the record. The
motivation behind reserving the fixed space for
NULL
values is that it enables an update
of the column from NULL
to a
non-NULL
value to be done in place
without causing fragmentation of the index page.
Records in InnoDB ROW_FORMAT=COMPACT
tables
have the following characteristics:
Each index record contains a five-byte header that may be preceded by a variable-length header. The header is used to link together consecutive records, and also in row-level locking.
The record header contains a bit vector for indicating
NULL
columns. The bit vector occupies
(n_nullable
+7)/8 bytes. Columns that are
NULL
will not occupy other space than the
bit in this vector.
For each non-NULL
variable-length field,
the record header contains the length of the column in one
or two bytes. Two bytes will only be needed if part of the
column is stored externally or the maximum length exceeds
255 bytes and the actual length exceeds 127 bytes.
The record header is followed by the data contents of the
columns. Columns that are NULL
are
omitted.
Records in the clustered index contain fields for all user-defined columns. In addition, there is a six-byte field for the transaction ID and a seven-byte field for the roll pointer.
If no primary key was defined for a table, each clustered index record also contains a six-byte row ID field.
Each secondary index record contains also all the fields defined for the clustered index key.
Internally, InnoDB stores fixed-length, fixed-width
character columns such as CHAR(10)
in a
fixed-length format. InnoDB truncates trailing spaces from
VARCHAR
columns.
Internally, InnoDB attempts to store UTF-8
CHAR(
columns in
n
)n
bytes by trimming trailing spaces. In
ROW_FORMAT=REDUNDANT
, such columns occupy
3*n
bytes. The motivation behind
reserving the minimum space n
is that it
in many cases enables an update of the column to be done in
place without causing fragmentation of the index page.
The presence of 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 it is likely to be faster. If it is a rare case that is limited by CPU speed, it might be slower.
InnoDB
uses simulated asynchronous disk I/O:
InnoDB
creates a number of threads to take
care of I/O operations, such as read-ahead.
There are two read-ahead heuristics in
InnoDB
:
In sequential read-ahead, if InnoDB
notices that the access pattern to a segment in the
tablespace is sequential, it posts in advance a batch of
reads of database pages to the I/O system.
In random read-ahead, if InnoDB
notices
that some area in a tablespace seems to be in the process of
being fully read into the buffer pool, it posts the
remaining reads to the I/O system.
InnoDB
uses a novel file flush technique
called doublewrite. It adds safety to
recovery following an operating system crash or a power outage,
and improves performance on most varieties of Unix by reducing
the need for fsync()
operations.
Doublewrite means that before writing pages to a data file,
InnoDB
first writes them to a contiguous
tablespace area called the doublewrite buffer. Only after the
write and the flush to the doublewrite buffer has completed does
InnoDB
write the pages to their proper
positions in the data file. If the operating system crashes in
the middle of a page write, InnoDB
can later
find a good copy of the page from the doublewrite buffer during
recovery.
The data files that you define in the configuration file form
the tablespace of InnoDB
. The files are
simply concatenated to form the tablespace. There is no striping
in use. Currently, you cannot define where within the tablespace
your tables are allocated. However, in a newly created
tablespace, InnoDB
allocates space starting
from the first data file.
The tablespace consists of database pages with a default size of
16KB. The pages are grouped into extents of 64 consecutive
pages. The “files” inside a tablespace are called
segments in InnoDB
.
The term “rollback segment” is somewhat confusing
because it actually contains many tablespace segments.
Two segments are allocated for each index in
InnoDB
. 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 ask for available free space in the tablespace by
issuing a SHOW TABLE STATUS
statement,
InnoDB
reports the extents that are
definitely free in the tablespace. InnoDB
always reserves some extents for cleanup and other internal
purposes; these reserved extents are not included in the free
space.
When you delete data from a table, InnoDB
contracts the corresponding B-tree indexes. Whether the freed
space becomes available for other users depends on whether the
pattern of deletes frees individual pages or extents to the
tablespace. Dropping a table or deleting all rows from it is
guaranteed to release the space to other users, but remember
that deleted rows are physically removed only in an (automatic)
purge operation after they are no longer needed for transaction
rollbacks or consistent reads. (See
Section 13.2.12, “Implementation of Multi-Versioning”.)
If there are random insertions into or deletions from the indexes of a table, the indexes may become fragmented. Fragmentation means that the physical ordering of the index pages on the disk is not close to the index ordering of the records on the pages, or that there are many unused pages in the 64-page blocks that were allocated to the index.
A symptom of fragmentation is that a table takes more space than
it “should” take. How much that is exactly, is
difficult to determine. All InnoDB
data and
indexes are stored in B-trees, and their fill factor may vary
from 50% to 100%. Another symptom of fragmentation is that a
table scan such as this takes more time than it
“should” take:
SELECT COUNT(*) FROM t WHERE a_non_indexed_column <> 12345;
(In the preceding query, we are “fooling” the SQL optimizer into scanning the clustered index, rather than a secondary index.) Most disks can read 10 to 50MB/s, which can be used to estimate how fast a table scan should run.
It can speed up index scans if you periodically perform a
“null” ALTER TABLE
operation:
ALTER TABLE tbl_name
ENGINE=INNODB
That causes MySQL to rebuild the table. Another way to perform a defragmentation operation is to use mysqldump to dump the table to a text file, drop the table, and reload it from the dump file.
If the insertions to an index are always ascending and records
are deleted only from the end, the InnoDB
filespace management algorithm guarantees that fragmentation in
the index does not occur.
Error handling in InnoDB
is not always the same
as specified in the SQL standard. According to the standard, any
error during an SQL statement should cause the rollback of that
statement. InnoDB
sometimes rolls back only
part of the statement, or the whole transaction. The following
items describe how InnoDB
performs error
handling:
If you run out of file space in the tablespace, a MySQL
Table is full
error occurs and
InnoDB
rolls back the SQL statement.
A transaction deadlock causes InnoDB
to
roll back the entire transaction. In the case of a lock wait
timeout, InnoDB
also rolls back the entire
transaction before MySQL 5.0.13; as of 5.0.13,
InnoDB
rolls back only the most recent SQL
statement.
When a transaction rollback occurs due to a deadlock or lock
wait timeout, it cancels the effect of the statements within
the transaction. But if the start-transaction statement was
START TRANSACTION
or
BEGIN
statement, rollback does not cancel
that statement. Further SQL statements become part of the
transaction until the occurrence of COMMIT
,
ROLLBACK
, or some SQL statement that causes
an implicit commit.
A duplicate-key error rolls back the SQL statement, if you
have not specified the IGNORE
option in
your statement.
A row too long error
rolls back the SQL
statement.
Other errors are mostly detected by the MySQL layer of code
(above the InnoDB
storage engine level),
and they roll back the corresponding SQL statement. Locks are
not released in a rollback of a single SQL statement.
During implicit rollbacks, as well as during the execution of an
explicit ROLLBACK
SQL statement, SHOW
PROCESSLIST
displays Rolling back
in
the State
column for the relevant connection.
The following is a non-exhaustive list of common
InnoDB
-specific errors that you may
encounter, with information about why each occurs and how to
resolve the problem.
1005 (ER_CANT_CREATE_TABLE)
Cannot create table. If the error message refers to
errno
150, table creation failed because
a foreign key constraint was not correctly formed. If the
error message refers to errno
-1, table
creation probably failed because the table included a column
name that matched the name of an internal InnoDB table.
1016 (ER_CANT_OPEN_FILE)
Cannot find the InnoDB
table from the
InnoDB
data files, although the
.frm
file for the table exists. See
Section 13.2.17.1, “Troubleshooting InnoDB
Data Dictionary Operations”.
1114 (ER_RECORD_FILE_FULL)
InnoDB
has run out of free space in the
tablespace. You should reconfigure the tablespace to add a
new data file.
1205 (ER_LOCK_WAIT_TIMEOUT)
Lock wait timeout expired. Transaction was rolled back.
1213 (ER_LOCK_DEADLOCK)
Transaction deadlock. You should rerun the transaction.
1216 (ER_NO_REFERENCED_ROW)
You are trying to add a row but there is no parent row, and a foreign key constraint fails. You should add the parent row first.
1217 (ER_ROW_IS_REFERENCED)
You are trying to delete a parent row that has children, and a foreign key constraint fails. You should delete the children first.
To print the meaning of an operating system error number, use the perror program that comes with the MySQL distribution.
The following table provides a list of some common Linux system error codes. For a more complete list, see Linux source code.
1 (EPERM)
Operation not permitted
2 (ENOENT)
No such file or directory
3 (ESRCH)
No such process
4 (EINTR)
Interrupted system call
5 (EIO)
I/O error
6 (ENXIO)
No such device or address
7 (E2BIG)
Arg list too long
8 (ENOEXEC)
Exec format error
9 (EBADF)
Bad file number
10 (ECHILD)
No child processes
11 (EAGAIN)
Try again
12 (ENOMEM)
Out of memory
13 (EACCES)
Permission denied
14 (EFAULT)
Bad address
15 (ENOTBLK)
Block device required
16 (EBUSY)
Device or resource busy
17 (EEXIST)
File exists
18 (EXDEV)
Cross-device link
19 (ENODEV)
No such device
20 (ENOTDIR)
Not a directory
21 (EISDIR)
Is a directory
22 (EINVAL)
Invalid argument
23 (ENFILE)
File table overflow
24 (EMFILE)
Too many open files
25 (ENOTTY)
Inappropriate ioctl for device
26 (ETXTBSY)
Text file busy
27 (EFBIG)
File too large
28 (ENOSPC)
No space left on device
29 (ESPIPE)
Illegal seek
30 (EROFS)
Read-only file system
31 (EMLINK)
Too many links
The following table provides a list of some common Windows system error codes. For a complete list see the Microsoft Web site.
1 (ERROR_INVALID_FUNCTION)
Incorrect function.
2 (ERROR_FILE_NOT_FOUND)
The system cannot find the file specified.
3 (ERROR_PATH_NOT_FOUND)
The system cannot find the path specified.
4 (ERROR_TOO_MANY_OPEN_FILES)
The system cannot open the file.
5 (ERROR_ACCESS_DENIED)
Access is denied.
6 (ERROR_INVALID_HANDLE)
The handle is invalid.
7 (ERROR_ARENA_TRASHED)
The storage control blocks were destroyed.
8 (ERROR_NOT_ENOUGH_MEMORY)
Not enough storage is available to process this command.
9 (ERROR_INVALID_BLOCK)
The storage control block address is invalid.
10 (ERROR_BAD_ENVIRONMENT)
The environment is incorrect.
11 (ERROR_BAD_FORMAT)
An attempt was made to load a program with an incorrect format.
12 (ERROR_INVALID_ACCESS)
The access code is invalid.
13 (ERROR_INVALID_DATA)
The data is invalid.
14 (ERROR_OUTOFMEMORY)
Not enough storage is available to complete this operation.
15 (ERROR_INVALID_DRIVE)
The system cannot find the drive specified.
16 (ERROR_CURRENT_DIRECTORY)
The directory cannot be removed.
17 (ERROR_NOT_SAME_DEVICE)
The system cannot move the file to a different disk drive.
18 (ERROR_NO_MORE_FILES)
There are no more files.
19 (ERROR_WRITE_PROTECT)
The media is write protected.
20 (ERROR_BAD_UNIT)
The system cannot find the device specified.
21 (ERROR_NOT_READY)
The device is not ready.
22 (ERROR_BAD_COMMAND)
The device does not recognize the command.
23 (ERROR_CRC)
Data error (cyclic redundancy check).
24 (ERROR_BAD_LENGTH)
The program issued a command but the command length is incorrect.
25 (ERROR_SEEK)
The drive cannot locate a specific area or track on the disk.
26 (ERROR_NOT_DOS_DISK)
The specified disk or diskette cannot be accessed.
27 (ERROR_SECTOR_NOT_FOUND)
The drive cannot find the sector requested.
28 (ERROR_OUT_OF_PAPER)
The printer is out of paper.
29 (ERROR_WRITE_FAULT)
The system cannot write to the specified device.
30 (ERROR_READ_FAULT)
The system cannot read from the specified device.
31 (ERROR_GEN_FAILURE)
A device attached to the system is not functioning.
32 (ERROR_SHARING_VIOLATION)
The process cannot access the file because it is being used by another process.
33 (ERROR_LOCK_VIOLATION)
The process cannot access the file because another process has locked a portion of the file.
34 (ERROR_WRONG_DISK)
The wrong diskette is in the drive. Insert %2 (Volume Serial Number: %3) into drive %1.
36 (ERROR_SHARING_BUFFER_EXCEEDED)
Too many files opened for sharing.
38 (ERROR_HANDLE_EOF)
Reached the end of the file.
39 (ERROR_HANDLE_DISK_FULL)
The disk is full.
87 (ERROR_INVALID_PARAMETER)
The parameter is incorrect. (If this error occurs on Windows
and you have enabled
innodb_file_per_table
in a server option
file, add the line
innodb_flush_method=unbuffered
to the
file as well.)
112 (ERROR_DISK_FULL)
The disk is full.
123 (ERROR_INVALID_NAME)
The filename, directory name, or volume label syntax is incorrect.
1450 (ERROR_NO_SYSTEM_RESOURCES)
Insufficient system resources exist to complete the requested service.
Do not convert MySQL system tables in
the mysql
database from
MyISAM
to InnoDB
tables! This is an unsupported operation. If you do this,
MySQL does not restart until you restore the old system
tables from a backup or re-generate them with the
mysql_install_db script.
A table cannot contain more than 1000 columns.
The internal maximum key length is 3500 bytes, but MySQL itself restricts this to 3072 bytes. (1024 bytes for non-64-bit builds before MySQL 5.0.17, and for all builds before 5.0.15.)
The maximum row length, except for
VARBINARY
, VARCHAR
,
BLOB
and TEXT
columns,
is slightly less than half of a database page. That is, the
maximum row length is about 8000 bytes.
LONGBLOB
and LONGTEXT
columns must be less than 4GB, and the total row length,
including also BLOB
and
TEXT
columns, must be less than 4GB.
InnoDB
stores the first 768 bytes of a
VARBINARY
, VARCHAR
,
BLOB
, or TEXT
column in
the row, and the rest into separate pages.
Although InnoDB
supports row sizes larger
than 65535 internally, you cannot define a row containing
VARBINARY
or VARCHAR
columns with a combined size larger than 65535:
mysql>CREATE TABLE t (a VARCHAR(8000), b VARCHAR(10000),
->c VARCHAR(10000), d VARCHAR(10000), e VARCHAR(10000),
->f VARCHAR(10000), g VARCHAR(10000)) ENGINE=InnoDB;
ERROR 1118 (42000): Row size too large. The maximum row size for the used table type, not counting BLOBs, is 65535. You have to change some columns to TEXT or BLOBs
On some older operating systems, files must be less than 2GB.
This is not a limitation of InnoDB
itself,
but if you require a large tablespace, you will need to
configure it using several smaller data files rather than one
or a file large data files.
The combined size of the InnoDB
log files
must be less than 4GB.
The minimum tablespace size is 10MB. The maximum tablespace size is four billion database pages (64TB). This is also the maximum size for a table.
InnoDB
tables do not support
FULLTEXT
indexes.
InnoDB
tables do not support spatial data
types before MySQL 5.0.16. As of 5.0.16,
InnoDB
supports spatial types, but not
indexes on them.
ANALYZE TABLE
determines index cardinality
(as displayed in the Cardinality
column of
SHOW INDEX
output) by doing ten random
dives to each of the index trees and updating index
cardinality estimates accordingly. Note that because these are
only estimates, repeated runs of ANALYZE
TABLE
may produce different numbers. This makes
ANALYZE TABLE
fast on
InnoDB
tables but not 100% accurate as it
doesn't take all rows into account.
MySQL uses index cardinality estimates only in join
optimization. If some join is not optimized in the right way,
you can try using ANALYZE TABLE
. In the few
cases that ANALYZE TABLE
doesn't produce
values good enough for your particular tables, you can use
FORCE INDEX
with your queries to force the
use of a particular index, or set the
max_seeks_for_key
system variable to ensure
that MySQL prefers index lookups over table scans. See
Section 5.1.3, “System Variables”, and
Section B.1.6, “Optimizer-Related Issues”.
SHOW TABLE STATUS
does not give accurate
statistics on InnoDB
tables, except for the
physical size reserved by the table. The row count is only a
rough estimate used in SQL optimization.
InnoDB
does not keep an internal count of
rows in a table. (In practice, this would be somewhat
complicated due to multi-versioning.) To process a
SELECT COUNT(*) FROM t
statement,
InnoDB
must scan an index of the table,
which takes some time if the index is not entirely in the
buffer pool. To get a fast count, you have to use a counter
table you create yourself and let your application update it
according to the inserts and deletes it does. If your table
does not change often, using the MySQL query cache is a good
solution. SHOW TABLE STATUS
also can be
used if an approximate row count is sufficient. See
Section 13.2.11, “InnoDB
Performance Tuning Tips”.
On Windows, InnoDB
always stores database
and table names internally in lowercase. To move databases in
binary format from Unix to Windows or from Windows to Unix,
you should always use explicitly lowercase names when creating
databases and tables.
For an AUTO_INCREMENT
column, you must
always define an index for the table, and that index must
contain just the AUTO_INCREMENT
column. In
MyISAM
tables, the
AUTO_INCREMENT
column may be part of a
multi-column index.
In MySQL 5.0 before MySQL 5.0.3,
InnoDB
does not support the
AUTO_INCREMENT
table option for setting the
initial sequence value in a CREATE TABLE
or
ALTER TABLE
statement. To set the value
with InnoDB
, insert a dummy row with a
value one less and delete that dummy row, or insert the first
row with an explicit value specified.
While initializing a previously specified
AUTO_INCREMENT
column on a table,
InnoDB
sets an exclusive lock on the end of
the index associated with the
AUTO_INCREMENT
column. In accessing the
auto-increment counter, InnoDB
uses a
specific table lock mode AUTO-INC
where the
lock lasts only to the end of the current SQL statement, not
to the end of the entire transaction. Note that other clients
cannot insert into the table while the
AUTO-INC
table lock is held; see
Section 13.2.10.2, “InnoDB
and AUTOCOMMIT
”.
When you restart the MySQL server, InnoDB
may reuse an old value that was generated for an
AUTO_INCREMENT
column but never stored
(that is, a value that was generated during an old transaction
that was rolled back).
When an AUTO_INCREMENT
column runs out of
values, InnoDB
wraps a
BIGINT
to
-9223372036854775808
and BIGINT
UNSIGNED
to 1
. However,
BIGINT
values have 64 bits, so do note that
if you were to insert one million rows per second, it would
still take nearly three hundred thousand years before
BIGINT
reached its upper bound. With all
other integer type columns, a duplicate-key error results.
This is similar to how MyISAM
works,
because it is mostly general MySQL behavior and not about any
storage engine in particular.
DELETE FROM
does not
regenerate the table but instead deletes all rows, one by one.
tbl_name
Under some conditions, TRUNCATE
for an
tbl_name
InnoDB
table is mapped to DELETE
FROM
and doesn't
reset the tbl_name
AUTO_INCREMENT
counter. See
Section 12.2.9, “TRUNCATE
Syntax”.
In MySQL 5.0, the MySQL LOCK
TABLES
operation acquires two locks on each table if
innodb_table_locks=1
(the default). In
addition to a table lock on the MySQL layer, it also acquires
an InnoDB
table lock. Older versions of
MySQL did not acquire InnoDB
table locks;
the old behavior can be selected by setting
innodb_table_locks=0
. If no
InnoDB
table lock is acquired,
LOCK TABLES
completes even if some records
of the tables are being locked by other transactions.
All InnoDB
locks held by a transaction are
released when the transaction is committed or aborted. Thus,
it does not make much sense to invoke LOCK
TABLES
on InnoDB
tables in
AUTOCOMMIT=1
mode, because the acquired
InnoDB
table locks would be released
immediately.
Sometimes it would be useful to lock further tables in the
course of a transaction. Unfortunately, LOCK
TABLES
in MySQL performs an implicit
COMMIT
and UNLOCK
TABLES
. An InnoDB
variant of
LOCK TABLES
has been planned that can be
executed in the middle of a transaction.
The LOAD TABLE FROM MASTER
statement for
setting up replication slave servers does not work for
InnoDB
tables. A workaround is to alter the
table to MyISAM
on the master, then do the
load, and after that alter the master table back to
InnoDB
. Do not do this if the tables use
InnoDB
-specific features such as foreign
keys.
The default database page size in InnoDB
is
16KB. By recompiling the code, you can set it to values
ranging from 8KB to 64KB. You must update the values of
UNIV_PAGE_SIZE
and
UNIV_PAGE_SIZE_SHIFT
in the
univ.i
source file.
Currently, triggers are not activated by cascaded foreign key actions.
You cannot create a table with a column name that matches the
name of an internal InnoDB column (including
DB_ROW_ID
, DB_TRX_ID
,
DB_ROLL_PTR
and
DB_MIX_ID
). In versions of MySQL before
5.0.21 this would cause a crash, since 5.0.21 the server will
report error 1005 and refers to errno
-1 in
the error message.
As of MySQL 5.0.19, InnoDB
does not ignore
trailing spaces when comparing BINARY
or
VARBINARY
column values. See
Section 10.4.2, “The BINARY
and VARBINARY
Types” and
Section E.1.11, “Changes in MySQL 5.0.19 (04 March 2006)”.
InnoDB
has a limit of 1023 concurrent
transactions that have created undo records by modifying data.
Workarounds include keeping transactions as small and fast as
possible, delaying changes until near the end of the
transaction, and using stored routines to reduce client-server
latency delays. Applications should commit transactions before
doing time-consuming client-side operations.
The following general guidelines apply to troubleshooting
InnoDB
problems:
When an operation fails or you suspect a bug, you should look
at the MySQL server error log, which is the file in the data
directory that has a suffix of .err
.
When troubleshooting, it is usually best to run the MySQL
server from the command prompt, rather than through the
mysqld_safe wrapper or as a Windows
service. You can then see what mysqld
prints to the console, and so have a better grasp of what is
going on. On Windows, you must start the server with the
--console
option to direct the output to
the console window.
Use the InnoDB
Monitors to obtain
information about a problem (see
Section 13.2.11.1, “SHOW ENGINE INNODB STATUS
and the
InnoDB
Monitors”). If the problem is
performance-related, or your server appears to be hung, you
should use innodb_monitor
to print
information about the internal state of
InnoDB
. If the problem is with locks, use
innodb_lock_monitor
. If the problem is in
creation of tables or other data dictionary operations, use
innodb_table_monitor
to print the contents
of the InnoDB
internal data dictionary.
If you suspect that a table is corrupt, run CHECK
TABLE
on that table.
MySQL Enterprise The MySQL Enterprise Monitor provides a number of advisors specifically designed for monitoring InnoDB tables. In some cases, these advisors can anticipate potential problems. For more information see http://www.mysql.com/products/enterprise/advisors.html.
A specific issue with tables is that the MySQL server keeps data
dictionary information in .frm
files it
stores in the database directories, whereas
InnoDB
also stores the information into its
own data dictionary inside the tablespace files. If you move
.frm
files around, or if the server crashes
in the middle of a data dictionary operation, the locations of
the .frm
files may end up out of synchrony
with the locations recorded in the InnoDB
internal data dictionary.
A symptom of an out-of-sync data dictionary is that a
CREATE TABLE
statement fails. If this occurs,
you should look in the server's error log. If the log says that
the table already exists inside the InnoDB
internal data dictionary, you have an orphaned table inside the
InnoDB
tablespace files that has no
corresponding .frm
file. The error message
looks like this:
InnoDB: Error: table test/parent already exists in InnoDB internal InnoDB: data dictionary. Have you deleted the .frm file InnoDB: and not used DROP TABLE? Have you used DROP DATABASE InnoDB: for InnoDB tables in MySQL version <= 3.23.43? InnoDB: See the Restrictions section of the InnoDB manual. InnoDB: You can drop the orphaned table inside InnoDB by InnoDB: creating an InnoDB table with the same name in another InnoDB: database and moving the .frm file to the current database. InnoDB: Then MySQL thinks the table exists, and DROP TABLE will InnoDB: succeed.
You can drop the orphaned table by following the instructions
given in the error message. If you are still unable to use
DROP TABLE
successfully, the problem may be
due to name completion in the mysql client.
To work around this problem, start the mysql
client with the --skip-auto-rehash
option and
try DROP TABLE
again. (With name completion
on, mysql tries to construct a list of table
names, which fails when a problem such as just described
exists.)
Another symptom of an out-of-sync data dictionary is that MySQL
prints an error that it cannot open a
.InnoDB
file:
ERROR 1016: Can't open file: 'child2.InnoDB'. (errno: 1)
In the error log you can find a message like this:
InnoDB: Cannot find table test/child2 from the internal data dictionary InnoDB: of InnoDB though the .frm file for the table exists. Maybe you InnoDB: have deleted and recreated InnoDB data files but have forgotten InnoDB: to delete the corresponding .frm files of InnoDB tables?
This means that there is an orphaned .frm
file without a corresponding table inside
InnoDB
. You can drop the orphaned
.frm
file by deleting it manually.
If MySQL crashes in the middle of an ALTER
TABLE
operation, you may end up with an orphaned
temporary table inside the InnoDB
tablespace.
Using innodb_table_monitor
you can see listed
a table whose name is #sql-...
. You can
perform SQL statements on tables whose name contains the
character “#
” if you enclose the
name within backticks. Thus, you can drop such an orphaned table
like any other orphaned table using the method described
earlier. Note that to copy or rename a file in the Unix shell,
you need to put the file name in double quotes if the file name
contains “#
”.
The MERGE
storage engine, also known as the
MRG_MyISAM
engine, is a collection of identical
MyISAM
tables that can be used as one.
“Identical” means that all tables have identical column
and index information. You cannot merge MyISAM
tables in which the columns are listed in a different order, do not
have exactly the same columns, or have the indexes in different
order. However, any or all of the MyISAM
tables
can be compressed with myisampack. See
Section 4.6.5, “myisampack — Generate Compressed, Read-Only MyISAM Tables”. Differences in table options such as
AVG_ROW_LENGTH
, MAX_ROWS
, or
PACK_KEYS
do not matter.
When you create a MERGE
table, MySQL creates two
files on disk. The files have names that begin with the table name
and have an extension to indicate the file type. An
.frm
file stores the table format, and an
.MRG
file contains the names of the tables that
should be used as one. The tables do not have to be in the same
database as the MERGE
table itself.
Starting with MySQL 5.0.36 the underlying table definitions and
indexes must conform more closely to the definition of the
MERGE
table. Conformance will be checked when the
merged tables are opened, not when the MERGE
table is created. This means that changes to the definitions of
tables within a MERGE
may cause a failure when
the MERGE
table is accessed.
You can use SELECT
, DELETE
,
UPDATE
, and INSERT
on
MERGE
tables. You must have
SELECT
, UPDATE
, and
DELETE
privileges on the
MyISAM
tables that you map to a
MERGE
table.
The use of MERGE
tables entails the following
security issue: If a user has access to MyISAM
table t
, that user can create a
MERGE
table m
that
accesses t
. However, if the user's
privileges on t
are subsequently
revoked, the user can continue to access
t
by doing so through
m
. If this behavior is undesirable, you
can start the server with the new --skip-merge
option to disable the MERGE
storage engine.
This option is available as of MySQL 5.0.24.
If you DROP
the MERGE
table,
you are dropping only the MERGE
specification.
The underlying tables are not affected.
To create a MERGE
table, you must specify a
UNION=(
clause that indicates which list-of-tables
)MyISAM
tables you
want to use as one. You can optionally specify an
INSERT_METHOD
option if you want inserts for the
MERGE
table to take place in the first or last
table of the UNION
list. Use a value of
FIRST
or LAST
to cause inserts
to be made in the first or last table, respectively. If you do not
specify an INSERT_METHOD
option or if you specify
it with a value of NO
, attempts to insert rows
into the MERGE
table result in an error.
The following example shows how to create a MERGE
table:
mysql>CREATE TABLE t1 (
->a INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
->message CHAR(20)) ENGINE=MyISAM;
mysql>CREATE TABLE t2 (
->a INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
->message CHAR(20)) ENGINE=MyISAM;
mysql>INSERT INTO t1 (message) VALUES ('Testing'),('table'),('t1');
mysql>INSERT INTO t2 (message) VALUES ('Testing'),('table'),('t2');
mysql>CREATE TABLE total (
->a INT NOT NULL AUTO_INCREMENT,
->message CHAR(20), INDEX(a))
->ENGINE=MERGE UNION=(t1,t2) INSERT_METHOD=LAST;
The older term TYPE
is supported as a synonym for
ENGINE
for backward compatibility, but
ENGINE
is the preferred term and
TYPE
is deprecated.
Note that the a
column is indexed as a
PRIMARY KEY
in the underlying
MyISAM
tables, but not in the
MERGE
table. There it is indexed but not as a
PRIMARY KEY
because a MERGE
table cannot enforce uniqueness over the set of underlying tables.
In MySQL 5.0.36 and higher, when a table that is part of a
MERGE
table is opened, the following checks are
applied before opening each table. If any table fails the
conformance checks, then the operation that triggered the opening of
the table will fail. The conformance checks applied to each table
are:
Table must have exactly the same amount of columns that
MERGE
table has.
Column order in the MERGE
table must match
the column order in the underlying tables.
Additionally, the specification for each column in the parent
MERGE
table and the underlying table are
compared. For each column, MySQL checks:
Column type in the underlying table equals the column type
of MERGE
table.
Column length in the underlying table equals the column
length of MERGE
table.
Column of underlying table and column of
MERGE
table can be
NULL
.
Underlying table must have at least the same amount of keys that
merge table has. The underlying table may have morekeys than the
MERGE
table, but cannot have less.
A known issue exists that keys on the some columns must be
identical in order in both the MERGE
table
and the underlying MyISAM
table. See Bug#33653.
For each key:
Check if the key type of underlying table equals the key type of merge table.
Check if number of key parts (i.e. multiple columns within a compound key) in the underlying table key definition equals the number of key parts in merge table key definition.
For each key part:
Check if key part lengths are equal.
Check if key part types are equal.
Check if key part languages are equal.
Check if key part can be NULL
.
After creating the MERGE
table, you can issue
queries that operate on the group of tables as a whole:
mysql> SELECT * FROM total;
+---+---------+
| a | message |
+---+---------+
| 1 | Testing |
| 2 | table |
| 3 | t1 |
| 1 | Testing |
| 2 | table |
| 3 | t2 |
+---+---------+
To remap a MERGE
table to a different collection
of MyISAM
tables, you can use one of the
following methods:
DROP
the MERGE
table and
re-create it.
Use ALTER TABLE
to change the list of underlying tables.
tbl_name
UNION=(...)
MERGE
tables can help you solve the following
problems:
Easily manage a set of log tables. For example, you can put data
from different months into separate tables, compress some of
them with myisampack, and then create a
MERGE
table to use them as one.
Obtain more speed. You can split a big read-only table based on
some criteria, and then put individual tables on different
disks. A MERGE
table on this could be much
faster than using the big table.
Perform more efficient searches. If you know exactly what you
are looking for, you can search in just one of the split tables
for some queries and use a MERGE
table for
others. You can even have many different
MERGE
tables that use overlapping sets of
tables.
Perform more efficient repairs. It is easier to repair
individual tables that are mapped to a MERGE
table than to repair a single large table.
Instantly map many tables as one. A MERGE
table need not maintain an index of its own because it uses the
indexes of the individual tables. As a result,
MERGE
table collections are
very fast to create or remap. (Note that
you must still specify the index definitions when you create a
MERGE
table, even though no indexes are
created.)
If you have a set of tables from which you create a large table
on demand, you should instead create a MERGE
table on them on demand. This is much faster and saves a lot of
disk space.
Exceed the file size limit for the operating system. Each
MyISAM
table is bound by this limit, but a
collection of MyISAM
tables is not.
You can create an alias or synonym for a
MyISAM
table by defining a
MERGE
table that maps to that single table.
There should be no really notable performance impact from doing
this (only a couple of indirect calls and
memcpy()
calls for each read).
The disadvantages of MERGE
tables are:
You can use only identical MyISAM
tables for
a MERGE
table.
You cannot use a number of MyISAM
features in
MERGE
tables. For example, you cannot create
FULLTEXT
indexes on MERGE
tables. (You can, of course, create FULLTEXT
indexes on the underlying MyISAM
tables, but
you cannot search the MERGE
table with a
full-text search.)
If the MERGE
table is non-temporary, all
underlying MyISAM
tables must be
non-temporary, too. If the MERGE
table is
temporary, the MyISAM
tables can be any mix
of temporary and non-temporary.
MERGE
tables use more file descriptors. If 10
clients are using a MERGE
table that maps to
10 tables, the server uses (10 × 10) + 10 file
descriptors. (10 data file descriptors for each of the 10
clients, and 10 index file descriptors shared among the
clients.)
Key reads are slower. When you read a key, the
MERGE
storage engine needs to issue a read on
all underlying tables to check which one most closely matches
the given key. To read the next key, the
MERGE
storage engine needs to search the read
buffers to find the next key. Only when one key buffer is used
up does the storage engine need to read the next key block. This
makes MERGE
keys much slower on
eq_ref
searches, but not much slower on
ref
searches. See Section 12.3.2, “EXPLAIN
Syntax”,
for more information about eq_ref
and
ref
.
Additional resources
A forum dedicated to the MERGE
storage engine
is available at http://forums.mysql.com/list.php?93.
The following are known problems with MERGE
tables:
If you use ALTER TABLE
to change a
MERGE
table to another storage engine, the
mapping to the underlying tables is lost. Instead, the rows
from the underlying MyISAM
tables are
copied into the altered table, which then uses the specified
storage engine.
REPLACE
does not work as expected because
the MERGE
engine cannot enforce uniqueness
over the set of underlying tables. The two key facts are:
REPLACE
can detect unique key
violations only in the underlying table to which it is
going to write (which is determined by
INSERT_METHOD
). This differs from
violations in the MERGE
table itself.
If REPLACE
detects such a violation, it
will only change the corresponding row in the first
underlying table in which the row is present, whereas a
row with the same unique key value may present in all
underlying tables.
Similar considerations apply for INSERT ... ON
DUPLICATE KEY UPDATE
.
You cannot use REPAIR TABLE
,
OPTIMIZE TABLE
, DROP
TABLE
, ALTER TABLE
,
DELETE
without a WHERE
clause, TRUNCATE TABLE
, or ANALYZE
TABLE
on any of the tables that are mapped into an
open MERGE
table. If you do so, the
MERGE
table may still refer to the original
table, which yields unexpected results. The easiest way to
work around this deficiency is to ensure that no
MERGE
tables remain open by issuing a
FLUSH TABLES
statement prior to performing
any of those operations.
The unexpected results include the possibility that the
operation on the MERGE
table will report
table corruption. However, if this occurs after operations on
the underlying MyISAM
tables such as those
listed in the previous paragraph (REPAIR
TABLE
, OPTIMIZE TABLE
, and so
forth), the corruption message is spurious. To deal with this,
issue a FLUSH TABLES
statement after
modifying the MyISAM
tables.
DROP TABLE
on a table that is in use by a
MERGE
table does not work on Windows
because the MERGE
storage engine's table
mapping is hidden from the upper layer of MySQL. Windows does
not allow open files to be deleted, so you first must flush
all MERGE
tables (with FLUSH
TABLES
) or drop the MERGE
table
before dropping the table.
A MERGE
table cannot maintain uniqueness
constraints over the entire table. When you perform an
INSERT
, the data goes into the first or
last MyISAM
table (depending on the value
of the INSERT_METHOD
option). MySQL ensures
that unique key values remain unique within that
MyISAM
table, but not across all the tables
in the collection.
In MySQL 5.0.36 and later, the definition of the
MyISAM
tables and the
MERGE
table are checked when the tables are
accessed (for example, as part of a SELECT
or INSERT
statement). The checks ensure
that the definitions of the tables and the parent
MERGE
table definition match by comparing
column order, types, sizes and associated indexes. If there is
a difference between the tables then an error will be returned
and the statement will fail.
Because these checks take place when the tables are opened, any changes to the definition of a single table, including column changes, column ordering and engine alterations will cause the statement to fail.
In MySQL 5.0.35 and earlier:
When you create or alter MERGE
table,
there is no check to ensure that the underlying tables are
existing MyISAM
tables and have
identical structures. When the MERGE
table is used, MySQL checks that the row length for all
mapped tables is equal, but this is not foolproof. If you
create a MERGE
table from dissimilar
MyISAM
tables, you are very likely to
run into strange problems.
Similarly, if you create a MERGE
table
from non-MyISAM
tables, or if you drop
an underlying table or alter it to be a
non-MyISAM
table, no error for the
MERGE
table occurs until later when you
attempt to use it.
Because the underlying MyISAM
tables
need not exist when the MERGE
table is
created, you can create the tables in any order, as long
as you do not use the MERGE
table until
all of its underlying tables are in place. Also, if you
can ensure that a MERGE
table will not
be used during a given period, you can perform maintenance
operations on the underlying tables, such as backing up or
restoring them, altering them, or dropping and recreating
them. It is not necessary to redefine the
MERGE
table temporarily to exclude the
underlying tables while you are operating on them.
The order of indexes in the MERGE
table and
its underlying tables should be the same. If you use
ALTER TABLE
to add a
UNIQUE
index to a table used in a
MERGE
table, and then use ALTER
TABLE
to add a non-unique index on the
MERGE
table, the index ordering is
different for the tables if there was already a non-unique
index in the underlying table. (This happens because
ALTER TABLE
puts UNIQUE
indexes before non-unique indexes to facilitate rapid
detection of duplicate keys.) Consequently, queries on tables
with such indexes may return unexpected results.
If you encounter an error message similar to ERROR
1017 (HY000): Can't find file:
'
it
generally indicates that some of the base tables are not using
the MyISAM storage engine. Confirm that all tables are MyISAM.
mm
.MRG' (errno: 2)
There is a limit of 232
(~4.295E+09)) rows to a MERGE
table, just
as there is with a MyISAM
, it is therefore
not possible to merge multiple MyISAM
tables that exceed this limitation. However, you build MySQL
with the --with-big-tables
option then the
row limitation is increased to
(232)2
(1.844E+19) rows. See Section 2.4.15.2, “Typical configure Options”.
Beginning with MySQL 5.0.4 all standard binaries are built
with this option.
The MERGE
storage engine does not support
INSERT DELAYED
statements.
Using MERGE
on underlying
MyISAM
tables that have different row
formats is possible.
As of MySQL 5.0.44, if a MERGE
table cannot be
opened or used because of a problem with an underlying table,
CHECK TABLE
displays information about which
table caused the problem.
The MEMORY
storage engine creates tables with
contents that are stored in memory. Formerly, these were known as
HEAP
tables. MEMORY
is the
preferred term, although HEAP
remains supported
for backward compatibility.
Each MEMORY
table is associated with one disk
file. The filename begins with the table name and has an extension
of .frm
to indicate that it stores the table
definition.
To specify explicitly that you want to create a
MEMORY
table, indicate that with an
ENGINE
table option:
CREATE TABLE t (i INT) ENGINE = MEMORY;
The older term TYPE
is supported as a synonym for
ENGINE
for backward compatibility, but
ENGINE
is the preferred term and
TYPE
is deprecated.
As indicated by the name, MEMORY
tables are
stored in memory. They use hash indexes by default, which makes them
very fast, and very useful for creating temporary tables. However,
when the server shuts down, all rows stored in
MEMORY
tables are lost. The tables themselves
continue to exist because their definitions are stored in
.frm
files on disk, but they are empty when the
server restarts.
This example shows how you might create, use, and remove a
MEMORY
table:
mysql>CREATE TABLE test ENGINE=MEMORY
->SELECT ip,SUM(downloads) AS down
->FROM log_table GROUP BY ip;
mysql>SELECT COUNT(ip),AVG(down) FROM test;
mysql>DROP TABLE test;
MEMORY
tables have the following characteristics:
Space for MEMORY
tables is allocated in small
blocks. Tables use 100% dynamic hashing for inserts. No overflow
area or extra key space is needed. No extra space is needed for
free lists. Deleted rows are put in a linked list and are reused
when you insert new data into the table.
MEMORY
tables also have none of the problems
commonly associated with deletes plus inserts in hashed tables.
MEMORY
tables can have up to 32 indexes per
table, 16 columns per index and a maximum key length of 500
bytes.
The MEMORY
storage engine implements both
HASH
and BTREE
indexes.
You can specify one or the other for a given index by adding a
USING
clause as shown here:
CREATE TABLE lookup (id INT, INDEX USING HASH (id)) ENGINE = MEMORY; CREATE TABLE lookup (id INT, INDEX USING BTREE (id)) ENGINE = MEMORY;
General characteristics of B-tree and hash indexes are described in Section 7.4.5, “How MySQL Uses Indexes”.
You can have non-unique keys in a MEMORY
table. (This is an uncommon feature for implementations of hash
indexes.)
If you have a hash index on a MEMORY
table
that has a high degree of key duplication (many index entries
containing the same value), updates to the table that affect key
values and all deletes are significantly slower. The degree of
this slowdown is proportional to the degree of duplication (or,
inversely proportional to the index cardinality). You can use a
BTREE
index to avoid this problem.
Columns that are indexed can contain NULL
values.
MEMORY
tables use a fixed-length row storage
format.
MEMORY
tables cannot contain
BLOB
or TEXT
columns.
MEMORY
includes support for
AUTO_INCREMENT
columns.
You can use INSERT DELAYED
with
MEMORY
tables. See
Section 12.2.4.2, “INSERT DELAYED
Syntax”.
MEMORY
tables are shared among all clients
(just like any other non-TEMPORARY
table).
MEMORY
table contents are stored in memory,
which is a property that MEMORY
tables share
with internal tables that the server creates on the fly while
processing queries. However, the two types of tables differ in
that MEMORY
tables are not subject to storage
conversion, whereas internal tables are:
If an internal table becomes too large, the server
automatically converts it to an on-disk table. The size
limit is determined by the value of the
tmp_table_size
system variable.
MEMORY
tables are never converted to disk
tables. To ensure that you don't accidentally do anything
foolish, you can set the
max_heap_table_size
system variable to
impose a maximum size on MEMORY
tables.
For individual tables, you can also specify a
MAX_ROWS
table option in the
CREATE TABLE
statement.
The server needs sufficient memory to maintain all
MEMORY
tables that are in use at the same
time.
Memory used by a MEMORY
table is not
reclaimed if you delete individual rows from the table. Memory
is only reclaimed when the entire table is deleted. Memory that
was previously used for rows that have been deleted will be
re-used for new rows only within the same table. To free up the
memory used by rows that have been deleted you should use
ALTER TABLE ENGINE=MEMORY
to force a table
rebuild.
To free all the memory used by a MEMORY
table
when you no longer require its contents, you should execute
DELETE
or TRUNCATE TABLE
,
or remove the table altogether using DROP
TABLE
.
If you want to populate a MEMORY
table when
the MySQL server starts, you can use the
--init-file
option. For example, you can put
statements such as INSERT INTO ... SELECT
or
LOAD DATA INFILE
into this file to load the
table from a persistent data source. See
Section 5.1.2, “Command Options”, and
Section 12.2.5, “LOAD DATA INFILE
Syntax”.
If you are using replication, the master server's
MEMORY
tables become empty when it is shut
down and restarted. However, a slave is not aware that these
tables have become empty, so it returns out-of-date content if
you select data from them. When a MEMORY
table is used on the master for the first time since the master
was started, a DELETE
statement is written to
the master's binary log automatically, thus synchronizing the
slave to the master again. Note that even with this strategy,
the slave still has outdated data in the table during the
interval between the master's restart and its first use of the
table. However, if you use the --init-file
option to populate the MEMORY
table on the
master at startup, it ensures that this time interval is zero.
The memory needed for one row in a MEMORY
table is calculated using the following expression:
SUM_OVER_ALL_BTREE_KEYS(max_length_of_key
+ sizeof(char*) × 4) + SUM_OVER_ALL_HASH_KEYS(sizeof(char*) × 2) + ALIGN(length_of_row
+1, sizeof(char*))
ALIGN()
represents a round-up factor to cause
the row length to be an exact multiple of the
char
pointer size.
sizeof(char*)
is 4 on 32-bit machines and 8
on 64-bit machines.
Additional resources
A forum dedicated to the MEMORY
storage
engine is available at http://forums.mysql.com/list.php?92.
Sleepycat Software has provided MySQL with the Berkeley DB
transactional storage engine. This storage engine typically is
called BDB
for short. BDB
tables may have a greater chance of surviving crashes and are also
capable of COMMIT
and ROLLBACK
operations on transactions.
Support for the BDB
storage engine is included in
MySQL source distributions, which come with a BDB
distribution that is patched to make it work with MySQL. You cannot
use a non-patched version of BDB
with MySQL.
BDB support will be removed
Note that, as of MySQL 5.1, BDB
isn't supported
any longer.
For general information about Berkeley DB, please visit the Sleepycat Web site, http://www.sleepycat.com/.
Currently, we know that the BDB
storage engine
works with the following operating systems:
Linux 2.x Intel
Sun Solaris (SPARC and x86)
FreeBSD 4.x/5.x (x86, sparc64)
IBM AIX 4.3.x
SCO OpenServer
SCO UnixWare 7.1.x
Windows
The BDB
storage engine does
not work with the following operating
systems:
Linux 2.x Alpha
Linux 2.x AMD64
Linux 2.x IA-64
Linux 2.x s390
Mac OS X
The preceding lists are not complete. We update them as we receive more information.
If you build MySQL from source with support for
BDB
tables, but the following error occurs when
you start mysqld, it means that the
BDB
storage engine is not supported for your
architecture:
bdb: architecture lacks fast mutexes: applications cannot be threaded Can't init databases
In this case, you must rebuild MySQL without
BDB
support or start the server with the
--skip-bdb
option.
If you have downloaded a binary version of MySQL that includes support for Berkeley DB, simply follow the usual binary distribution installation instructions.
If you build MySQL from source, you can enable
BDB
support by invoking
configure with the
--with-berkeley-db
option in addition to any
other options that you normally use. Download a MySQL
5.0 distribution, change location into its top-level
directory, and run this command:
shell> ./configure --with-berkeley-db [other-options
]
For more information, Section 2.4.14, “Installing MySQL from tar.gz
Packages on Other
Unix-Like Systems”, and
Section 2.4.15, “MySQL Installation Using a Source Distribution”.
The following options to mysqld can be used to
change the behavior of the BDB
storage engine.
For more information, see Section 5.1.2, “Command Options”.
Name | Cmd-line | Option file | System Var | Status Var | Var Scope | Dynamic |
---|---|---|---|---|---|---|
bdb_cache_size | Y | Y | Y | global | no | |
bdb-home | Y | Y | Y | global | no | |
bdb-lock-detect | Y | Y | global | no | ||
- Variable: bdb_lock_detect | Y | global | no | |||
bdb_log_buffer_size | Y | Y | Y | global | no | |
bdb-logdir | Y | Y | Y | global | no | |
bdb_max_lock | Y | Y | Y | global | no | |
bdb-no-recover | Y | Y | ||||
bdb-shared-data | Y | Y | global | no | ||
- Variable: bdb_shared_data | Y | global | no | |||
bdb-tmpdir | Y | Y | Y | global | no | |
have_bdb | Y | global | no | |||
skip-bdb | Y | Y | ||||
- Variable: skip_bdb | ||||||
skip-sync-bdb-logs | Y | Y | Y | global | no | |
sync-bdb-logs | Y | Y | Y | global | no |
The base directory for BDB
tables. This
should be the same directory that you use for
--datadir
.
The BDB
lock detection method. The option
value should be DEFAULT
,
OLDEST
, RANDOM
, or
YOUNGEST
.
The BDB
log file directory.
Do not start Berkeley DB in recover mode.
Don't synchronously flush the BDB
logs.
This option is deprecated; use
--skip-sync-bdb-logs
instead (see the
description for --sync-bdb-logs
).
Start Berkeley DB in multi-process mode. (Do not use
DB_PRIVATE
when initializing Berkeley DB.)
The BDB
temporary file directory.
Disable the BDB
storage engine.
Synchronously flush the BDB
logs. This
option is enabled by default. Use
--skip-sync-bdb-logs
to disable it.
If you use the --skip-bdb
option, MySQL does not
initialize the Berkeley DB library and this saves a lot of memory.
However, if you use this option, you cannot use
BDB
tables. If you try to create a
BDB
table, MySQL uses the default storage
engine instead.
Normally, you should start mysqld without the
--bdb-no-recover
option if you intend to use
BDB
tables. However, this may cause problems
when you try to start mysqld if the
BDB
log files are corrupted. See
Section 2.4.16.2.3, “Starting and Troubleshooting the MySQL Server”.
With the bdb_max_lock
variable, you can specify
the maximum number of locks that can be active on a
BDB
table. The default is 10,000. You should
increase this if errors such as the following occur when you
perform long transactions or when mysqld has to
examine many rows to execute a query:
bdb: Lock table is out of available locks Got error 12 from ...
You may also want to change the
binlog_cache_size
and
max_binlog_cache_size
variables if you are
using large multiple-statement transactions. See
Section 5.2.3, “The Binary Log”.
See also Section 5.1.3, “System Variables”.
Each BDB
table is stored on disk in two files.
The files have names that begin with the table name and have an
extension to indicate the file type. An .frm
file stores the table format, and a .db
file
contains the table data and indexes.
To specify explicitly that you want a BDB
table, indicate that with an ENGINE
table
option:
CREATE TABLE t (i INT) ENGINE = BDB;
The older term TYPE
is supported as a synonym
for ENGINE
for backward compatibility, but
ENGINE
is the preferred term and
TYPE
is deprecated.
BerkeleyDB
is a synonym for
BDB
in the ENGINE
table
option.
The BDB
storage engine provides transactional
tables. The way you use these tables depends on the autocommit
mode:
If you are running with autocommit enabled (which is the
default), changes to BDB
tables are
committed immediately and cannot be rolled back.
If you are running with autocommit disabled, changes do not
become permanent until you execute a COMMIT
statement. Instead of committing, you can execute
ROLLBACK
to forget the changes.
You can start a transaction with the START
TRANSACTION
or BEGIN
statement to
suspend autocommit, or with SET
AUTOCOMMIT=0
to disable autocommit explicitly.
For more information about transactions, see
Section 12.4.1, “START TRANSACTION
, COMMIT
, and
ROLLBACK
Syntax”.
The BDB
storage engine has the following
characteristics:
BDB
tables can have up to 31 indexes per
table, 16 columns per index, and a maximum key size of 1024
bytes.
MySQL requires a primary key in each BDB
table so that each row can be uniquely identified. If you
don't create one explicitly by declaring a PRIMARY
KEY
, MySQL creates and maintains a hidden primary
key for you. The hidden key has a length of five bytes and is
incremented for each insert attempt. This key does not appear
in the output of SHOW CREATE TABLE
or
DESCRIBE
.
The primary key is faster than any other index, because it is stored together with the row data. The other indexes are stored as the key data plus the primary key, so it's important to keep the primary key as short as possible to save disk space and get better speed.
This behavior is similar to that of InnoDB
,
where shorter primary keys save space not only in the primary
index but in secondary indexes as well.
If all columns that you access in a BDB
table are part of the same index or part of the primary key,
MySQL can execute the query without having to access the
actual row. In a MyISAM
table, this can be
done only if the columns are part of the same index.
Sequential scanning is slower for BDB
tables than for MyISAM
tables because the
data in BDB
tables is stored in B-trees and
not in a separate data file.
Key values are not prefix- or suffix-compressed like key
values in MyISAM
tables. In other words,
key information takes a little more space in
BDB
tables compared to
MyISAM
tables.
There are often holes in the BDB
table to
allow you to insert new rows in the middle of the index tree.
This makes BDB
tables somewhat larger than
MyISAM
tables.
SELECT COUNT(*) FROM
is slow for
tbl_name
BDB
tables, because no row count is
maintained in the table.
The optimizer needs to know the approximate number of rows in
the table. MySQL solves this by counting inserts and
maintaining this in a separate segment in each
BDB
table. If you don't issue a lot of
DELETE
or ROLLBACK
statements, this number should be accurate enough for the
MySQL optimizer. However, MySQL stores the number only on
close, so it may be incorrect if the server terminates
unexpectedly. It should not be fatal even if this number is
not 100% correct. You can update the row count by using
ANALYZE TABLE
or OPTIMIZE
TABLE
. See Section 12.5.2.1, “ANALYZE TABLE
Syntax”, and
Section 12.5.2.5, “OPTIMIZE TABLE
Syntax”.
Internal locking in BDB
tables is done at
the page level.
LOCK TABLES
works on BDB
tables as with other tables. If you do not use LOCK
TABLES
, MySQL issues an internal multiple-write lock
on the table (a lock that does not block other writers) to
ensure that the table is properly locked if another thread
issues a table lock.
To support transaction rollback, the BDB
storage engine maintains log files. For maximum performance,
you can use the --bdb-logdir
option to place
the BDB
logs on a different disk than the
one where your databases are located.
MySQL performs a checkpoint each time a new
BDB
log file is started, and removes any
BDB
log files that are not needed for
current transactions. You can also use FLUSH
LOGS
at any time to checkpoint the Berkeley DB
tables.
For disaster recovery, you should use table backups plus MySQL's binary log. See Section 6.1, “Database Backups”.
If you delete old log files that are still in use,
BDB
is not able to do recovery at all and
you may lose data if something goes wrong.
Applications must always be prepared to handle cases where any
change of a BDB
table may cause an
automatic rollback and any read may fail with a deadlock
error.
If you get a full disk with a BDB
table,
you get an error (probably error 28) and the transaction
should roll back. This contrasts with
MyISAM
tables, for which
mysqld waits for sufficient free disk space
before continuing.
The following list indicates restrictions that you must observe
when using BDB
tables:
Each BDB
table stores in its
.db
file the path to the file as it was
created. This is done to enable detection of locks in a
multi-user environment that supports symlinks. As a
consequence of this, it is not possible to move
BDB
table files from one database directory
to another.
When making backups of BDB
tables, you must
either use mysqldump or else make a backup
that includes the files for each BDB
table
(the .frm
and .db
files) as well as the BDB
log files. The
BDB
storage engine stores unfinished
transactions in its log files and requires them to be present
when mysqld starts. The
BDB
logs are the files in the data
directory with names of the form
log.
(ten digits).
NNNNNNNNNN
If a column that allows NULL
values has a
unique index, only a single NULL
value is
allowed. This differs from other storage engines, which allow
multiple NULL
values in unique indexes.
If the following error occurs when you start
mysqld after upgrading, it means that the
current version of BDB
doesn't support the
old log file format:
bdb: Ignoring log file: .../log.NNNNNNNNNN
:
unsupported log version #
In this case, you must delete all BDB
logs
from your data directory (the files that have names of the
form
log.
)
and restart mysqld. We also recommend that
you then use mysqldump --opt to dump your
NNNNNNNNNN
BDB
tables, drop the tables, and restore
them from the dump file.
If autocommit mode is disabled and you drop a
BDB
table that is referenced in another
transaction, you may get error messages of the following form
in your MySQL error log:
001119 23:43:56 bdb: Missing log fileid entry 001119 23:43:56 bdb: txn_abort: Log undo failed for LSN: 1 3644744: Invalid
This is not fatal, but the fix is not trivial. We recommend
that you not drop BDB
tables except while
autocommit mode is enabled.
The EXAMPLE
storage engine is a stub engine that
does nothing. Its purpose is to serve as an example in the MySQL
source code that illustrates how to begin writing new storage
engines. As such, it is primarily of interest to developers.
The EXAMPLE
storage engine is included in MySQL
binary distributions. To enable this storage engine if you build
MySQL from source, invoke configure with the
--with-example-storage-engine
option.
To examine the source for the EXAMPLE
engine,
look in the sql/examples
directory of a MySQL
source distribution.
When you create an EXAMPLE
table, the server
creates a table format file in the database directory. The file
begins with the table name and has an .frm
extension. No other files are created. No data can be stored into
the table. Retrievals return an empty result.
mysql>CREATE TABLE test (i INT) ENGINE = EXAMPLE;
Query OK, 0 rows affected (0.78 sec) mysql>INSERT INTO test VALUES(1),(2),(3);
ERROR 1031 (HY000): Table storage engine for 'test' doesn't have this option mysql>SELECT * FROM test;
Empty set (0.31 sec)
The EXAMPLE
storage engine does not support
indexing.
The FEDERATED
storage engine is available
beginning with MySQL 5.0.3. It is a storage engine that accesses
data in tables of remote databases rather than in local tables.
The FEDERATED
storage engine is included in MySQL
binary distributions. To enable this storage engine if you build
MySQL from source, invoke configure with the
--with-federated-storage-engine
option.
To examine the source for the FEDERATED
engine,
look in the sql
directory of a source
distribution for MySQL 5.0.3 or newer.
Additional resources
A forum dedicated to the FEDERATED
storage
engine is available at http://forums.mysql.com/list.php?105.
MySQL Enterprise
MySQL Enterprise subscribers will find MySQL Knowledge Base
articles about the FEDERATED
storage engine at
FEDERATED Storage Engine. Access to the Knowledge Base
collection of articles is one of the advantages of subscribing to
MySQL Enterprise. For more information see
http://www.mysql.com/products/enterprise/advisors.html.
When you create a FEDERATED
table, the server
creates a table format file in the database directory. The file
begins with the table name and has an .frm
extension. No other files are created, because the actual data is
in a remote table. This differs from the way that storage engines
for local tables work.
For local database tables, data files are local. For example, if
you create a MyISAM
table named
users
, the MyISAM
handler
creates a data file named users.MYD
. A handler
for local tables reads, inserts, deletes, and updates data in
local data files, and rows are stored in a format particular to
the handler. To read rows, the handler must parse data into
columns. To write rows, column values must be converted to the row
format used by the handler and written to the local data file.
With the MySQL FEDERATED
storage engine, there
are no local data files for a table (for example, there is no
.MYD
file). Instead, a remote database stores
the data that normally would be in the table. The local server
connects to a remote server, and uses the MySQL client API to
read, delete, update, and insert data in the remote table. For
example, data retrieval is initiated via a SELECT * FROM
SQL statement.
tbl_name
When a client issues a SQL statement that refers to a
FEDERATED
table, the flow of information
between the local server (where the SQL statement is executed) and
the remote server (where the data is physically stored) is as
follows:
The storage engine looks through each column that the
FEDERATED
table has and constructs an
appropriate SQL statement that refers to the remote table.
The statement is sent to the remote server using the MySQL client API.
The remote server processes the statement and the the local server retrieves any result that the statement produces (an affected-rows count or a result set).
If the statement produces a result set, each column is
converted to internal storage engine format that the
FEDERATED
engine expects and can use to
display the result to the client that issued the original
statement.
The local server communicates with the remote server using MySQL
client C API functions. It invokes
mysql_real_query()
to send the
statement. To read a result set, it uses
mysql_store_result()
and fetches
rows one at a time using
mysql_fetch_row()
.
The procedure for using FEDERATED
tables is
very simple. Normally, you have two servers running, either both
on the same host or on different hosts. (It is possible for a
FEDERATED
table to use another table that is
managed by the same server, although there is little point in
doing so.)
First, you must have a table on the remote server that you want to
access by using a FEDERATED
table. Suppose that
the remote table is in the federated
database
and is defined like this:
CREATE TABLE test_table ( id INT(20) NOT NULL AUTO_INCREMENT, name VARCHAR(32) NOT NULL DEFAULT '', other INT(20) NOT NULL DEFAULT '0', PRIMARY KEY (id), INDEX name (name), INDEX other_key (other) ) ENGINE=MyISAM DEFAULT CHARSET=latin1;
The example uses a MyISAM
table, but the table
could use any storage engine.
Next, create a FEDERATED
table on the local
server for accessing the remote table:
CREATE TABLE federated_table ( id INT(20) NOT NULL AUTO_INCREMENT, name VARCHAR(32) NOT NULL DEFAULT '', other INT(20) NOT NULL DEFAULT '0', PRIMARY KEY (id), INDEX name (name), INDEX other_key (other) ) ENGINE=FEDERATED DEFAULT CHARSET=latin1 CONNECTION='mysql://fed_user@remote_host:9306/federated/test_table';
(Before MySQL 5.0.13, use COMMENT
rather than
CONNECTION
.)
The structure of this table must be exactly the same as that of
the remote table, except that the ENGINE
table
option should be FEDERATED
and the
CONNECTION
table option is a connection string
that indicates to the FEDERATED
engine how to
connect to the remote server.
The FEDERATED
engine creates only the
test_table.frm
file in the
federated
database.
The remote host information indicates the remote server to which
your local server connects, and the database and table information
indicates which remote table to use as the data source. In this
example, the remote server is indicated to be running as
remote_host
on port 9306, so there must be a
MySQL server running on the remote host and listening to port
9306.
The general form of the connection string in the
CONNECTION
option is as follows:
scheme
://user_name
[:password
]@host_name
[:port_num
]/db_name
/tbl_name
Only mysql
is supported as the
scheme
value at this point; the
password and port number are optional.
Sample connection strings:
CONNECTION='mysql://username:password@hostname:port/database/tablename' CONNECTION='mysql://username@hostname/database/tablename' CONNECTION='mysql://username:password@hostname/database/tablename'
The use of CONNECTION
for specifying the
connection string is non-optimal and is likely to change in
future. Keep this in mind for applications that use
FEDERATED
tables. Such applications are likely
to need modification if the format for specifying connection
information changes.
Because any password given in the connection string is stored as
plain text, it can be seen by any user who can use SHOW
CREATE TABLE
or SHOW TABLE STATUS
for
the FEDERATED
table, or query the
TABLES
table in the
INFORMATION_SCHEMA
database.
The following items indicate features that the
FEDERATED
storage engine does and does not
support:
The remote server must be a MySQL server. Support by
FEDERATED
for other database engines may be
added in the future.
The remote table that a FEDERATED
table
points to must exist before you try to
access the table through the FEDERATED
table.
It is possible for one FEDERATED
table to
point to another, but you must be careful not to create a
loop.
There is no support for transactions.
A FEDERATED
table does not support indexes
per se. Because access to the table is handled remotely, it is
the remote table that supports the indexes. Care should be
taken when creating a FEDERATED
table since
the index definition from an equivalent
MyISAM
or other table may not be supported.
For example, creating a FEDERATED
table
with an index prefix on VARCHAR
,
TEXT
or BLOB
columns
will fail. The following definition in
MyISAM
is valid:
CREATE TABLE `T1`(`A` VARCHAR(100),UNIQUE KEY(`A`(30))) ENGINE=MYISAM;
The key prefix in this example is incompatible with the
FEDERATED
engine, and the equivalent
statement will fail:
CREATE TABLE `T1`(`A` VARCHAR(100),UNIQUE KEY(`A`(30))) ENGINE=FEDERATED CONNECTION='MYSQL://127.0.0.1:3306/TEST/T1';
If possible, you should try to separate the column and index definition when creating tables on both the remote server and the local server to avoid these index issues.
Internally, the implementation uses SELECT
,
INSERT
, UPDATE
, and
DELETE
, but not HANDLER
.
The FEDERATED
storage engine supports
SELECT
, INSERT
,
UPDATE
, DELETE
, and
indexes. It does not support ALTER TABLE
,
or any Data Definition Language statements that directly
affect the structure of the table, other than DROP
TABLE
. The current implementation does not use
prepared statements.
FEDERATED
accepts INSERT ... ON
DUPLICATE KEY UPDATE
statements, but if a
duplicate-key violation occurs, the statement fails with an
error.
Performance on a FEDERATED
table when
performing bulk inserts (for example, on a INSERT
INTO ... SELECT ...
statement) is slower than with
other table types because each selected row is treated as an
individual INSERT
statement on the
federated table.
Before MySQL 5.0.46, for a multiple-row insert into a
FEDERATED
table that refers to a remote
transactional table, if the insert failed for a row due to
constraint failure, the remote table would contain a partial
commit (the rows preceding the failed one) instead of rolling
back the statement completely. This occurred because the rows
were treated as individual inserts.
As of MySQL 5.0.46, FEDERATED
performs
bulk-insert handling such that multiple rows are sent to the
remote table in a batch. This provides a performance
improvement. Also, if the remote table is transactional, it
enables the remote storage engine to perform statement
rollback properly should an error occur. This capability has
the following limitations:
The size of the insert cannot exceed the maximum packet size between servers. If the insert exceeds this size, it is broken into multiple packets and the rollback problem can occur.
Bulk-insert handling does not occur for INSERT
... ON DUPLICATE KEY UPDATE
.
There is no way for the FEDERATED
engine to
know if the remote table has changed. The reason for this is
that this table must work like a data file that would never be
written to by anything other than the database system. The
integrity of the data in the local table could be breached if
there was any change to the remote database.
Any DROP TABLE
statement issued against a
FEDERATED
table drops only the local table,
not the remote table.
FEDERATED
tables do not work with the query
cache.
Some of these limitations may be lifted in future versions of the
FEDERATED
handler.
The ARCHIVE
storage engine is used for storing
large amounts of data without indexes in a very small footprint.
The ARCHIVE
storage engine is included in MySQL
binary distributions. To enable this storage engine if you build
MySQL from source, invoke configure with the
--with-archive-storage-engine
option.
To examine the source for the ARCHIVE
engine,
look in the sql
directory of a MySQL source
distribution.
You can check whether the ARCHIVE
storage engine
is available with this statement:
mysql> SHOW VARIABLES LIKE 'have_archive';
When you create an ARCHIVE
table, the server
creates a table format file in the database directory. The file
begins with the table name and has an .frm
extension. The storage engine creates other files, all having names
beginning with the table name. The data and metadata files have
extensions of .ARZ
and
.ARM
, respectively. An
.ARN
file may appear during optimization
operations.
The ARCHIVE
engine supports
INSERT
and SELECT
, but not
DELETE
, REPLACE
, or
UPDATE
. It does support ORDER
BY
operations, BLOB
columns, and
basically all but spatial data types (see
Section 17.4.1, “MySQL Spatial Data Types”). The
ARCHIVE
engine uses row-level locking.
Storage: Rows are compressed as
they are inserted. The ARCHIVE
engine uses
zlib
lossless data compression (see
http://www.zlib.net/). You can use OPTIMIZE
TABLE
to analyze the table and pack it into a smaller
format (for a reason to use OPTIMIZE TABLE
, see
later in this section). Beginning with MySQL 5.0.15, the engine also
supports CHECK TABLE
. There are several types of
insertions that are used:
An INSERT
statement just pushes rows into a
compression buffer, and that buffer flushes as necessary. The
insertion into the buffer is protected by a lock. A
SELECT
forces a flush to occur, unless the
only insertions that have come in were INSERT
DELAYED
(those flush as necessary). See
Section 12.2.4.2, “INSERT DELAYED
Syntax”.
A bulk insert is visible only after it completes, unless other
inserts occur at the same time, in which case it can be seen
partially. A SELECT
never causes a flush of a
bulk insert unless a normal insert occurs while it is loading.
Retrieval: On retrieval, rows are
uncompressed on demand; there is no row cache. A
SELECT
operation performs a complete table scan:
When a SELECT
occurs, it finds out how many rows
are currently available and reads that number of rows.
SELECT
is performed as a consistent read. Note
that lots of SELECT
statements during insertion
can deteriorate the compression, unless only bulk or delayed inserts
are used. To achieve better compression, you can use
OPTIMIZE TABLE
or REPAIR
TABLE
. The number of rows in ARCHIVE
tables reported by SHOW TABLE STATUS
is always
accurate. See Section 12.5.2.5, “OPTIMIZE TABLE
Syntax”,
Section 12.5.2.6, “REPAIR TABLE
Syntax”, and
Section 12.5.4.24, “SHOW TABLE STATUS
Syntax”.
Additional resources
A forum dedicated to the ARCHIVE
storage
engine is available at http://forums.mysql.com/list.php?112.
The CSV
storage engine stores data in text files
using comma-separated values format. It is unavailable on Windows
until MySQL 5.1.
The CSV
storage engine is included in MySQL
binary distributions (except on Windows). To enable this storage
engine if you build MySQL from source, invoke
configure with the
--with-csv-storage-engine
option.
To examine the source for the CSV
engine, look in
the sql/examples
directory of a MySQL source
distribution.
When you create a CSV
table, the server creates a
table format file in the database directory. The file begins with
the table name and has an .frm
extension. The
storage engine also creates a data file. Its name begins with the
table name and has a .CSV
extension. The data
file is a plain text file. When you store data into the table, the
storage engine saves it into the data file in comma-separated values
format.
mysql>CREATE TABLE test (i INT NOT NULL, c CHAR(10) NOT NULL)
->ENGINE = CSV;
Query OK, 0 rows affected (0.12 sec) mysql>INSERT INTO test VALUES(1,'record one'),(2,'record two');
Query OK, 2 rows affected (0.00 sec) Records: 2 Duplicates: 0 Warnings: 0 mysql>SELECT * FROM test;
+------+------------+ | i | c | +------+------------+ | 1 | record one | | 2 | record two | +------+------------+ 2 rows in set (0.00 sec)
If you examine the test.CSV
file in the
database directory created by executing the preceding statements,
its contents should look like this:
"1","record one" "2","record two"
This format can be read, and even written, by spreadsheet applications such as Microsoft Excel or StarOffice Calc.
The CSV
storage engine does not support indexing.
The BLACKHOLE
storage engine acts as a
“black hole” that accepts data but throws it away and
does not store it. Retrievals always return an empty result:
mysql>CREATE TABLE test(i INT, c CHAR(10)) ENGINE = BLACKHOLE;
Query OK, 0 rows affected (0.03 sec) mysql>INSERT INTO test VALUES(1,'record one'),(2,'record two');
Query OK, 2 rows affected (0.00 sec) Records: 2 Duplicates: 0 Warnings: 0 mysql>SELECT * FROM test;
Empty set (0.00 sec)
The BLACKHOLE
storage engine is included in MySQL
binary distributions. To enable this storage engine if you build
MySQL from source, invoke configure with the
--with-blackhole-storage-engine
option.
To examine the source for the BLACKHOLE
engine,
look in the sql
directory of a MySQL source
distribution.
When you create a BLACKHOLE
table, the server
creates a table format file in the database directory. The file
begins with the table name and has an .frm
extension. There are no other files associated with the table.
The BLACKHOLE
storage engine supports all kinds
of indexes. That is, you can include index declarations in the table
definition.
You can check whether the BLACKHOLE
storage
engine is available with this statement:
mysql> SHOW VARIABLES LIKE 'have_blackhole_engine';
Inserts into a BLACKHOLE
table do not store any
data, but if the binary log is enabled, the SQL statements are
logged (and replicated to slave servers). This can be useful as a
repeater or filter mechanism. For example, suppose that your
application requires slave-side filtering rules, but transferring
all binary log data to the slave first results in too much traffic.
In such a case, it is possible to set up on the master host a
“dummy” slave process whose default storage engine is
BLACKHOLE
, depicted as follows:
The master writes to its binary log. The “dummy”
mysqld process acts as a slave, applying the
desired combination of replicate-do-*
and
replicate-ignore-*
rules, and writes a new,
filtered binary log of its own. (See
Section 15.1.2, “Replication Startup Options and Variables”.) This filtered log is
provided to the slave.
The dummy process does not actually store any data, so there is little processing overhead incurred by running the additional mysqld process on the replication master host. This type of setup can be repeated with additional replication slaves.
INSERT
triggers for BLACKHOLE
tables work as expected. However, because the
BLACKHOLE
table does not actually store any data,
UPDATE
and DELETE
triggers are
not activated: The FOR EACH ROW
clause in the
trigger definition does not apply because there are no rows.
Other possible uses for the BLACKHOLE
storage
engine include:
Verification of dump file syntax.
Measurement of the overhead from binary logging, by comparing
performance using BLACKHOLE
with and without
binary logging enabled.
BLACKHOLE
is essentially a
“no-op” storage engine, so it could be used for
finding performance bottlenecks not related to the storage
engine itself.