Table of Contents
InnoDB
is a general-purpose storage engine that
balances high reliability and high performance. In MySQL
5.7, InnoDB
is the default MySQL
storage engine. Unless you have configured a different default
storage engine, issuing a CREATE
TABLE
statement without an ENGINE=
clause creates an InnoDB
table.
Its DML operations follow the ACID model, with transactions featuring commit, rollback, and crash-recovery capabilities to protect user data. See Section 14.2, “InnoDB and the ACID Model” for more information.
Row-level locking and Oracle-style consistent reads increase multi-user concurrency and performance. See Section 14.5, “InnoDB Locking and Transaction Model” for more information.
InnoDB
tables arrange your data on disk to
optimize queries based on
primary keys. Each
InnoDB
table has a primary key index called
the clustered index
that organizes the data to minimize I/O for primary key lookups.
See Section 14.8.2.1, “Clustered and Secondary Indexes” for more information.
To maintain data
integrity,
InnoDB
supports
FOREIGN
KEY
constraints. With foreign keys, inserts,
updates, and deletes are checked to ensure they do not result in
inconsistencies across different tables. See
Section 14.8.1.6, “InnoDB and FOREIGN KEY Constraints” for more
information.
Table 14.1 InnoDB Storage Engine Features
Feature | Support |
---|---|
B-tree indexes | Yes |
Backup/point-in-time recovery (Implemented in the server, rather than in the storage engine.) | Yes |
Cluster database support | No |
Clustered indexes | Yes |
Compressed data | Yes |
Data caches | Yes |
Encrypted data (Implemented in the server via encryption functions. Data-at-rest tablespace encryption is available in MySQL 5.7 and later.) | Yes |
Foreign key support | Yes |
Full-text search indexes | Yes (InnoDB support for FULLTEXT indexes is available in MySQL 5.6 and later.) |
Geospatial data type support | Yes |
Geospatial indexing support | Yes (InnoDB support for geospatial indexing is available in MySQL 5.7 and later.) |
Hash indexes | No (InnoDB utilizes hash indexes internally for its Adaptive Hash Index feature.) |
Index caches | Yes |
Locking granularity | Row |
MVCC | Yes |
Query cache support | Yes |
Replication support (Implemented in the server, rather than in the storage engine.) | Yes |
Storage limits | 64TB |
T-tree indexes | No |
Transactions | Yes |
Update statistics for data dictionary | Yes |
To compare the features of InnoDB
with other
storage engines provided with MySQL, see the Storage
Engine Features table in
Chapter 15, Alternative Storage Engines.
For information about InnoDB
enhancements and new
features, refer to:
The InnoDB
enhancements list in
Section 1.4, “What Is New in MySQL 5.7”.
The Release Notes.
For InnoDB
-related terms and definitions, see
the MySQL Glossary.
For a forum dedicated to the InnoDB
storage
engine, see
MySQL
Forums::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/.
You may find InnoDB
tables beneficial for the
following reasons:
If your server crashes because of a hardware or software
issue, regardless of what was happening in the database at the
time, you don't need to do anything special after restarting
the database. InnoDB
crash recovery
automatically finalizes any changes that were committed before
the time of the crash, and undoes any changes that were in
process but not committed. Just restart and continue where you
left off.
The InnoDB
storage engine maintains its own
buffer pool that
caches table and index data in main memory as data is
accessed. Frequently used data is processed directly from
memory. This cache applies to many types of information and
speeds up processing. On dedicated database servers, up to 80%
of physical memory is often assigned to the buffer pool.
If you split up related data into different tables, you can set up foreign keys that enforce referential integrity. Update or delete data, and the related data in other tables is updated or deleted automatically. Try to insert data into a secondary table without corresponding data in the primary table, and the bad data gets kicked out automatically.
If data becomes corrupted on disk or in memory, a checksum mechanism alerts you to the bogus data before you use it.
When you design your database with appropriate
primary key columns
for each table, operations involving those columns are
automatically optimized. It is very fast to reference the
primary key columns in
WHERE
clauses, ORDER
BY
clauses,
GROUP BY
clauses, and join operations.
Inserts, updates, and deletes are optimized by an automatic
mechanism called change
buffering. InnoDB
not only allows
concurrent read and write access to the same table, it caches
changed data to streamline disk I/O.
Performance benefits are not limited to giant tables with long-running queries. When the same rows are accessed over and over from a table, a feature called the Adaptive Hash Index takes over to make these lookups even faster, as if they came out of a hash table.
You can compress tables and associated indexes.
You can create and drop indexes with much less impact on performance and availability.
Truncating a
file-per-table
tablespace is very fast, and can free up disk space for the
operating system to reuse, rather than freeing up space within
the system
tablespace that only InnoDB
can
reuse.
The storage layout for table data is more efficient for
BLOB
and long text fields, with
the DYNAMIC row
format.
You can monitor the internal workings of the storage engine by querying INFORMATION_SCHEMA tables.
You can monitor the performance details of the storage engine by querying Performance Schema tables.
You can freely mix InnoDB
tables with
tables from other MySQL storage engines, even within the same
statement. For example, you can use a
join operation to combine
data from InnoDB
and
MEMORY
tables in a single query.
InnoDB
has been designed for CPU efficiency
and maximum performance when processing large data volumes.
InnoDB
tables can handle large quantities
of data, even on operating systems where file size is limited
to 2GB.
For InnoDB
-specific tuning techniques you can
apply in your application code, see
Section 8.5, “Optimizing for InnoDB Tables”.
This section describes best practices when using
InnoDB
tables.
Specifying a primary key for every table using the most frequently queried column or columns, or an auto-increment value if there is no obvious primary key.
Using joins wherever data is pulled from multiple tables based on identical ID values from those tables. For fast join performance, define foreign keys on the join columns, and declare those columns with the same data type in each table. Adding foreign keys ensures that referenced columns are indexed, which can improve performance. Foreign keys also propagate deletes or updates to all affected tables, and prevent insertion of data in a child table if the corresponding IDs are not present in the parent table.
Turning off autocommit. Committing hundreds of times a second puts a cap on performance (limited by the write speed of your storage device).
Grouping sets of related DML
operations into
transactions, by
bracketing them with START TRANSACTION
and
COMMIT
statements. While you don't want to
commit too often, you also don't want to issue huge batches of
INSERT
,
UPDATE
, or
DELETE
statements that run for
hours without committing.
Not using LOCK TABLES
statements. InnoDB
can handle multiple
sessions all reading and writing to the same table at once,
without sacrificing reliability or high performance. To get
exclusive write access to a set of rows, use the
SELECT
... FOR UPDATE
syntax to lock just the rows you
intend to update.
Enabling the
innodb_file_per_table
option
or using general tablespaces to put the data and indexes for
tables into separate files, instead of the
system
tablespace.
The innodb_file_per_table
option is enabled by default.
Evaluating whether your data and access patterns benefit from
the InnoDB
table or page
compression features.
You can compress InnoDB
tables without
sacrificing read/write capability.
Running your server with the option
--sql_mode=NO_ENGINE_SUBSTITUTION
to prevent tables being created with a different storage
engine if there is an issue with the engine specified in the
ENGINE=
clause of
CREATE TABLE
.
Issue the SHOW ENGINES
statement to
view the available MySQL storage engines. Look for
DEFAULT
in the InnoDB
line.
mysql> SHOW ENGINES;
Alternatively, query the
INFORMATION_SCHEMA.ENGINES
table.
mysql> SELECT * FROM INFORMATION_SCHEMA.ENGINES;
If InnoDB
is not your default storage engine,
you can determine if your database server or applications work
correctly with InnoDB
by restarting the server
with
--default-storage-engine=InnoDB
defined on the command line or with
default-storage-engine=innodb
defined in the [mysqld]
section of your MySQL
server option file.
Since changing the default storage engine only affects new tables
as they are created, run all your application installation and
setup steps to confirm that everything installs properly. Then
exercise all the application features to make sure all the data
loading, editing, and querying features work. If a table relies on
a feature that is specific to another storage engine, you will
receive an error; add the
ENGINE=
clause to the other_engine_name
CREATE TABLE
statement to avoid the error.
If you did not make a deliberate decision about the storage
engine, and you want to preview how certain tables work when
created using InnoDB
, issue the command
ALTER TABLE
table_name ENGINE=InnoDB;
for each table. Or, to run
test queries and other statements without disturbing the original
table, make a copy:
CREATE TABLE InnoDB_Table (...) ENGINE=InnoDB AS SELECT * FROM other_engine_table
;
To assess performance with a full application under a realistic workload, install the latest MySQL server and run benchmarks.
Test the full application lifecycle, from installation, through heavy usage, and server restart. Kill the server process while the database is busy to simulate a power failure, and verify that the data is recovered successfully when you restart the server.
Test any replication configurations, especially if you use different MySQL versions and options on the master and slaves.
Oracle recommends InnoDB
as the preferred
storage engine for typical database applications, from single-user
wikis and blogs running on a local system, to high-end
applications pushing the limits of performance. In MySQL
5.7, InnoDB
is the default storage
engine for new tables.
InnoDB
cannot be disabled. The
--skip-innodb
option is deprecated and has no effect, and its use results in a
warning. It will be removed in a future MySQL release. This also
applies to its synonyms (--innodb=OFF
,
--disable-innodb
, and so forth).
The ACID model is a set of database
design principles that emphasize aspects of reliability that are
important for business data and mission-critical applications. MySQL
includes components such as the InnoDB
storage
engine that adhere closely to the ACID model, so that data is not
corrupted and results are not distorted by exceptional conditions
such as software crashes and hardware malfunctions. When you rely on
ACID-compliant features, you do not need to reinvent the wheel of
consistency checking and crash recovery mechanisms. In cases where
you have additional software safeguards, ultra-reliable hardware, or
an application that can tolerate a small amount of data loss or
inconsistency, you can adjust MySQL settings to trade some of the
ACID reliability for greater performance or throughput.
The following sections discuss how MySQL features, in particular the
InnoDB
storage engine, interact with the
categories of the ACID model:
A: atomicity.
C: consistency.
I:: isolation.
D: durability.
The atomicity aspect of the ACID
model mainly involves InnoDB
transactions. Related MySQL
features include:
The consistency aspect of the ACID
model mainly involves internal InnoDB
processing
to protect data from crashes. Related MySQL features include:
InnoDB
doublewrite
buffer.
InnoDB
crash recovery.
The isolation aspect of the ACID
model mainly involves InnoDB
transactions, in particular
the isolation level that
applies to each transaction. Related MySQL features include:
Autocommit setting.
SET ISOLATION LEVEL
statement.
The low-level details of InnoDB
locking. During performance
tuning, you see these details through
INFORMATION_SCHEMA
tables.
The durability aspect of the ACID model involves MySQL software features interacting with your particular hardware configuration. Because of the many possibilities depending on the capabilities of your CPU, network, and storage devices, this aspect is the most complicated to provide concrete guidelines for. (And those guidelines might take the form of buy “new hardware”.) Related MySQL features include:
InnoDB
doublewrite
buffer, turned on and off by the
innodb_doublewrite
configuration option.
Configuration option
innodb_flush_log_at_trx_commit
.
Configuration option
sync_binlog
.
Configuration option
innodb_file_per_table
.
Write buffer in a storage device, such as a disk drive, SSD, or RAID array.
Battery-backed cache in a storage device.
The operating system used to run MySQL, in particular its
support for the fsync()
system call.
Uninterruptible power supply (UPS) protecting the electrical power to all computer servers and storage devices that run MySQL servers and store MySQL data.
Your backup strategy, such as frequency and types of backups, and backup retention periods.
For distributed or hosted data applications, the particular characteristics of the data centers where the hardware for the MySQL servers is located, and network connections between the data centers.
InnoDB
is a
multi-versioned storage engine: it
keeps information about old versions of changed rows, to support
transactional features such as concurrency and
rollback. This information is
stored in the tablespace in a data structure called a
rollback segment (after
an analogous data structure in Oracle). 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.
Internally, InnoDB
adds three fields to each row
stored in the database. A 6-byte DB_TRX_ID
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
DB_ROLL_PTR
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. A 6-byte DB_ROW_ID
field contains a
row ID that increases monotonically as new rows are inserted. If
InnoDB
generates a clustered index automatically,
the index contains row ID values. Otherwise, the
DB_ROW_ID
column does not appear in any index.
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.
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 needed 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. InnoDB
only physically
removes the corresponding row and its index records when it discards
the update undo log record written for the deletion. 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.
If you insert and delete rows in smallish batches at about the same
rate in the table, the purge thread can start to lag behind and the
table can grow bigger and bigger because of all the
“dead” rows, making everything disk-bound and very
slow. In such a case, throttle new row operations, and allocate more
resources to the purge thread by tuning the
innodb_max_purge_lag
system
variable. See Section 14.14, “InnoDB Startup Options and System Variables” for more
information.
InnoDB
multiversion concurrency control (MVCC)
treats secondary indexes differently than clustered indexes.
Records in a clustered index are updated in-place, and their
hidden system columns point undo log entries from which earlier
versions of records can be reconstructed. Unlike clustered index
records, secondary index records do not contain hidden system
columns nor are they updated in-place.
When a secondary index column is updated, old secondary index
records are delete-marked, new records are inserted, and
delete-marked records are eventually purged. When a secondary
index record is delete-marked or the secondary index page is
updated by a newer transaction, InnoDB
looks up
the database record in the clustered index. In the clustered
index, the record's DB_TRX_ID
is checked, and
the correct version of the record is retrieved from the undo log
if the record was modified after the reading transaction was
initiated.
If a secondary index record is marked for deletion or the
secondary index page is updated by a newer transaction, the
covering index
technique is not used. Instead of returning values from the index
structure, InnoDB
looks up the record in the
clustered index.
However, if the
index
condition pushdown (ICP) optimization is enabled, and parts
of the WHERE
condition can be evaluated using
only fields from the index, the MySQL server still pushes this
part of the WHERE
condition down to the storage
engine where it is evaluated using the index. If no matching
records are found, the clustered index lookup is avoided. If
matching records are found, even among delete-marked records,
InnoDB
looks up the record in the clustered
index.
This section provides an introduction to the major components of the
InnoDB
storage engine architecture.
The buffer pool is an area in main memory where
InnoDB
caches table and index data as data is
accessed. The buffer pool allows frequently used data to be
processed directly from memory, which speeds up processing. On
dedicated database servers, up to 80% of physical memory is often
assigned to the InnoDB
buffer pool.
For efficiency of high-volume read operations, the buffer pool is divided into pages that can potentially hold multiple rows. For efficiency of cache management, the buffer pool is implemented as a linked list of pages; data that is rarely used is aged out of the cache, using a variation of the LRU algorithm.
For more information, see Section 14.6.3.1, “The InnoDB Buffer Pool”, and Section 14.6.3, “InnoDB Buffer Pool Configuration”.
The change buffer is a special data structure that caches changes
to secondary index
pages when affected pages are not in the
buffer pool. The buffered
changes, which may result from
INSERT
,
UPDATE
, or
DELETE
operations (DML), are merged
later when the pages are loaded into the buffer pool by other read
operations.
Unlike clustered indexes, secondary indexes are usually nonunique, and inserts into secondary indexes happen in a relatively random order. Similarly, deletes and updates may affect secondary index pages that are not adjacently located in an index tree. Merging cached changes at a later time, when affected pages are read into the buffer pool by other operations, avoids substantial random access I/O that would be required to read-in secondary index pages from disk.
Periodically, the purge operation that runs when the system is mostly idle, or during a slow shutdown, writes the updated index pages to disk. The purge operation can write disk blocks for a series of index values more efficiently than if each value were written to disk immediately.
Change buffer merging may take several hours when there are numerous secondary indexes to update and many affected rows. During this time, disk I/O is increased, which can cause a significant slowdown for disk-bound queries. Change buffer merging may also continue to occur after a transaction is committed. In fact, change buffer merging may continue to occur after a server shutdown and restart (see Section 14.21.2, “Forcing InnoDB Recovery” for more information).
In memory, the change buffer occupies part of the
InnoDB
buffer pool. On disk, the change buffer
is part of the system tablespace, so that index changes remain
buffered across database restarts.
The type of data cached in the change buffer is governed by the
innodb_change_buffering
configuration option. For more information, see
Section 14.6.5, “Configuring InnoDB Change Buffering”. You can
also configure the maximum change buffer size. For more
information, see
Section 14.6.5.1, “Configuring the Change Buffer Maximum Size”.
The following options are available for change buffer monitoring:
InnoDB
Standard Monitor output includes
status information for the change buffer. To view monitor
data, issue the SHOW ENGINE INNODB STATUS
command.
mysql> SHOW ENGINE INNODB STATUS\G
Change buffer status information is located under the
INSERT BUFFER AND ADAPTIVE HASH INDEX
heading and appears similar to the following:
------------------------------------- INSERT BUFFER AND ADAPTIVE HASH INDEX ------------------------------------- Ibuf: size 1, free list len 0, seg size 2, 0 merges merged operations: insert 0, delete mark 0, delete 0 discarded operations: insert 0, delete mark 0, delete 0 Hash table size 4425293, used cells 32, node heap has 1 buffer(s) 13577.57 hash searches/s, 202.47 non-hash searches/s
For more information, see Section 14.17.3, “InnoDB Standard Monitor and Lock Monitor Output”.
The
INFORMATION_SCHEMA.INNODB_METRICS
table provides most of the data points found in
InnoDB
Standard Monitor output, plus
other data points. To view change buffer metrics and a
description of each, issue the following query:
mysql> SELECT NAME, COMMENT FROM INFORMATION_SCHEMA.INNODB_METRICS WHERE NAME LIKE '%ibuf%'\G
For INNODB_METRICS
table usage
information, see
Section 14.15.6, “InnoDB INFORMATION_SCHEMA Metrics Table”.
The
INFORMATION_SCHEMA.INNODB_BUFFER_PAGE
table provides metadata about each page in the buffer pool,
including change buffer index and change buffer bitmap
pages. Change buffer pages are identified by
PAGE_TYPE
. IBUF_INDEX
is the page type for change buffer index pages, and
IBUF_BITMAP
is the page type for change
buffer bitmap pages.
Querying the
INNODB_BUFFER_PAGE
table can
introduce significant performance overhead. To avoid
impacting performance, reproduce the issue you want to
investigate on a test instance and run your queries on the
test instance.
For example, you can query the
INNODB_BUFFER_PAGE
table to
determine the approximate number of
IBUF_INDEX
and
IBUF_BITMAP
pages as a percentage of
total buffer pool pages.
mysql>SELECT (SELECT COUNT(*) FROM INFORMATION_SCHEMA.INNODB_BUFFER_PAGE
WHERE PAGE_TYPE LIKE 'IBUF%') AS change_buffer_pages,
(SELECT COUNT(*) FROM INFORMATION_SCHEMA.INNODB_BUFFER_PAGE) AS total_pages,
(SELECT ((change_buffer_pages/total_pages)*100))
AS change_buffer_page_percentage;
+---------------------+-------------+-------------------------------+ | change_buffer_pages | total_pages | change_buffer_page_percentage | +---------------------+-------------+-------------------------------+ | 25 | 8192 | 0.3052 | +---------------------+-------------+-------------------------------+
For information about other data provided by the
INNODB_BUFFER_PAGE
table, see
Section 24.31.1, “The INFORMATION_SCHEMA INNODB_BUFFER_PAGE Table”. For related
usage information, see
Section 14.15.5, “InnoDB INFORMATION_SCHEMA Buffer Pool Tables”.
Performance Schema provides change buffer mutex wait instrumentation for advanced performance monitoring. To view change buffer instrumentation, issue the following query:
mysql>SELECT * FROM performance_schema.setup_instruments
WHERE NAME LIKE '%wait/synch/mutex/innodb/ibuf%';
+-------------------------------------------------------+---------+-------+ | NAME | ENABLED | TIMED | +-------------------------------------------------------+---------+-------+ | wait/synch/mutex/innodb/ibuf_bitmap_mutex | YES | YES | | wait/synch/mutex/innodb/ibuf_mutex | YES | YES | | wait/synch/mutex/innodb/ibuf_pessimistic_insert_mutex | YES | YES | +-------------------------------------------------------+---------+-------+
For information about monitoring InnoDB
mutex waits, see
Section 14.16.2, “Monitoring InnoDB Mutex Waits Using Performance Schema”.
The adaptive hash
index (AHI) lets InnoDB
perform more
like an in-memory database on systems with appropriate
combinations of workload and ample memory for the
buffer pool, without
sacrificing any transactional features or reliability. This
feature is enabled by the
innodb_adaptive_hash_index
option, or turned off by
--skip-innodb_adaptive_hash_index
at server
startup.
Based on the observed pattern of searches, MySQL builds a hash index using a prefix of the index key. The prefix of the key can be any length, and it may be that only some of the values in the B-tree appear in the hash index. Hash indexes are built on demand for those pages of the index that are often accessed.
If a table fits almost entirely in main memory, a hash index can
speed up queries by enabling direct lookup of any element, turning
the index value into a sort of pointer. InnoDB
has a mechanism that monitors index searches. If
InnoDB
notices that queries could benefit from
building a hash index, it does so automatically.
With some workloads, the
speedup from hash index lookups greatly outweighs the extra work
to monitor index lookups and maintain the hash index structure.
Sometimes, the read/write lock that guards access to the adaptive
hash index can become a source of contention under heavy
workloads, such as multiple concurrent joins. Queries with
LIKE
operators and %
wildcards also tend not to benefit from the AHI. For workloads
where the adaptive hash index is not needed, turning it off
reduces unnecessary performance overhead. Because it is difficult
to predict in advance whether this feature is appropriate for a
particular system, consider running benchmarks with it both
enabled and disabled, using a realistic workload. The
architectural changes in MySQL 5.6 and higher make more workloads
suitable for disabling the adaptive hash index than in earlier
releases, although it is still enabled by default.
In MySQL 5.7, the adaptive hash index search system
is partitioned. Each index is bound to a specific partition, and
each partition is protected by a separate latch. Partitioning is
controlled by the
innodb_adaptive_hash_index_parts
configuration option. In earlier releases, the adaptive hash index
search system was protected by a single latch which could become a
point of contention under heavy workloads. The
innodb_adaptive_hash_index_parts
option is set to 8 by default. The maximum setting is 512.
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, covering only those
pages of the index that are often accessed.
You can monitor the use of the adaptive hash index and the
contention for its use in the SEMAPHORES
section of the output of the
SHOW ENGINE INNODB
STATUS
command. If you see many threads waiting on an
RW-latch created in btr0sea.c
, then it might
be useful to disable adaptive hash indexing.
For more information about the performance characteristics of hash indexes, see Section 8.3.8, “Comparison of B-Tree and Hash Indexes”.
The redo log buffer is the memory area that holds data to be
written to the redo log. Redo
log buffer size is defined by the
innodb_log_buffer_size
configuration option. The redo log buffer is periodically flushed
to the log file on disk. A large redo log buffer enables large
transactions to run without the need to write redo log to disk
before the transactions commit. Thus, if you have transactions
that update, insert, or delete many rows, making the log buffer
larger saves disk I/O.
The
innodb_flush_log_at_trx_commit
option controls how the contents of the redo log buffer are
written to the log file. The
innodb_flush_log_at_timeout
option controls redo log flushing frequency.
The InnoDB
system tablespace contains the
InnoDB
data dictionary (metadata for
InnoDB
-related objects) and is the storage area
for the doublewrite buffer, the change buffer, and undo logs. The
system tablespace also contains table and index data for any
user-created tables that are created in the system tablespace. The
system tablespace is considered a shared tablespace since it is
shared by multiple tables.
The system tablespace is represented by one or more data files. By
default, one system data file, named ibdata1
,
is created in the MySQL data
directory. The
size and number of system data files is controlled by the
innodb_data_file_path
startup
option.
For related information, see Section 14.6.1, “InnoDB Startup Configuration”, and Section 14.7.1, “Resizing the InnoDB System Tablespace”.
The InnoDB
data dictionary is comprised of
internal system tables that contain metadata used to keep track of
objects such as tables, indexes, and table columns. The metadata
is physically located in the InnoDB
system
tablespace. For historical reasons, data dictionary metadata
overlaps to some degree with information stored in
InnoDB
table metadata files
(.frm
files).
The doublewrite buffer is a storage area located in the system
tablespace where InnoDB
writes pages that are
flushed from the InnoDB
buffer pool, before the
pages are written to their proper positions in the data file. Only
after flushing and writing pages to the doublewrite buffer, does
InnoDB
write pages to their proper positions.
If there is an operating system, storage subsystem, or
mysqld process crash in the middle of a page
write, InnoDB
can later find a good copy of the
page from the doublewrite buffer during crash recovery.
Although data is always written twice, the doublewrite buffer does
not require twice as much I/O overhead or twice as many I/O
operations. Data is written to the doublewrite buffer itself as a
large sequential chunk, with a single fsync()
call to the operating system.
The doublewrite buffer is enabled by default in most cases. To
disable the doublewrite buffer, set
innodb_doublewrite
to 0.
If system tablespace files (“ibdata files”) are
located on Fusion-io devices that support atomic writes,
doublewrite buffering is automatically disabled and Fusion-io
atomic writes are used for all data files. Because the doublewrite
buffer setting is global, doublewrite buffering is also disabled
for data files residing on non-Fusion-io hardware. This feature is
only supported on Fusion-io hardware and is only enabled for
Fusion-io NVMFS on Linux. To take full advantage of this feature,
an innodb_flush_method
setting of
O_DIRECT
is recommended.
An undo log is a collection of undo log records associated with a single transaction. An undo log record contains information about how to undo the latest change by a transaction to a clustered index record. If another transaction needs to see the original data (as part of a consistent read operation), the unmodified data is retrieved from the undo log records. Undo logs exist within undo log segments, which are contained within rollback segments. Rollback segments reside in the system tablespace, temporary tablespace, and undo tablespaces. For more information, see Section 14.7.7, “Configuring Undo Tablespaces”. For information about multi-versioning, see Section 14.3, “InnoDB Multi-Versioning”.
InnoDB
supports 128 rollback segments, 32 of
which are reserved as non-redo rollback segments for temporary
table transactions. Each transaction that updates a temporary
table (excluding read-only transactions) is assigned two rollback
segments, one redo-enabled rollback segment and one non-redo
rollback segment. Read-only transactions are only assigned
non-redo rollback segments, as read-only transactions are only
permitted to modify temporary tables.
This leaves 96 available rollback segments, each of which supports up to 1023 concurrent data-modifying transactions, for a total limit of approximately 96K concurrent data-modifying transactions. The 96K limit assumes that transactions do not modify temporary tables. If all data-modifying transactions also modify temporary tables, the total limit is approximately 32K concurrent data modifying transactions. For more information about rollback segments that are reserved for temporary table transactions, see Temporary Table Undo Logs.
The innodb_rollback_segments
option defines the number of rollback segments used by
InnoDB
.
A file-per-table tablespace is a single-table tablespace that is
created in its own data file rather than in the system tablespace.
Tables are created in file-per-table tablespaces when the
innodb_file_per_table
option is
enabled. Otherwise, InnoDB
tables are created
in the system tablespace. Each file-per-table tablespace is
represented by a single .ibd
data file, which
is created in the database directory by default.
File per-table tablespaces support DYNAMIC
and
COMPRESSED
row formats which support features
such as off-page storage for variable length data and table
compression. For information about these features, and about other
advantages of file-per-table tablespaces, see
Section 14.7.4, “InnoDB File-Per-Table Tablespaces”.
A shared InnoDB
tablespace created using
CREATE TABLESPACE
syntax. General
tablespaces can be created outside of the MySQL data directory,
are capable of holding multiple tables, and support tables of all
row formats.
Tables are added to a general tablespace using
CREATE TABLE
or
tbl_name
... TABLESPACE [=]
tablespace_name
ALTER TABLE
syntax.
tbl_name
TABLESPACE [=]
tablespace_name
For more information, see Section 14.7.9, “InnoDB General Tablespaces”.
An undo tablespace comprises one or more files that contain
undo logs. The number of undo
tablespaces used by InnoDB
is defined by the
innodb_undo_tablespaces
configuration option. For more information, see
Section 14.7.7, “Configuring Undo Tablespaces”.
innodb_undo_tablespaces
is
deprecated and will be removed in a future release.
Non-compressed, user-created temporary tables and on-disk internal
temporary tables are created in a shared temporary tablespace. The
innodb_temp_data_file_path
configuration option defines the relative path, name, size, and
attributes for temporary tablespace data files. If no value is
specified for
innodb_temp_data_file_path
, the
default behavior is to create an auto-extending data file named
ibtmp1
in the
innodb_data_home_dir
directory
that is slightly larger than 12MB.
Compressed temporary tables, which are temporary tables created
using the ROW_FORMAT=COMPRESSED
attribute, are
created in
file-per-table
tablespaces in the temporary file directory.
The temporary tablespace is removed on normal shutdown or on an aborted initialization, and is recreated each time the server is started. The temporary tablespace receives a dynamically generated space ID when it is created. Startup is refused if the temporary tablespace cannot be created. The temporary tablespace is not removed if the server halts unexpectedly. In this case, a database administrator can remove the temporary tablespace manually or restart the server, which removes and recreates the temporary tablespace automatically.
The temporary tablespace cannot reside on a raw device.
INFORMATION_SCHEMA.FILES
provides
metadata about the InnoDB
temporary tablespace.
Issue a query similar to this one to view temporary tablespace
metadata:
mysql> SELECT * FROM INFORMATION_SCHEMA.FILES WHERE TABLESPACE_NAME='innodb_temporary'\G
INFORMATION_SCHEMA.INNODB_TEMP_TABLE_INFO
provides metadata about user-created temporary tables that are
currently active within an InnoDB
instance. For
more information, see
Section 14.15.7, “InnoDB INFORMATION_SCHEMA Temporary Table Info Table”.
By default, the temporary tablespace data file is autoextending and increases in size as necessary to accommodate on-disk temporary tables. For example, if an operation creates a temporary table that is 20MB in size, the temporary tablespace data file, which is 12MB in size by default when created, extends in size to accommodate it. When temporary tables are dropped, freed space can be reused for new temporary tables, but the data file remains at the extended size.
An autoextending temporary tablespace data file can become large in environments that use large temporary tables or that use temporary tables extensively. A large data file can also result from long running queries that use temporary tables.
To determine if a temporary tablespace data file is
autoextending, check the
innodb_temp_data_file_path
setting:
mysql> SELECT @@innodb_temp_data_file_path;
+------------------------------+
| @@innodb_temp_data_file_path |
+------------------------------+
| ibtmp1:12M:autoextend |
+------------------------------+
To check the size of temporary tablespace data files, query the
INFORMATION_SCHEMA.FILES
table
using a query similar to this:
mysql>SELECT FILE_NAME, TABLESPACE_NAME, ENGINE, INITIAL_SIZE, TOTAL_EXTENTS*EXTENT_SIZE
AS TotalSizeBytes, DATA_FREE, MAXIMUM_SIZE FROM INFORMATION_SCHEMA.FILES
WHERE TABLESPACE_NAME = 'innodb_temporary'\G
*************************** 1. row *************************** FILE_NAME: ./ibtmp1 TABLESPACE_NAME: innodb_temporary ENGINE: InnoDB INITIAL_SIZE: 12582912 TotalSizeBytes: 12582912 DATA_FREE: 6291456 MAXIMUM_SIZE: NULL
The TotalSizeBytes
value reports the current
size of the temporary tablespace data file. For information
about other field values, see Section 24.8, “The INFORMATION_SCHEMA FILES Table”.
Alternatively, you can check the temporary tablespace data file
size on your operating system. By default, the temporary
tablespace data file is located in the directory defined by the
innodb_temp_data_file_path
configuration option. If a value was not specified for this
option explicitly, a temporary tablespace data file named
ibtmp1
is created in
innodb_data_home_dir
, which
defaults to the MySQL data directory if unspecified.
To reclaim disk space occupied by a temporary tablespace data
file, you can restart the MySQL server. Restarting the server
removes and recreates the temporary tablespace data file
according to the attributes defined by
innodb_temp_data_file_path
.
To prevent the temporary data file from becoming too large, you
can configure the
innodb_temp_data_file_path
option to specify a maximum file size. For example:
[mysqld] innodb_temp_data_file_path=ibtmp1:12M:autoextend:max:500M
When the data file reaches the maximum size, queries fail with
an error indicating that the table is full. Configuring
innodb_temp_data_file_path
requires restarting the server.
Alternatively, you can configure the
default_tmp_storage_engine
and
internal_tmp_disk_storage_engine
options, which define the storage engine to use for user-created
and on-disk internal temporary tables, respectively. Both
options are set to InnoDB
by default. The
MyISAM
storage engine uses an individual file
for each temporary table, which is removed when the temporary
table is dropped.
Temporary table undo logs reside in the temporary tablespace and are used for temporary tables and related objects. Temporary table undo logs are not redo-logged, as they are not required for crash recovery. They are only used for rollback while the server is running. This special type of undo log benefits performance by avoiding redo logging I/O. 32 rollback segments are reserved for temporary table undo logs for transactions that modify temporary tables and related objects.
The redo log is a disk-based data structure used during crash
recovery to correct data written by incomplete transactions.
During normal operations, the redo log encodes requests to change
InnoDB
table data that result from SQL
statements or low-level API calls. Modifications that did not
finish updating the data files before an unexpected shutdown are
replayed automatically during initialization, and before the
connections are accepted. For information about the role of the
redo log in crash recovery, see Section 14.18.2, “InnoDB Recovery”.
By default, the redo log is physically represented on disk as a
set of files, named ib_logfile0
and
ib_logfile1
. MySQL writes to the redo log
files in a circular fashion. Data in the redo log is encoded in
terms of records affected; this data is collectively referred to
as redo. The passage of data through the redo log is represented
by an ever-increasing LSN value.
For related information, see:
InnoDB
, like any other
ACID-compliant database engine,
flushes the redo log of a
transaction before it is committed. InnoDB
uses group commit
functionality to group multiple such flush requests together to
avoid one flush for each commit. With group commit,
InnoDB
issues a single write to the log file
to perform the commit action for multiple user transactions that
commit at about the same time, significantly improving
throughput.
For more information about performance of
COMMIT
and other transactional operations,
see Section 8.5.2, “Optimizing InnoDB Transaction Management”.
To implement a large-scale, busy, or highly reliable database
application, to port substantial code from a different database
system, or to tune MySQL performance, it is important to understand
InnoDB
locking and the InnoDB
transaction model.
This section discusses several topics related to
InnoDB
locking and the InnoDB
transaction model with which you should be familiar.
Section 14.5.1, “InnoDB Locking” describes lock types used by
InnoDB
.
Section 14.5.2, “InnoDB Transaction Model” describes transaction
isolation levels and the locking strategies used by each. It
also discusses the use of
autocommit
, consistent
non-locking reads, and locking reads.
Section 14.5.3, “Locks Set by Different SQL Statements in InnoDB” discusses specific types of
locks set in InnoDB
for various statements.
Section 14.5.4, “Phantom Rows” describes how
InnoDB
uses next-key locking to avoid phantom
rows.
Section 14.5.5, “Deadlocks in InnoDB” provides a deadlock example,
discusses deadlock detection and rollback, and provides tips for
minimizing and handling deadlocks in InnoDB
.
This section describes lock types used by
InnoDB
.
InnoDB
implements standard row-level locking
where there are two types of locks,
shared
(S
) locks and
exclusive
(X
) locks.
A shared
(S
) lock permits the
transaction that holds the lock to read a row.
An exclusive
(X
) lock permits the
transaction that holds the lock to update or delete a row.
If transaction T1
holds a shared
(S
) lock on row r
,
then requests from some distinct transaction
T2
for a lock on row r
are
handled as follows:
A request by T2
for an
S
lock can be granted
immediately. As a result, both T1
and
T2
hold an S
lock on r
.
A request by T2
for an
X
lock cannot be granted
immediately.
If a transaction T1
holds an exclusive
(X
) lock on row r
,
a request from some distinct transaction T2
for a lock of either type on r
cannot be
granted immediately. Instead, transaction T2
has to wait for transaction T1
to release its
lock on row r
.
InnoDB
supports multiple
granularity locking which permits coexistence of row
locks and table locks. For example, a statement such as
LOCK TABLES ...
WRITE
takes an exclusive lock (an X
lock) on the specified table. To make locking at multiple
granularity levels practical, InnoDB
uses
intention locks.
Intention locks are table-level locks that indicate which type
of lock (shared or exclusive) a transaction requires later for a
row in a table. There are two types of intention locks:
An intention
shared lock (IS
) indicates that a
transaction intends to set a shared
lock on individual rows in a table.
An intention
exclusive lock (IX
) indicates that
that a transaction intends to set an exclusive lock on
individual rows in a table.
For example, SELECT ...
LOCK IN SHARE MODE
sets an IS
lock,
and SELECT ... FOR
UPDATE
sets an IX
lock.
The intention locking protocol is as follows:
Before a transaction can acquire a shared lock on a row in a
table, it must first acquire an IS
lock
or stronger on the table.
Before a transaction can acquire an exclusive lock on a row
in a table, it must first acquire an IX
lock on the table.
Table-level lock type compatibility is summarized in the following 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, but not if it conflicts with existing locks. A transaction waits until the conflicting existing lock is released. If a lock request conflicts with an existing lock and cannot be granted because it would cause deadlock, an error occurs.
Intention locks do not block anything except full table requests
(for example, LOCK
TABLES ... WRITE
). The main purpose of intention locks
is to show that someone is locking a row, or going to lock a row
in the table.
Transaction data for an intention lock appears similar to the
following in SHOW
ENGINE INNODB STATUS
and
InnoDB monitor
output:
TABLE LOCK table `test`.`t` trx id 10080 lock mode IX
A record lock is a lock on an index record. For example,
SELECT c1 FROM t WHERE c1 = 10 FOR UPDATE;
prevents any other transaction from inserting, updating, or
deleting rows where the value of t.c1
is
10
.
Record locks always lock index records, even if a table is
defined with no indexes. For such cases,
InnoDB
creates a hidden clustered index and
uses this index for record locking. See
Section 14.8.2.1, “Clustered and Secondary Indexes”.
Transaction data for a record lock appears similar to the
following in SHOW
ENGINE INNODB STATUS
and
InnoDB monitor
output:
RECORD LOCKS space id 58 page no 3 n bits 72 index `PRIMARY` of table `test`.`t` trx id 10078 lock_mode X locks rec but not gap Record lock, heap no 2 PHYSICAL RECORD: n_fields 3; compact format; info bits 0 0: len 4; hex 8000000a; asc ;; 1: len 6; hex 00000000274f; asc 'O;; 2: len 7; hex b60000019d0110; asc ;;
A gap lock is a lock on a gap between index records, or a lock
on the gap before the first or after the last index record. For
example, SELECT c1 FROM t WHERE c1 BETWEEN 10 and 20
FOR UPDATE;
prevents other transactions from inserting
a value of 15
into column
t.c1
, whether or not there was already any
such value in the column, because the gaps between all existing
values in the range are locked.
A gap might span a single index value, multiple index values, or even be empty.
Gap locks are part of the tradeoff between performance and concurrency, and are used in some transaction isolation levels and not others.
Gap locking is not needed for statements that lock rows using a
unique index to search for a unique row. (This does not include
the case that the search condition includes only some columns of
a multiple-column unique index; in that case, gap locking does
occur.) For example, if the id
column has a
unique index, the following statement uses only an index-record
lock for the row having id
value 100 and it
does not matter whether other sessions insert rows in the
preceding gap:
SELECT * FROM child WHERE id = 100;
If id
is not indexed or has a nonunique
index, the statement does lock the preceding gap.
It is also worth noting here that conflicting locks can be held on a gap by different transactions. For example, transaction A can hold a shared gap lock (gap S-lock) on a gap while transaction B holds an exclusive gap lock (gap X-lock) on the same gap. The reason conflicting gap locks are allowed is that if a record is purged from an index, the gap locks held on the record by different transactions must be merged.
Gap locks in InnoDB
are “purely
inhibitive”, which means they only stop other
transactions from inserting to the gap. They do not prevent
different transactions from taking gap locks on the same gap.
Thus, a gap X-lock has the same effect as a gap S-lock.
Gap locking can be disabled explicitly. This occurs if you
change the transaction isolation level to
READ COMMITTED
or enable the
innodb_locks_unsafe_for_binlog
system variable (which is now deprecated). Under these
circumstances, gap locking is disabled for searches and index
scans and is used only for foreign-key constraint checking and
duplicate-key checking.
There are also other effects of using the
READ COMMITTED
isolation
level or enabling
innodb_locks_unsafe_for_binlog
.
Record locks for nonmatching rows are released after MySQL has
evaluated the WHERE
condition. For
UPDATE
statements, InnoDB
does a “semi-consistent” read, such that it returns
the latest committed version to MySQL so that MySQL can
determine whether the row matches the WHERE
condition of the UPDATE
.
A next-key lock is a combination of a record lock on the index record and a gap lock on the gap before the index record.
InnoDB
performs row-level locking in such a
way that when it searches or scans a table index, it sets shared
or exclusive locks on the index records it encounters. Thus, the
row-level locks are actually index-record locks. A next-key lock
on an index record also affects the “gap” before
that index record. That is, a next-key lock is an index-record
lock plus a gap lock on the gap preceding the index record. If
one session has a shared or exclusive lock on record
R
in an index, another session cannot insert
a new index record in the gap immediately before
R
in the index order.
Suppose that an index contains the values 10, 11, 13, and 20. The possible next-key locks for this index cover the following intervals, where a round bracket denotes exclusion of the interval endpoint and a square bracket denotes inclusion of the endpoint:
(negative infinity, 10] (10, 11] (11, 13] (13, 20] (20, positive infinity)
For the last interval, the next-key lock locks the gap above the largest value in the index and the “supremum” pseudo-record having a value higher than any value actually in the index. The supremum is not a real index record, so, in effect, this next-key lock locks only the gap following the largest index value.
By default, InnoDB
operates in
REPEATABLE READ
transaction
isolation level. In this case, InnoDB
uses
next-key locks for searches and index scans, which prevents
phantom rows (see Section 14.5.4, “Phantom Rows”).
Transaction data for a next-key lock appears similar to the
following in SHOW
ENGINE INNODB STATUS
and
InnoDB monitor
output:
RECORD LOCKS space id 58 page no 3 n bits 72 index `PRIMARY` of table `test`.`t` trx id 10080 lock_mode X Record lock, heap no 1 PHYSICAL RECORD: n_fields 1; compact format; info bits 0 0: len 8; hex 73757072656d756d; asc supremum;; Record lock, heap no 2 PHYSICAL RECORD: n_fields 3; compact format; info bits 0 0: len 4; hex 8000000a; asc ;; 1: len 6; hex 00000000274f; asc 'O;; 2: len 7; hex b60000019d0110; asc ;;
An insert intention lock is a type of gap lock set by
INSERT
operations prior to row
insertion. This lock signals the intent to insert in such a way
that multiple transactions inserting into the same index gap
need not wait for each other if they are not inserting at the
same position within the gap. Suppose that there are index
records with values of 4 and 7. Separate transactions that
attempt to insert values of 5 and 6, respectively, each lock the
gap between 4 and 7 with insert intention locks prior to
obtaining the exclusive lock on the inserted row, but do not
block each other because the rows are nonconflicting.
The following example demonstrates a transaction taking an insert intention lock prior to obtaining an exclusive lock on the inserted record. The example involves two clients, A and B.
Client A creates a table containing two index records (90 and 102) and then starts a transaction that places an exclusive lock on index records with an ID greater than 100. The exclusive lock includes a gap lock before record 102:
mysql>CREATE TABLE child (id int(11) NOT NULL, PRIMARY KEY(id)) ENGINE=InnoDB;
mysql>INSERT INTO child (id) values (90),(102);
mysql>START TRANSACTION;
mysql>SELECT * FROM child WHERE id > 100 FOR UPDATE;
+-----+ | id | +-----+ | 102 | +-----+
Client B begins a transaction to insert a record into the gap. The transaction takes an insert intention lock while it waits to obtain an exclusive lock.
mysql>START TRANSACTION;
mysql>INSERT INTO child (id) VALUES (101);
Transaction data for an insert intention lock appears similar to
the following in
SHOW ENGINE INNODB
STATUS
and
InnoDB monitor
output:
RECORD LOCKS space id 31 page no 3 n bits 72 index `PRIMARY` of table `test`.`child`
trx id 8731 lock_mode X locks gap before rec insert intention waiting
Record lock, heap no 3 PHYSICAL RECORD: n_fields 3; compact format; info bits 0
0: len 4; hex 80000066; asc f;;
1: len 6; hex 000000002215; asc " ;;
2: len 7; hex 9000000172011c; asc r ;;...
An AUTO-INC
lock is a special table-level
lock taken by transactions inserting into tables with
AUTO_INCREMENT
columns. In the simplest case,
if one transaction is inserting values into the table, any other
transactions must wait to do their own inserts into that table,
so that rows inserted by the first transaction receive
consecutive primary key values.
The innodb_autoinc_lock_mode
configuration option controls the algorithm used for
auto-increment locking. It allows you to choose how to trade off
between predictable sequences of auto-increment values and
maximum concurrency for insert operations.
For more information, see Section 14.8.1.5, “AUTO_INCREMENT Handling in InnoDB”.
InnoDB
supports SPATIAL
indexing of columns containing spatial columns (see
Section 11.5.8, “Optimizing Spatial Analysis”).
To handle locking for operations involving
SPATIAL
indexes, next-key locking does not
work well to support REPEATABLE
READ
or
SERIALIZABLE
transaction
isolation levels. There is no absolute ordering concept in
multidimensional data, so it is not clear which is the
“next” key.
To enable support of isolation levels for tables with
SPATIAL
indexes, InnoDB
uses predicate locks. A SPATIAL
index
contains minimum bounding rectangle (MBR) values, so
InnoDB
enforces consistent read on the index
by setting a predicate lock on the MBR value used for a query.
Other transactions cannot insert or modify a row that would
match the query condition.
In the InnoDB
transaction model, the goal is to
combine the best properties of a
multi-versioning database with
traditional two-phase locking. InnoDB
performs
locking at the row level and runs queries as nonlocking
consistent reads by
default, in the style of Oracle. The lock information in
InnoDB
is stored space-efficiently so that lock
escalation is not needed. Typically, several users are permitted
to lock every row in InnoDB
tables, or any
random subset of the rows, without causing
InnoDB
memory exhaustion.
Transaction isolation is one of the foundations of database processing. Isolation is the I in the acronym ACID; the isolation level is the setting that fine-tunes the balance between performance and reliability, consistency, and reproducibility of results when multiple transactions are making changes and performing queries at the same time.
InnoDB
offers all four transaction isolation
levels described by the SQL:1992 standard:
READ UNCOMMITTED
,
READ COMMITTED
,
REPEATABLE READ
, and
SERIALIZABLE
. The default
isolation level for InnoDB
is
REPEATABLE READ
.
A user can change the isolation level for a single session or
for all subsequent connections with the SET
TRANSACTION
statement. To set the server's default
isolation level for all connections, use the
--transaction-isolation
option on
the command line or in an option file. For detailed information
about isolation levels and level-setting syntax, see
Section 13.3.6, “SET TRANSACTION Syntax”.
InnoDB
supports each of the transaction
isolation levels described here using different
locking strategies. You can
enforce a high degree of consistency with the default
REPEATABLE READ
level, for
operations on crucial data where
ACID compliance is important.
Or you can relax the consistency rules with
READ COMMITTED
or even
READ UNCOMMITTED
, in
situations such as bulk reporting where precise consistency and
repeatable results are less important than minimizing the amount
of overhead for locking.
SERIALIZABLE
enforces even
stricter rules than REPEATABLE
READ
, and is used mainly in specialized situations,
such as with XA transactions and
for troubleshooting issues with concurrency and
deadlocks.
The following list describes how MySQL supports the different transaction levels. The list goes from the most commonly used level to the least used.
This is the default isolation level for
InnoDB
.
Consistent reads
within the same transaction read the
snapshot established by
the first read. This means that if you issue several plain
(nonlocking) SELECT
statements within the same transaction, these
SELECT
statements are
consistent also with respect to each other. See
Section 14.5.2.3, “Consistent Nonlocking Reads”.
For locking reads
(SELECT
with FOR
UPDATE
or LOCK IN SHARE MODE
),
UPDATE
, and
DELETE
statements, locking
depends on whether the statement uses a unique index with a
unique search condition, or a range-type search condition.
For a unique index with a unique search condition,
InnoDB
locks only the index record
found, not the gap
before it.
For other search conditions, InnoDB
locks the index range scanned, using
gap locks or
next-key locks
to block insertions by other sessions into the gaps
covered by the range. For information about gap locks
and next-key locks, see
Section 14.5.1, “InnoDB Locking”.
Each consistent read, even within the same transaction, sets and reads its own fresh snapshot. For information about consistent reads, see Section 14.5.2.3, “Consistent Nonlocking Reads”.
For locking reads (SELECT
with FOR UPDATE
or LOCK IN SHARE
MODE
), UPDATE
statements, and DELETE
statements, InnoDB
locks only index
records, not the gaps before them, and thus permits the free
insertion of new records next to locked records. Gap locking
is only used for foreign-key constraint checking and
duplicate-key checking.
Because gap locking is disabled, phantom problems may occur, as other sessions can insert new rows into the gaps. For information about phantoms, see Section 14.5.4, “Phantom Rows”.
If you use READ COMMITTED
, you
must use row-based binary logging.
Using READ COMMITTED
has additional
effects:
For UPDATE
or
DELETE
statements,
InnoDB
holds locks only for rows that
it updates or deletes. Record locks for nonmatching rows
are released after MySQL has evaluated the
WHERE
condition. This greatly reduces
the probability of deadlocks, but they can still happen.
For UPDATE
statements, if
a row is already locked, InnoDB
performs a “semi-consistent” read,
returning the latest committed version to MySQL so that
MySQL can determine whether the row matches the
WHERE
condition of the
UPDATE
. If the row
matches (must be updated), MySQL reads the row again and
this time InnoDB
either locks it or
waits for a lock on it.
Consider the following example, beginning with this table:
CREATE TABLE t (a INT NOT NULL, b INT) ENGINE = InnoDB; INSERT INTO t VALUES (1,2),(2,3),(3,2),(4,3),(5,2); COMMIT;
In this case, the table has no indexes, so searches and index scans use the hidden clustered index for record locking (see Section 14.8.2.1, “Clustered and Secondary Indexes”) rather than indexed columns.
Suppose that one session performs an
UPDATE
using these
statements:
# Session A START TRANSACTION; UPDATE t SET b = 5 WHERE b = 3;
Suppose also that a second session performs an
UPDATE
by executing this
statement following those of the first session:
# Session B UPDATE t SET b = 4 WHERE b = 2;
As InnoDB
executes each
UPDATE
, it first acquires an
exclusive lock for each row that it reads, and then
determines whether to modify it. If
InnoDB
does not modify the row,
it releases the lock. Otherwise,
InnoDB
retains the lock until
the end of the transaction. This affects transaction
processing as follows.
When using the default REPEATABLE READ
isolation level, the first
UPDATE
acquires an x-lock on
each row that it reads and does not release any of them:
x-lock(1,2); retain x-lock x-lock(2,3); update(2,3) to (2,5); retain x-lock x-lock(3,2); retain x-lock x-lock(4,3); update(4,3) to (4,5); retain x-lock x-lock(5,2); retain x-lock
The second UPDATE
blocks as
soon as it tries to acquire any locks (because first update
has retained locks on all rows), and does not proceed until
the first UPDATE
commits or
rolls back:
x-lock(1,2); block and wait for first UPDATE to commit or roll back
If READ COMMITTED
is used instead, the
first UPDATE
acquires an
x-lock on each row that it reads and releases those for rows
that it does not modify:
x-lock(1,2); unlock(1,2) x-lock(2,3); update(2,3) to (2,5); retain x-lock x-lock(3,2); unlock(3,2) x-lock(4,3); update(4,3) to (4,5); retain x-lock x-lock(5,2); unlock(5,2)
For the second UPDATE
,
InnoDB
does a
“semi-consistent” read, returning the latest
committed version of each row that it reads to MySQL so that
MySQL can determine whether the row matches the
WHERE
condition of the
UPDATE
:
x-lock(1,2); update(1,2) to (1,4); retain x-lock x-lock(2,3); unlock(2,3) x-lock(3,2); update(3,2) to (3,4); retain x-lock x-lock(4,3); unlock(4,3) x-lock(5,2); update(5,2) to (5,4); retain x-lock
However, if the WHERE
condition includes
an indexed column, and InnoDB
uses the
index, only the indexed column is considered when taking and
retaining record locks. In the following example, the first
UPDATE
takes and retains an
x-lock on each row where b = 2. The second
UPDATE
blocks when it tries
to acquire x-locks on the same records, as it also uses the
index defined on column b.
CREATE TABLE t (a INT NOT NULL, b INT, c INT, INDEX (b)) ENGINE = InnoDB; INSERT INTO t VALUES (1,2,3),(2,2,4); COMMIT; # Session A START TRANSACTION; UPDATE t SET b = 3 WHERE b = 2 AND c = 3; # Session B UPDATE t SET b = 4 WHERE b = 2 AND c = 4;
The effects of using the READ COMMITTED
isolation level are the same as enabling the deprecated
innodb_locks_unsafe_for_binlog
configuration option, with these exceptions:
Enabling
innodb_locks_unsafe_for_binlog
is a global setting and affects all sessions, whereas
the isolation level can be set globally for all
sessions, or individually per session.
innodb_locks_unsafe_for_binlog
can be set only at server startup, whereas the isolation
level can be set at startup or changed at runtime.
READ COMMITTED
therefore offers finer and
more flexible control than
innodb_locks_unsafe_for_binlog
.
SELECT
statements are
performed in a nonlocking fashion, but a possible earlier
version of a row 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
.
This level is like REPEATABLE
READ
, but InnoDB
implicitly
converts all plain SELECT
statements to SELECT
... LOCK IN SHARE MODE
if
autocommit
is disabled. If
autocommit
is enabled, the
SELECT
is its own
transaction. It therefore is known to be read only and can
be serialized if performed as a consistent (nonlocking) read
and need not block for other transactions. (To force a plain
SELECT
to block if other
transactions have modified the selected rows, disable
autocommit
.)
In InnoDB
, all user activity occurs inside a
transaction. If autocommit
mode
is enabled, each SQL statement forms a single transaction on its
own. By default, MySQL starts the session for each new
connection with autocommit
enabled, so MySQL does a commit after each SQL statement if that
statement did not return an error. If a statement returns an
error, the commit or rollback behavior depends on the error. See
Section 14.21.4, “InnoDB Error Handling”.
A session that has autocommit
enabled can perform a multiple-statement transaction by starting
it with an explicit
START
TRANSACTION
or
BEGIN
statement and ending it with a
COMMIT
or
ROLLBACK
statement. See Section 13.3.1, “START TRANSACTION, COMMIT, and ROLLBACK Syntax”.
If autocommit
mode is disabled
within a session with SET autocommit = 0
, the
session always has a transaction open. A
COMMIT
or
ROLLBACK
statement ends the current transaction and a new one starts.
If a session that has
autocommit
disabled ends
without explicitly committing the final transaction, MySQL rolls
back that transaction.
Some statements implicitly end a transaction, as if you had done
a COMMIT
before executing the
statement. For details, see Section 13.3.3, “Statements That Cause an Implicit Commit”.
A COMMIT
means that the changes
made in the current transaction are made permanent and become
visible to other sessions. A
ROLLBACK
statement, on the other hand, cancels all modifications made by
the current transaction. Both
COMMIT
and
ROLLBACK
release all InnoDB
locks that were set during
the current transaction.
By default, connection to the MySQL server begins with autocommit mode enabled, which automatically commits every SQL statement as you execute it. This mode of operation might be unfamiliar if you have experience with other database systems, where it is standard practice to issue a sequence of DML statements and commit them or roll them back all together.
To use multiple-statement
transactions, switch
autocommit off with the SQL statement SET autocommit
= 0
and end each transaction with
COMMIT
or
ROLLBACK
as
appropriate. To leave autocommit on, begin each transaction
with START
TRANSACTION
and end it with
COMMIT
or
ROLLBACK
.
The following example shows two transactions. The first is
committed; the second is rolled back.
shell> mysql test
mysql>CREATE TABLE customer (a INT, b CHAR (20), INDEX (a));
Query OK, 0 rows affected (0.00 sec) mysql>-- Do a transaction with autocommit turned on.
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>-- Do another transaction with autocommit turned off.
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>INSERT INTO customer VALUES (20, 'Paul');
Query OK, 1 row affected (0.00 sec) mysql>DELETE FROM customer WHERE b = 'Heikki';
Query OK, 1 row affected (0.00 sec) mysql>-- Now we undo those last 2 inserts and the delete.
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.
A consistent read
means that InnoDB
uses multi-versioning to
present to a query a snapshot of the database at a point in
time. The query sees the changes made by transactions that
committed before that point of time, and no changes made by
later or uncommitted transactions. The exception to this rule is
that the query sees the changes made by earlier statements
within the same transaction. This exception causes the following
anomaly: If you update some rows in a table, a
SELECT
sees the latest version of
the updated rows, but it might also see older versions of any
rows. If other sessions simultaneously update the same table,
the anomaly means that you might see the table in a state that
never existed in the database.
If the transaction
isolation level is
REPEATABLE READ
(the default
level), all consistent reads within the same transaction read
the snapshot established by the first such read in that
transaction. You can get a fresher snapshot for your queries by
committing the current transaction and after that issuing new
queries.
With READ COMMITTED
isolation
level, each consistent read within a transaction sets and reads
its own fresh snapshot.
Consistent read is the default mode in which
InnoDB
processes
SELECT
statements in
READ COMMITTED
and
REPEATABLE READ
isolation
levels. A consistent read does not set any locks on the tables
it accesses, and therefore other sessions are free to modify
those tables at the same time a consistent read is being
performed on the table.
Suppose that you are running in the default
REPEATABLE READ
isolation
level. When you issue a consistent read (that is, an ordinary
SELECT
statement),
InnoDB
gives your transaction a timepoint
according to which your query sees the database. If another
transaction deletes a row and commits after your timepoint was
assigned, you do not see the row as having been deleted. Inserts
and updates are treated similarly.
The snapshot of the database state applies to
SELECT
statements within a
transaction, not necessarily to
DML statements. If you insert
or modify some rows and then commit that transaction, a
DELETE
or
UPDATE
statement issued from
another concurrent REPEATABLE READ
transaction could affect those just-committed rows, even
though the session could not query them. If a transaction does
update or delete rows committed by a different transaction,
those changes do become visible to the current transaction.
For example, you might encounter a situation like the
following:
SELECT COUNT(c1) FROM t1 WHERE c1 = 'xyz'; -- Returns 0: no rows match. DELETE FROM t1 WHERE c1 = 'xyz'; -- Deletes several rows recently committed by other transaction. SELECT COUNT(c2) FROM t1 WHERE c2 = 'abc'; -- Returns 0: no rows match. UPDATE t1 SET c2 = 'cba' WHERE c2 = 'abc'; -- Affects 10 rows: another txn just committed 10 rows with 'abc' values. SELECT COUNT(c2) FROM t1 WHERE c2 = 'cba'; -- Returns 10: this txn can now see the rows it just updated.
You can advance your timepoint by committing your transaction
and then doing another SELECT
or
START TRANSACTION WITH
CONSISTENT SNAPSHOT
.
This is called multi-versioned concurrency control.
In the following example, session A sees the row inserted by B only when B has committed the insert and A has committed as well, so that the timepoint is advanced past the commit of B.
Session A Session B SET autocommit=0; SET autocommit=0; time | SELECT * FROM t; | empty set | INSERT INTO t VALUES (1, 2); | v SELECT * FROM t; empty set COMMIT; SELECT * FROM t; empty set COMMIT; SELECT * FROM t; --------------------- | 1 | 2 | ---------------------
If you want to see the “freshest” state of the
database, use either the READ
COMMITTED
isolation level or a
locking read:
SELECT * FROM t FOR SHARE;
With READ COMMITTED
isolation
level, each consistent read within a transaction sets and reads
its own fresh snapshot. With LOCK IN SHARE
MODE
, a locking read occurs instead: A
SELECT
blocks until the transaction
containing the freshest rows ends (see
Section 14.5.2.4, “Locking Reads”).
Consistent read does not work over certain DDL statements:
Consistent read does not work over DROP
TABLE
, because MySQL cannot use a table that has
been dropped and InnoDB
destroys the
table.
Consistent read does not work over
ALTER TABLE
, because that
statement makes a temporary copy of the original table and
deletes 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. In this
case, the transaction returns an error:
ER_TABLE_DEF_CHANGED
,
“Table definition has changed, please retry
transaction”.
The type of read varies for selects in clauses like
INSERT INTO ...
SELECT
, UPDATE
... (SELECT)
, and
CREATE TABLE ...
SELECT
that do not specify FOR
UPDATE
or LOCK IN SHARE MODE
:
By default, 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.
To use a consistent read in such cases, enable the
innodb_locks_unsafe_for_binlog
option and set the isolation level of the transaction to
READ UNCOMMITTED
,
READ COMMITTED
, or
REPEATABLE READ
(that is,
anything other than
SERIALIZABLE
). In this
case, no locks are set on rows read from the selected table.
If you query data and then insert or update related data within
the same transaction, the regular SELECT
statement does not give enough protection. Other transactions
can update or delete the same rows you just queried.
InnoDB
supports two types of
locking reads that
offer extra safety:
Sets a shared mode lock on any rows that are read. Other sessions can read the rows, but cannot modify them until your transaction commits. If any of these rows were changed by another transaction that has not yet committed, your query waits until that transaction ends and then uses the latest values.
For index records the search encounters, locks the rows and
any associated index entries, the same as if you issued an
UPDATE
statement for those rows. Other
transactions are blocked from updating those rows, from
doing SELECT ... LOCK IN SHARE MODE
, or
from reading the data in certain transaction isolation
levels. Consistent reads ignore any locks set on the records
that exist in the read view. (Old versions of a record
cannot be locked; they are reconstructed by applying
undo logs on an
in-memory copy of the record.)
These clauses are primarily useful when dealing with tree-structured or graph-structured data, either in a single table or split across multiple tables. You traverse edges or tree branches from one place to another, while reserving the right to come back and change any of these “pointer” values.
All locks set by LOCK IN SHARE MODE
and
FOR UPDATE
queries are released when the
transaction is committed or rolled back.
Locking of rows for update using SELECT FOR
UPDATE
only applies when autocommit is disabled
(either by beginning transaction with
START
TRANSACTION
or by setting
autocommit
to 0. If
autocommit is enabled, the rows matching the specification are
not locked.
Suppose that you want to insert a new row into a table
child
, and make sure that the child row has
a parent row in table parent
. Your
application code can ensure referential integrity throughout
this sequence of operations.
First, use a consistent read to query the table
PARENT
and verify that the parent row
exists. Can you safely insert the child row to table
CHILD
? No, because some other session could
delete the parent row in the moment between your
SELECT
and your INSERT
,
without you being aware of it.
To avoid this potential issue, perform the
SELECT
using LOCK IN
SHARE MODE
:
SELECT * FROM parent WHERE NAME = 'Jones' LOCK IN SHARE MODE;
After the LOCK IN SHARE MODE
query returns
the parent 'Jones'
, you can safely add the
child record to the CHILD
table and commit
the transaction. Any transaction that tries to acquire an
exclusive lock in the applicable row in the
PARENT
table waits until you are finished,
that is, until the data in all tables is in a consistent
state.
For another example, consider an integer counter field in a
table CHILD_CODES
, used to assign a unique
identifier to each child added to table
CHILD
. Do not use either consistent read or
a shared mode read to read the present value of the counter,
because two users of the database could see the same value for
the counter, and a duplicate-key error occurs if two
transactions attempt to add rows with the same identifier to
the CHILD
table.
Here, LOCK IN SHARE MODE
is not a good
solution because if two users read the counter at the same
time, at least one of them ends up in deadlock when it
attempts to update the counter.
To implement reading and incrementing the counter, first
perform a locking read of the counter using FOR
UPDATE
, and then increment the counter. For example:
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.
A locking read, an
UPDATE
, or a
DELETE
generally set record locks
on every index record that is scanned in the processing of the SQL
statement. It does not matter whether there are
WHERE
conditions in the statement that would
exclude the row. InnoDB
does not remember the
exact WHERE
condition, but only knows which
index ranges were scanned. The locks are normally
next-key locks that also
block inserts into the “gap” immediately before the
record. However, gap locking
can be disabled explicitly, which causes next-key locking not to
be used. For more information, see
Section 14.5.1, “InnoDB Locking”. The transaction isolation level
also can affect which locks are set; see
Section 14.5.2.1, “Transaction Isolation Levels”.
If a secondary index is used in a search and index record locks to
be set are exclusive, InnoDB
also retrieves the
corresponding clustered index records and sets locks on them.
Differences between shared and exclusive locks are described in Section 14.5.1, “InnoDB Locking”.
If you have no indexes suitable for your statement and MySQL must scan the entire table to process the statement, every row of the table becomes locked, which in turn blocks all inserts by other users to the table. It is important to create good indexes so that your queries do not unnecessarily scan many rows.
For SELECT ... FOR
UPDATE
or SELECT
... LOCK 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, the
search sets shared next-key locks on the index records it
encounters. However, only an index record lock is required for
statements that lock rows using a unique index to search for a
unique row.
SELECT ... FROM ...
LOCK IN SHARE MODE
sets shared next-key locks on all
index records the search encounters. However, only an index
record lock is required for statements that lock rows using a
unique index to search for a unique row.
SELECT ... FROM ...
FOR UPDATE
sets an exclusive next-key lock on every
record the search encounters. However, only an index record
lock is required for statements that lock rows using a unique
index to search for a unique row.
For index records the search encounters,
SELECT ... FROM ...
FOR UPDATE
blocks other sessions from doing
SELECT ... FROM ...
LOCK IN SHARE MODE
or from reading in certain
transaction isolation levels. Consistent reads ignore any
locks set on the records that exist in the read view.
UPDATE ... WHERE
...
sets an exclusive next-key lock on every record
the search encounters. However, only an index record lock is
required for statements that lock rows using a unique index to
search for a unique row.
When UPDATE
modifies a
clustered index record, implicit locks are taken on affected
secondary index records. The
UPDATE
operation also takes
shared locks on affected secondary index records when
performing duplicate check scans prior to inserting new
secondary index records, and when inserting new secondary
index records.
DELETE FROM ... WHERE
...
sets an exclusive next-key lock on every record
the search encounters. However, only an index record lock is
required for statements that lock rows using a unique index to
search for a unique row.
INSERT
sets an exclusive lock
on the inserted row. This lock is an index-record lock, not a
next-key lock (that is, there is no gap lock) and does not
prevent other sessions from inserting into the gap before the
inserted row.
Prior to inserting the row, a type of gap lock called an insert intention gap lock is set. This lock signals the intent to insert in such a way that multiple transactions inserting into the same index gap need not wait for each other if they are not inserting at the same position within the gap. Suppose that there are index records with values of 4 and 7. Separate transactions that attempt to insert values of 5 and 6 each lock the gap between 4 and 7 with insert intention locks prior to obtaining the exclusive lock on the inserted row, but do not block each other because the rows are nonconflicting.
If a duplicate-key error occurs, a shared lock on the
duplicate index record is set. This use of a shared lock can
result in deadlock should there be multiple sessions trying to
insert the same row if another session already has an
exclusive lock. This can occur if another session deletes the
row. Suppose that an InnoDB
table
t1
has the following structure:
CREATE TABLE t1 (i INT, PRIMARY KEY (i)) ENGINE = InnoDB;
Now suppose that three sessions perform the following operations in order:
Session 1:
START TRANSACTION; INSERT INTO t1 VALUES(1);
Session 2:
START TRANSACTION; INSERT INTO t1 VALUES(1);
Session 3:
START TRANSACTION; INSERT INTO t1 VALUES(1);
Session 1:
ROLLBACK;
The first operation by session 1 acquires an exclusive lock for the row. The operations by sessions 2 and 3 both result in a duplicate-key error and they both request a shared lock for the row. When session 1 rolls back, it releases its exclusive lock on the row and the queued shared lock requests for sessions 2 and 3 are granted. At this point, sessions 2 and 3 deadlock: Neither can acquire an exclusive lock for the row because of the shared lock held by the other.
A similar situation occurs if the table already contains a row with key value 1 and three sessions perform the following operations in order:
Session 1:
START TRANSACTION; DELETE FROM t1 WHERE i = 1;
Session 2:
START TRANSACTION; INSERT INTO t1 VALUES(1);
Session 3:
START TRANSACTION; INSERT INTO t1 VALUES(1);
Session 1:
COMMIT;
The first operation by session 1 acquires an exclusive lock for the row. The operations by sessions 2 and 3 both result in a duplicate-key error and they both request a shared lock for the row. When session 1 commits, it releases its exclusive lock on the row and the queued shared lock requests for sessions 2 and 3 are granted. At this point, sessions 2 and 3 deadlock: Neither can acquire an exclusive lock for the row because of the shared lock held by the other.
INSERT
... ON DUPLICATE KEY UPDATE
differs from a simple
INSERT
in that an exclusive
lock rather than a shared lock is placed on the row to be
updated when a duplicate-key error occurs. An exclusive
index-record lock is taken for a duplicate primary key value.
An exclusive next-key lock is taken for a duplicate unique key
value.
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 to be replaced.
INSERT INTO T SELECT ... FROM S WHERE ...
sets an exclusive index record lock (without a gap lock) on
each row inserted into T
. If the
transaction isolation level is READ
COMMITTED
, or
innodb_locks_unsafe_for_binlog
is enabled and the transaction isolation level is not
SERIALIZABLE
,
InnoDB
does the search on
S
as a consistent read (no locks).
Otherwise, InnoDB
sets shared next-key
locks on rows from S
.
InnoDB
has to set locks in the latter case:
In roll-forward recovery from a backup, every SQL statement
must be executed in exactly the same way it was done
originally.
CREATE TABLE ...
SELECT ...
performs the
SELECT
with shared next-key
locks or as a consistent read, as for
INSERT ...
SELECT
.
When a SELECT
is used in the constructs
REPLACE INTO t SELECT ... FROM s WHERE ...
or UPDATE t ... WHERE col IN (SELECT ... FROM s
...)
, InnoDB
sets shared next-key
locks on rows from table s
.
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 AUTO-INC
table lock mode where the
lock lasts only to the end of the current SQL statement, not
to the end of the entire transaction. Other sessions cannot
insert into the table while the AUTO-INC
table lock is held; see
Section 14.5.2, “InnoDB Transaction Model”.
InnoDB
fetches the value of a previously
initialized AUTO_INCREMENT
column without
setting any locks.
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 in this case the higher MySQL layer
does not know about row-level locks, it is possible to get a
table lock on a table where another session currently has
row-level locks. However, this does not endanger transaction
integrity, as discussed in
Section 14.5.5.2, “Deadlock Detection and Rollback”. See also
Section 14.8.1.7, “Limits on InnoDB Tables”.
The so-called phantom
problem occurs within a transaction when the same query produces
different sets of rows at different times. For example, if a
SELECT
is executed twice, but
returns a row the second time that was not returned the first
time, the row is a “phantom” row.
Suppose that there is an index on the id
column
of the child
table and that you want to read
and lock all rows from the table having an identifier value larger
than 100, with the intention of updating some column in the
selected rows later:
SELECT * FROM child WHERE id > 100 FOR UPDATE;
The query scans the index starting from the first record where
id
is bigger than 100. Let the table contain
rows having id
values of 90 and 102. If the
locks set on the index records in the scanned range do not lock
out inserts made in the gaps (in this case, the gap between 90 and
102), another session can insert a new row into the table with an
id
of 101. If you were to execute the same
SELECT
within the same transaction,
you would see a new row with an id
of 101 (a
“phantom”) in the result set returned by the query.
If we regard a set of rows as a data item, the new phantom child
would violate the isolation principle of transactions that a
transaction should be able to run so that the data it has read
does not change during the transaction.
To prevent phantoms, InnoDB
uses an algorithm
called next-key locking that
combines index-row locking with gap locking.
InnoDB
performs row-level locking in such a way
that when it searches or scans a table index, it sets shared or
exclusive locks on the index records it encounters. Thus, the
row-level locks are actually index-record locks. In addition, a
next-key lock on an index record also affects the
“gap” before that index record. That is, a next-key
lock is an index-record lock plus a gap lock on the gap preceding
the index record. If one session has a shared or exclusive lock on
record R
in an index, another session cannot
insert a new index record in the gap immediately before
R
in the index order.
When InnoDB
scans an index, it can also lock
the gap after the last record in the index. Just that happens in
the preceding example: To prevent any insert into the table where
id
would be bigger than 100, the locks set by
InnoDB
include a lock on the gap following
id
value 102.
You can use next-key locking to implement a uniqueness check in your application: If you read your data in share mode and do not see a duplicate for a row you are going to insert, then you can safely insert your row and know that the next-key lock set on the successor of your row during the read prevents anyone meanwhile inserting a duplicate for your row. Thus, the next-key locking enables you to “lock” the nonexistence of something in your table.
Gap locking can be disabled as discussed in Section 14.5.1, “InnoDB Locking”. This may cause phantom problems because other sessions can insert new rows into the gaps when gap locking is disabled.
A deadlock is a situation where different transactions are unable to proceed because each holds a lock that the other needs. Because both transactions are waiting for a resource to become available, neither ever release the locks it holds.
A deadlock can occur when transactions lock rows in multiple
tables (through statements such as
UPDATE
or
SELECT ... FOR
UPDATE
), but in the opposite order. A deadlock can also
occur when such statements lock ranges of index records and gaps,
with each transaction acquiring some locks but not others due to a
timing issue. For a deadlock example, see
Section 14.5.5.1, “An InnoDB Deadlock Example”.
To reduce the possibility of deadlocks, use transactions rather
than LOCK TABLES
statements; keep
transactions that insert or update data small enough that they do
not stay open for long periods of time; when different
transactions update multiple tables or large ranges of rows, use
the same order of operations (such as
SELECT ... FOR
UPDATE
) in each transaction; create indexes on the
columns used in SELECT ...
FOR UPDATE
and
UPDATE ... WHERE
statements. The possibility of deadlocks is not affected by the
isolation level, because the isolation level changes the behavior
of read operations, while deadlocks occur because of write
operations. For more information about avoiding and recovering
from deadlock conditions, see
Section 14.5.5.3, “How to Minimize and Handle Deadlocks”.
When deadlock detection is enabled (the default) and a deadlock
does occur, InnoDB
detects the condition and
rolls back one of the transactions (the victim). If deadlock
detection is disabled using the
innodb_deadlock_detect
configuration option, InnoDB
relies on the
innodb_lock_wait_timeout
setting
to roll back transactions in case of a deadlock. Thus, even if
your application logic is correct, you must still handle the case
where a transaction must be retried. To see the last deadlock in
an InnoDB
user transaction, use the
SHOW ENGINE INNODB
STATUS
command. If frequent deadlocks highlight a
problem with transaction structure or application error handling,
run with the
innodb_print_all_deadlocks
setting enabled to print information about all deadlocks to the
mysqld error log. For more information about
how deadlocks are automatically detected and handled, see
Section 14.5.5.2, “Deadlock Detection and Rollback”.
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 | +------+
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 one
of the clients and releases its locks. The client returns this
error:
ERROR 1213 (40001): Deadlock found when trying to get lock; try restarting transaction
At that point, the lock request for the other client can be granted and it deletes the row from the table.
When deadlock
detection is enabled (the default),
InnoDB
automatically detects transaction
deadlocks 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. 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.
If a SELECT
calls a stored
function in a transaction, and a statement within the function
fails, that statement rolls back. Furthermore, if
ROLLBACK
is
executed after that, the entire transaction rolls back.
If the LATEST DETECTED DEADLOCK
section of
InnoDB
Monitor output includes a message
stating, “TOO DEEP OR LONG SEARCH IN THE LOCK
TABLE WAITS-FOR GRAPH, WE WILL ROLL BACK FOLLOWING
TRANSACTION,” this indicates that the number
of transactions on the wait-for list has reached a limit of 200.
A wait-for list that exceeds 200 transactions is treated as a
deadlock and the transaction attempting to check the wait-for
list is rolled back. The same error may also occur if the
locking thread must look at more than 1,000,000 locks owned by
transactions on the wait-for list.
For techniques to organize database operations to avoid deadlocks, see Section 14.5.5, “Deadlocks in InnoDB”.
On high concurrency systems, deadlock detection can cause a
slowdown when numerous threads wait for the same lock. At
times, it may be more efficient to disable deadlock detection
and rely on the
innodb_lock_wait_timeout
setting for transaction rollback when a deadlock occurs.
Deadlock detection can be disabled using the
innodb_deadlock_detect
configuration option.
This section builds on the conceptual information about deadlocks in Section 14.5.5.2, “Deadlock Detection and Rollback”. It explains how to organize database operations to minimize deadlocks and the subsequent error handling required in applications.
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:
At any time, issue the
SHOW ENGINE
INNODB STATUS
command to determine the cause of
the most recent deadlock. That can help you to tune your
application to avoid deadlocks.
If frequent deadlock warnings cause concern, collect more
extensive debugging information by enabling the
innodb_print_all_deadlocks
configuration option. Information about each deadlock, not
just the latest one, is recorded in the MySQL
error log. Disable
this option when you are finished debugging.
Always be prepared to re-issue a transaction if it fails due to deadlock. Deadlocks are not dangerous. Just try again.
Keep transactions small and short in duration to make them less prone to collision.
Commit transactions immediately after making a set of related changes to make them less prone to collision. In particular, do not leave an interactive mysql session open for a long time with an uncommitted transaction.
If you use locking
reads (SELECT
... FOR UPDATE
or
SELECT ... LOCK IN SHARE
MODE
), try using a lower isolation level such as
READ COMMITTED
.
When modifying multiple tables within a transaction, or
different sets of rows in the same table, do those
operations in a consistent order each time. Then
transactions form well-defined queues and do not deadlock.
For example, organize database operations into functions
within your application, or call stored routines, rather
than coding multiple similar sequences of
INSERT
, UPDATE
, and
DELETE
statements in different places.
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 permit 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.
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 begin a transaction with SET
autocommit = 0
(not
START
TRANSACTION
) followed by LOCK
TABLES
, and to not call
UNLOCK
TABLES
until 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 prevent concurrent updates to the table, avoiding deadlocks at the expense of less responsiveness for a busy system.
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.
This section provides configuration information and procedures for
InnoDB
initialization, startup, and various
components and features of the InnoDB
storage
engine. For information about optimizing database operations for
InnoDB
tables, see
Section 8.5, “Optimizing for InnoDB Tables”.
The first decisions to make about InnoDB
configuration involve the configuration of data files, log files,
page size, and memory buffers. It is recommended that you define
data file, log file, and page size configuration before creating
the InnoDB
instance. Modifying data file or log
file configuration after the InnoDB
instance is
created may involve a non-trivial procedure, and page size can
only be defined when the InnoDB
instance is
first initialized.
In addition to these topics, this section provides information
about specifying InnoDB
options in a
configuration file, viewing InnoDB
initialization information, and important storage considerations.
Because MySQL uses data file, log file, and page size
configuration settings to initialize the
InnoDB
instance, it is recommended that you
define these settings in a configuration file that MySQL reads
at startup, prior to initializing InnoDB
for
the first time. InnoDB
is initialized when
the MySQL server is started, and the first initialization of
InnoDB
normally occurs the first time you
start the MySQL server.
You can place InnoDB
options in the
[mysqld]
group of any option file that your
server reads when it starts. The locations of MySQL option files
are described in Section 4.2.6, “Using Option Files”.
To make sure that mysqld reads options only
from a specific file, use the
--defaults-file
option as the
first option on the command line when starting the server:
mysqld --defaults-file=path_to_configuration_file
To view InnoDB
initialization information
during startup, start mysqld from a command
prompt. When mysqld is started from a command
prompt, initialization information is printed to the console.
For example, on Windows, if mysqld is located
in C:\Program Files\MySQL\MySQL Server
5.7\bin
, start the MySQL server like
this:
C:\> "C:\Program Files\MySQL\MySQL Server 5.7\bin\mysqld" --console
On Unix-like systems, mysqld is located in
the bin
directory of your MySQL
installation:
shell> bin/mysqld --user=mysql &
If you do not send server output to the console, check the error
log after startup to see the initialization information
InnoDB
printed during the startup process.
For information about starting MySQL using other methods, see Section 2.10.5, “Starting and Stopping MySQL Automatically”.
InnoDB
does not open all user tables and
associated data files at startup. However,
InnoDB
does check for the existence of
tablespace files (*.ibd
files) that are
referenced in the data dictionary. If a tablespace file is not
found, InnoDB
logs an error and continues
the startup sequence. Tablespace files that are referenced in
the redo log may be opened during crash recovery for redo
application.
Review the following storage-related considerations before proceeding with your startup configuration.
In some cases, database performance improves if the data is
not all placed on the same physical disk. Putting log files
on a different disk from data is very often beneficial for
performance. For example, you can place system tablespace
data files and log files on different disks. You can also
use raw disk partitions (raw devices) for
InnoDB
data files, which may speed up
I/O. See Section 14.7.3, “Using Raw Disk Partitions for the System Tablespace”.
InnoDB
is a transaction-safe (ACID
compliant) storage engine for MySQL that has commit,
rollback, and crash-recovery capabilities to protect user
data. 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
fsync()
system call that should wait
until all unwritten data for a file has been flushed 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, perform some “pull-the-plug”
tests before using anything in production. On OS X 10.3 and
higher, InnoDB
uses a special
fcntl()
file flush method. Under Linux,
it is advisable to disable the
write-back cache.
On ATA/SATA disk drives, 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.
With regard to InnoDB
recovery
capabilities that protect user data,
InnoDB
uses a file flush technique
involving a structure called the
doublewrite
buffer, which is enabled by default
(innodb_doublewrite=ON
).
The doublewrite buffer adds safety to recovery following a
crash or power outage, and improves performance on most
varieties of Unix by reducing the need for
fsync()
operations. It is recommended
that the innodb_doublewrite
option remains enabled if you are concerned with data
integrity or possible failures. For additional information
about the doublewrite buffer, see
Section 14.12.1, “InnoDB Disk I/O”.
Before using NFS with InnoDB
, review
potential issues outlined in
Using NFS with MySQL.
Running MySQL server on a 4K sector hard drive on Windows is
not supported with
innodb_flush_method=async_unbuffered
,
which is the default setting. The workaround is to use
innodb_flush_method=normal
.
The innodb_data_file_path
configuration option defines the name, size, and attributes of
InnoDB
system tablespace data files. If you
do not specify a value for
innodb_data_file_path
, the default behavior
is to create a single auto-extending data file, slightly larger
than 12MB, named ibdata1
.
To specify more than one data file, separate them by semicolon
(;
) characters:
innodb_data_file_path=datafile_spec1
[;datafile_spec2
]...
The following setting configures a single 12MB 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:
[mysqld] innodb_data_file_path=ibdata1:12M:autoextend
File size is specified using K
,
M
, or G
suffix letters to
indicate units of KB, MB, or GB. If specifying the data file
size in kilobytes (KB), do so in multiples of 1024. Otherwise,
KB values are rounded to nearest megabyte (MB) boundary. The sum
of the sizes of the files must be at least slightly larger than
12MB.
A minimum file size is enforced for the first system tablespace data file to ensure that there is enough space for doublewrite buffer pages:
For an innodb_page_size
value of 16KB or less, the minimum file size is 3MB.
For an innodb_page_size
value of 32KB, the minimum file size is 6MB.
For an innodb_page_size
value of 64KB, the minimum file size is 12MB.
A system tablespace with a fixed-size 50MB data file named
ibdata1
and a 50MB auto-extending file
named ibdata2
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 file
name, file size, and optional autoextend
and
max
attributes:
file_name
:file_size
[:autoextend[:max:max_file_size
]]
The autoextend
and max
attributes can be used only for the data file that is specified
last in the
innodb_data_file_path
setting.
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
autoextend
increment is 64MB at a time by
default. To modify the increment, change the
innodb_autoextend_increment
system variable.
If the disk becomes full, you might want to add another data file on another disk. For instructions, see Section 14.7.1, “Resizing the InnoDB System Tablespace”.
The size limit of individual files is determined by your operating system. You can set the file size to more than 4GB on operating systems that support large files. You can also use raw disk partitions as data files.
InnoDB
is not aware of the file system
maximum file size, so be cautious on file systems 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 following the
autoextend
attribute. Use the
max
attribute only in cases where
constraining disk usage is of critical importance, because
exceeding the maximum size causes a fatal error, possibly
causing the server to exit. The following configuration permits
ibdata1
to grow to a limit of 500MB:
[mysqld] innodb_data_file_path=ibdata1:12M:autoextend:max:500M
InnoDB
creates system tablespace files in the
MySQL data directory by default
(datadir
). To specify a
location explicitly, use the
innodb_data_home_dir
option.
For example, to create two files named
ibdata1
and ibdata2
in
a directory named myibdata
, configure
InnoDB
like this:
[mysqld] innodb_data_home_dir = /path/to/myibdata/ innodb_data_file_path=ibdata1:50M;ibdata2:50M:autoextend
A trailing slash is required when specifying a value for
innodb_data_home_dir
.
InnoDB
does not create directories, so make
sure that the myibdata
directory exists
before you start the server. Use the Unix or DOS
mkdir
command to create directories.
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.
InnoDB
forms the directory path for each data
file by textually concatenating the value of
innodb_data_home_dir
to the
data file name. If the
innodb_data_home_dir
option is
not specified, 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 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=/path/to/myibdata/ibdata1:50M;/path/to/myibdata/ibdata2:50M:autoextend
By default, InnoDB
creates two 48MB log files
in the MySQL data directory
(datadir
) named
ib_logfile0
and
ib_logfile1
.
The following options can be used to modify the default configuration:
innodb_log_group_home_dir
defines directory path to the InnoDB
log
files (the redo logs). If this option is not configured,
InnoDB
log files are created in the MySQL
data directory (datadir
).
You might use this option to place InnoDB
log files in a different physical storage location than
InnoDB
data files to avoid potential I/O
resource conflicts. For example:
[mysqld] innodb_log_group_home_dir = /dr3/iblogs
InnoDB
does not create directories, so
make sure that the log directory exists before you start
the server. Use the Unix or DOS mkdir
command to create any necessary directories.
Make sure that the MySQL server has the proper access rights to create files in the log directory. More generally, the server must have access rights in any directory where it needs to create log files.
innodb_log_files_in_group
defines the number of log files in the log group. The
default and recommended value is 2.
innodb_log_file_size
defines the size in bytes of each log file in the log group.
The combined size of log files
(innodb_log_file_size
*
innodb_log_files_in_group
)
cannot exceed a maximum value that is slightly less than
512GB. A pair of 255 GB log files, for example, approaches
the limit but does not exceed it. The default log file size
is 48MB. Generally, the combined size of the log files
should be large enough that the server can smooth out peaks
and troughs in workload activity, which often means that
there is enough redo log space to handle more than an hour
of write activity. The larger the value, the less checkpoint
flush activity is needed in the buffer pool, saving disk
I/O. For additional information, see
Section 8.5.4, “Optimizing InnoDB Redo Logging”.
By default, InnoDB
undo logs are part of the
system tablespace. However, you can choose to store
InnoDB
undo logs in one or more separate undo
tablespaces, typically on a different storage device.
The innodb_undo_directory
configuration option defines the path where
InnoDB
creates separate tablespaces for the
undo logs. This option is typically used in conjunction with the
innodb_rollback_segments
and
innodb_undo_tablespaces
options, which determine the disk layout of the undo logs
outside the system tablespace.
innodb_undo_tablespaces
is
deprecated and will be removed in a future release.
For more information, see Section 14.7.7, “Configuring Undo Tablespaces”.
By default, InnoDB
creates a single
auto-extending temporary tablespace data file named
ibtmp1
that is slightly larger than 12MB in
the innodb_data_home_dir
directory. The default temporary tablespace data file
configuration can be modified at startup using the
innodb_temp_data_file_path
configuration option.
The innodb_temp_data_file_path
option specifies the path, file name, and file size for
InnoDB
temporary tablespace data files. The
full directory path for a file is formed by concatenating
innodb_data_home_dir
to the
path specified by
innodb_temp_data_file_path
.
File size is specified in KB, MB, or GB (1024MB) by appending K,
M, or G to the size value. The sum of the sizes of the files
must be slightly larger than 12MB.
The innodb_data_home_dir
default value is the MySQL data directory
(datadir
).
The innodb_page_size
option
specifies the page size for all InnoDB
tablespaces in a MySQL instance. This value is set when the
instance is created and remains constant afterward. Valid values
are 64k, 32k, 16k (the default), 8k, and 4k. Alternatively, you
can specify page size in bytes (65536, 32768, 16384, 8192,
4096).
The default page size of 16k is appropriate for a wide range of
workloads, particularly for queries involving table scans and
DML operations involving bulk updates. Smaller page sizes might
be more efficient for OLTP workloads involving many small
writes, where contention can be an issue when a single page
contains many rows. Smaller pages might also be efficient with
SSD storage devices, which typically use small block sizes.
Keeping the InnoDB
page size close to the
storage device block size minimizes the amount of unchanged data
that is rewritten to disk.
MySQL allocates memory to various caches and buffers to improve
performance of database operations. When allocating memory for
InnoDB
, always consider memory required by
the operating system, memory allocated to other applications,
and memory allocated for other MySQL buffers and caches. For
example, if you use MyISAM
tables, consider
the amount of memory allocated for the key buffer
(key_buffer_size
). For an
overview of MySQL buffers and caches, see
Section 8.12.4.1, “How MySQL Uses Memory”.
Buffers specific to InnoDB
are configured
using the following parameters:
innodb_buffer_pool_size
defines size of the buffer pool, which is the memory area
that holds cached data for InnoDB
tables,
indexes, and other auxiliary buffers. The size of the buffer
pool is important for system performance, and it is
typically recommended that
innodb_buffer_pool_size
is
configured to 50 to 75 percent of system memory. The default
buffer pool size is 128MB. For additional guidance, see
Section 8.12.4.1, “How MySQL Uses Memory”. For information about how to
configure InnoDB
buffer pool size, see
Section 14.6.3.2, “Configuring InnoDB Buffer Pool Size”. Buffer pool
size can be configured at startup or dynamically.
On systems with a large amount of memory, you can improve
concurrency by dividing the buffer pool into multiple buffer
pool instances. The number of buffer pool instances is
controlled by the by
innodb_buffer_pool_instances
option. By default, InnoDB
creates one
buffer pool instance. The number of buffer pool instances
can be configured at startup. For more information, see
Section 14.6.3.3, “Configuring Multiple Buffer Pool Instances”.
innodb_log_buffer_size
defines the size in bytes of the buffer that
InnoDB
uses to write to the log files on
disk. The default size is 16MB. A large log buffer enables
large transactions to run without a need to write the log to
disk before the transactions commit. If you have
transactions that update, insert, or delete many rows, you
might consider increasing the size of the log buffer to save
disk I/O.
innodb_log_buffer_size
can
be configured at startup. For related information, see
Section 8.5.4, “Optimizing InnoDB Redo Logging”.
On 32-bit GNU/Linux x86, be careful not to set memory usage
too high. glibc
may permit the process heap
to grow over thread stacks, which crashes your server. It is a
risk if the memory allocated to the mysqld
process for global and per-thread buffers and caches is close
to or exceeds 2GB.
A formula similar to the following that calculates global and per-thread memory allocation for MySQL can be used to estimate MySQL memory usage. You may need to modify the formula to account for buffers and caches in your MySQL version and configuration. For an overview of MySQL buffers and caches, see Section 8.12.4.1, “How MySQL Uses Memory”.
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
binaries provided by Oracle Corporation.) and in the worst
case also uses sort_buffer_size +
read_buffer_size
additional memory.
On Linux, if the kernel is enabled for large page support,
InnoDB
can use large pages to allocate memory
for its buffer pool. See Section 8.12.4.2, “Enabling Large Page Support”.
You can now query InnoDB
tables where the MySQL
data directory is on read-only media, by enabling the
--innodb-read-only
configuration
option at server startup.
To prepare an instance for read-only operation, make sure all the
necessary information is flushed
to the data files before storing it on the read-only medium. Run
the server with change buffering disabled
(innodb_change_buffering=0
) and
do a slow shutdown.
To enable read-only mode for an entire MySQL instance, specify the following configuration options at server startup:
If the instance is on read-only media such as a DVD or CD, or
the /var
directory is not writeable by
all:
--pid-file=
and path_on_writeable_media
--event-scheduler=disabled
--innodb_temp_data_file_path
.
This option specifies the path, file name, and file size for
InnoDB
temporary tablespace data files. The
default setting is ibtmp1:12M:autoextend
,
which creates the ibtmp1
temporary
tablespace data file in the data directory. To prepare an
instance for read-only operation, set
innodb_temp_data_file_path
to
a location outside of the data directory. The path must be
relative to the data directory; for example:
--innodb_temp_data_file_path=../../../tmp/ibtmp1:12M:autoextend
This mode of operation is appropriate in situations such as:
Distributing a MySQL application, or a set of MySQL data, on a read-only storage medium such as a DVD or CD.
Multiple MySQL instances querying the same data directory simultaneously, typically in a data warehousing configuration. You might use this technique to avoid bottlenecks that can occur with a heavily loaded MySQL instance, or you might use different configuration options for the various instances to tune each one for particular kinds of queries.
Querying data that has been put into a read-only state for security or data integrity reasons, such as archived backup data.
This feature is mainly intended for flexibility in distribution and deployment, rather than raw performance based on the read-only aspect. See Section 8.5.3, “Optimizing InnoDB Read-Only Transactions” for ways to tune the performance of read-only queries, which do not require making the entire server read-only.
When the server is run in read-only mode through the
--innodb-read-only
option,
certain InnoDB
features and components are
reduced or turned off entirely:
No change
buffering is done, in particular no merges from the
change buffer. To make sure the change buffer is empty when
you prepare the instance for read-only operation, disable
change buffering
(innodb_change_buffering=0
)
and do a slow
shutdown first.
There is no crash recovery phase at startup. The instance must have performed a slow shutdown before being put into the read-only state.
Because the redo log is
not used in read-only operation, you can set
innodb_log_file_size
to the
smallest size possible (1 MB) before making the instance
read-only.
All background threads other than I/O read threads are turned off. As a consequence, a read-only instance cannot encounter any deadlocks.
Information about deadlocks, monitor output, and so on is not
written to temporary files. As a consequence,
SHOW ENGINE
INNODB STATUS
does not produce any output.
If the MySQL server is started with
--innodb-read-only
but the
data directory is still on writeable media, the root user can
still perform DCL operations
such as GRANT
and
REVOKE
.
Changes to configuration option settings that would normally change the behavior of write operations, have no effect when the server is in read-only mode.
The MVCC processing to enforce isolation levels is turned off. All queries read the latest version of a record, because update and deletes are not possible.
The undo log is not used.
Disable any settings for the
innodb_undo_tablespaces
and
innodb_undo_directory
configuration options.
This section provides configuration and tuning information for the
InnoDB
buffer pool.
InnoDB
maintains a storage area
called the buffer pool
for caching data and indexes in memory. Knowing how the
InnoDB
buffer pool works, and taking
advantage of it to keep frequently accessed data in memory, is
an important aspect of MySQL tuning. For information about how
the InnoDB
buffer pool works, see
InnoDB Buffer Pool LRU Algorithm.
You can configure the various aspects of the
InnoDB
buffer pool to improve performance.
Ideally, you set the size of the buffer pool to as large a
value as practical, leaving enough memory for other
processes on the server to run without excessive paging. The
larger the buffer pool, the more InnoDB
acts like an in-memory database, reading data from disk once
and then accessing the data from memory during subsequent
reads. See Section 14.6.3.2, “Configuring InnoDB Buffer Pool Size”.
With 64-bit systems with large memory sizes, you can split the buffer pool into multiple parts, to minimize contention for the memory structures among concurrent operations. For details, see Section 14.6.3.3, “Configuring Multiple Buffer Pool Instances”.
You can keep frequently accessed data in memory despite sudden spikes of activity for operations such as backups or reporting. For details, see Section 14.6.3.4, “Making the Buffer Pool Scan Resistant”.
You can control when and how InnoDB
performs read-ahead requests to prefetch pages into the
buffer pool asynchronously, in anticipation that the pages
will be needed soon. For details, see
Section 14.6.3.5, “Configuring InnoDB Buffer Pool Prefetching (Read-Ahead)”.
You can control when background flushing of dirty pages
occurs and whether or not InnoDB
dynamically adjusts the rate of flushing based on workload.
For details, see
Section 14.6.3.6, “Configuring InnoDB Buffer Pool Flushing”.
You can fine-tune aspects of InnoDB
buffer pool flushing behavior to improve performance. For
details, see
Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing”.
You can configure how InnoDB
preserves
the current buffer pool state to avoid a lengthy warmup
period after a server restart. You can also save the current
buffer pool state while the server is running. For details,
see Section 14.6.3.8, “Saving and Restoring the Buffer Pool State”.
InnoDB
manages the buffer pool as a list,
using a variation of the least recently used (LRU) algorithm.
When room is needed to add a new page to the pool,
InnoDB
evicts the least recently used page
and adds the new page to the middle of the list. This
“midpoint insertion strategy” treats the list as
two sublists:
At the head, a sublist of “new” (or “young”) pages that were accessed recently.
At the tail, a sublist of “old” pages that were accessed less recently.
This algorithm keeps pages that are heavily used by queries in the new sublist. The old sublist contains less-used pages; these pages are candidates for eviction.
The LRU algorithm operates as follows by default:
3/8 of the buffer pool is devoted to the old sublist.
The midpoint of the list is the boundary where the tail of the new sublist meets the head of the old sublist.
When InnoDB
reads a page into the
buffer pool, it initially inserts it at the midpoint (the
head of the old sublist). A page can be read in because it
is required for a user-specified operation such as an SQL
query, or as part of a
read-ahead
operation performed automatically by
InnoDB
.
Accessing a page in the old sublist makes it “young”, moving it to the head of the buffer pool (the head of the new sublist). If the page was read in because it was required, the first access occurs immediately and the page is made young. If the page was read in due to read-ahead, the first access does not occur immediately (and might not occur at all before the page is evicted).
As the database operates, pages in the buffer pool that are not accessed “age” by moving toward the tail of the list. Pages in both the new and old sublists age as other pages are made new. Pages in the old sublist also age as pages are inserted at the midpoint. Eventually, a page that remains unused for long enough reaches the tail of the old sublist and is evicted.
By default, pages read by queries immediately move into the
new sublist, meaning they stay in the buffer pool longer. A
table scan (such as performed for a
mysqldump operation, or a
SELECT
statement with no
WHERE
clause) can bring a large amount of
data into the buffer pool and evict an equivalent amount of
older data, even if the new data is never used again.
Similarly, pages that are loaded by the read-ahead background
thread and then accessed only once move to the head of the new
list. These situations can push frequently used pages to the
old sublist, where they become subject to eviction. For
information about optimizing this behavior, see
Section 14.6.3.4, “Making the Buffer Pool Scan Resistant”, and
Section 14.6.3.5, “Configuring InnoDB Buffer Pool Prefetching (Read-Ahead)”.
InnoDB
Standard Monitor output contains
several fields in the BUFFER POOL AND
MEMORY
section that pertain to operation of the
buffer pool LRU algorithm. For details, see
Section 14.6.3.9, “Monitoring the Buffer Pool Using the InnoDB Standard Monitor”.
Several configuration options affect different aspects of the
InnoDB
buffer pool.
Specifies the size of the buffer pool. If the buffer pool
is small and you have sufficient memory, making the buffer
pool larger can improve performance by reducing the amount
of disk I/O needed as queries access
InnoDB
tables. The
innodb_buffer_pool_size
option is dynamic, which allows you to configure buffer
pool size without restarting the server. See
Section 14.6.3.2, “Configuring InnoDB Buffer Pool Size” for more
information.
innodb_buffer_pool_chunk_size
Defines the chunk size for InnoDB
buffer pool resizing operations. See
Section 14.6.3.2, “Configuring InnoDB Buffer Pool Size” for more
information.
Divides the buffer pool into a user-specified number of
separate regions, each with its own LRU list and related
data structures, to reduce contention during concurrent
memory read and write operations. This option only takes
effect when you set
innodb_buffer_pool_size
to a value of 1GB or more. The total size you specify is
divided among all the buffer pools. For best efficiency,
specify a combination of
innodb_buffer_pool_instances
and
innodb_buffer_pool_size
so that each buffer pool instance is at least 1 gigabyte.
See Section 14.6.3.3, “Configuring Multiple Buffer Pool Instances” for
more information.
Specifies the approximate percentage of the buffer pool
that InnoDB
uses for the old block
sublist. The range of values is 5 to 95. The default value
is 37 (that is, 3/8 of the pool). See
Section 14.6.3.4, “Making the Buffer Pool Scan Resistant”
for more information.
Specifies how long in milliseconds (ms) a page inserted into the old sublist must stay there after its first access before it can be moved to the new sublist. If the value is 0, a page inserted into the old sublist moves immediately to the new sublist the first time it is accessed, no matter how soon after insertion the access occurs. If the value is greater than 0, pages remain in the old sublist until an access occurs at least that many milliseconds after the first access. For example, a value of 1000 causes pages to stay in the old sublist for 1 second after the first access before they become eligible to move to the new sublist.
Setting
innodb_old_blocks_time
greater than 0 prevents one-time table scans from flooding
the new sublist with pages used only for the scan. Rows in
a page read in for a scan are accessed many times in rapid
succession, but the page is unused after that. If
innodb_old_blocks_time
is
set to a value greater than time to process the page, the
page remains in the “old” sublist and ages to
the tail of the list to be evicted quickly. This way,
pages used only for a one-time scan do not act to the
detriment of heavily used pages in the new sublist.
innodb_old_blocks_time
can be set at runtime, so you can change it temporarily
while performing operations such as table scans and dumps:
SET GLOBAL innodb_old_blocks_time = 1000;
... perform queries that scan tables ...
SET GLOBAL innodb_old_blocks_time = 0;
This strategy does not apply if your intent is to
“warm up” the buffer pool by filling it with
a table's content. For example, benchmark tests often
perform a table or index scan at server startup, because
that data would normally be in the buffer pool after a
period of normal use. In this case, leave
innodb_old_blocks_time
set to 0, at least until the warmup phase is complete.
See Section 14.6.3.4, “Making the Buffer Pool Scan Resistant” for more information.
Controls the sensitivity of linear
read-ahead that
InnoDB
uses to prefetch pages into the
buffer pool.
See Section 14.6.3.5, “Configuring InnoDB Buffer Pool Prefetching (Read-Ahead)” for more information.
Enables random
read-ahead
technique for prefetching pages into the buffer pool.
Random read-ahead is a technique that predicts when pages
might be needed soon based on pages already in the buffer
pool, regardless of the order in which those pages were
read.
innodb_random_read_ahead
is disabled by default.
See Section 14.6.3.5, “Configuring InnoDB Buffer Pool Prefetching (Read-Ahead)” for more information.
Specifies whether to dynamically adjust the rate of flushing dirty pages in the buffer pool based on workload. Adjusting the flush rate dynamically is intended to avoid bursts of I/O activity. This setting is enabled by default.
See Section 14.6.3.6, “Configuring InnoDB Buffer Pool Flushing” for more information.
Low water mark representing percentage of redo log capacity at which adaptive flushing is enabled.
See Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing” for more information.
Specifies whether flushing a page from the buffer pool also flushes other dirty pages in the same extent.
See Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing” for more information.
Number of iterations for which InnoDB keeps the previously calculated snapshot of the flushing state, controlling how quickly adaptive flushing responds to changing workloads.
See Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing” for more information.
A parameter that influences the algorithms and heuristics
for the flush operation
for the buffer pool. Primarily of interest to performance
experts tuning I/O-intensive workloads. It specifies, per
buffer pool instance, how far down the buffer pool LRU
list the page_cleaner
thread scans
looking for dirty
pages to flush.
See Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing” for more information.
InnoDB
tries to
flush data from the
buffer pool so that the percentage of
dirty pages does
not exceed this value. Specify an integer in the range
from 0 to 99. The default value is 75.
See Section 14.6.3.6, “Configuring InnoDB Buffer Pool Flushing” for more information.
innodb_max_dirty_pages_pct_lwm
Low water mark representing percentage of dirty pages where preflushing is enabled to control the dirty page ratio. The default of 0 disables the pre-flushing behavior entirely.
See Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing” for more information.
Specifies the name of the file that holds the list of
tablespace IDs and page IDs produced by
innodb_buffer_pool_dump_at_shutdown
or
innodb_buffer_pool_dump_now
.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
innodb_buffer_pool_dump_at_shutdown
Specifies whether to record the pages cached in the buffer pool when the MySQL server is shut down, to shorten the warmup process at the next restart.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
innodb_buffer_pool_load_at_startup
Specifies that, on MySQL server startup, the buffer pool
is automatically warmed
up by loading the same pages it held at an earlier
time. Typically used in combination with
innodb_buffer_pool_dump_at_shutdown
.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
Immediately records the pages cached in the buffer pool.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
Immediately warms up
the buffer pool by loading a set of data pages, without
waiting for a server restart. Can be useful to bring cache
memory back to a known state during benchmarking, or to
ready the MySQL server to resume its normal workload after
running queries for reports or maintenance. Typically used
with
innodb_buffer_pool_dump_now
.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
Specifies the percentage of the most recently used pages for each buffer pool to read out and dump. The range is 1 to 100.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
Interrupts the process of restoring buffer pool contents
triggered by
innodb_buffer_pool_load_at_startup
or
innodb_buffer_pool_load_now
.
See Section 14.6.3.8, “Saving and Restoring the Buffer Pool State” for more information.
You can configure InnoDB
buffer pool size
offline (at startup) or online, while the server is running.
Behavior described in this section applies to both methods. For
additional information about configuring buffer pool size
online, see Configuring InnoDB Buffer Pool Size Online.
When increasing or decreasing
innodb_buffer_pool_size
, the
operation is performed in chunks. Chunk size is defined by the
innodb_buffer_pool_chunk_size
configuration option, which has a default of
128M
. For more information, see
Configuring InnoDB Buffer Pool Chunk Size.
Buffer pool size must always be equal to or a multiple of
innodb_buffer_pool_chunk_size
*
innodb_buffer_pool_instances
.
If you configure
innodb_buffer_pool_size
to a
value that is not equal to or a multiple of
innodb_buffer_pool_chunk_size
*
innodb_buffer_pool_instances
,
buffer pool size is automatically adjusted to a value that is
equal to or a multiple of
innodb_buffer_pool_chunk_size
*
innodb_buffer_pool_instances
that is not less than the specified buffer pool size.
In the following example,
innodb_buffer_pool_size
is set
to 8G
, and
innodb_buffer_pool_instances
is
set to 16
.
innodb_buffer_pool_chunk_size
is 128M
, which is the default value.
8G
is a valid
innodb_buffer_pool_size
value
because 8G
is a multiple of
innodb_buffer_pool_instances=16
*
innodb_buffer_pool_chunk_size=128M
,
which is 2G
.
shell> mysqld --innodb_buffer_pool_size=8G --innodb_buffer_pool_instances=16
mysql> SELECT @@innodb_buffer_pool_size/1024/1024/1024;
+------------------------------------------+
| @@innodb_buffer_pool_size/1024/1024/1024 |
+------------------------------------------+
| 8.000000000000 |
+------------------------------------------+
In this example,
innodb_buffer_pool_size
is set
to 9G
, and
innodb_buffer_pool_instances
is
set to 16
.
innodb_buffer_pool_chunk_size
is 128M
, which is the default value. In this
case, 9G
is not a multiple of
innodb_buffer_pool_instances=16
*
innodb_buffer_pool_chunk_size=128M
,
so innodb_buffer_pool_size
is
adjusted to 10G
, which is the next multiple
of
innodb_buffer_pool_chunk_size
*
innodb_buffer_pool_instances
that is not less than the specified buffer pool size.
shell> mysqld --innodb_buffer_pool_size=9G --innodb_buffer_pool_instances=16
mysql> SELECT @@innodb_buffer_pool_size/1024/1024/1024;
+------------------------------------------+
| @@innodb_buffer_pool_size/1024/1024/1024 |
+------------------------------------------+
| 10.000000000000 |
+------------------------------------------+
innodb_buffer_pool_chunk_size
can be increased or decreased in 1MB (1048576 byte) units but
can only be modified at startup, in a command line string or
in a MySQL configuration file.
Command line:
shell> mysqld --innodb_buffer_pool_chunk_size=134217728
Configuration file:
[mysqld] innodb_buffer_pool_chunk_size=134217728
The following conditions apply when altering
innodb_buffer_pool_chunk_size
:
If the new
innodb_buffer_pool_chunk_size
value *
innodb_buffer_pool_instances
is larger than the current buffer pool size when the
buffer pool is initialized,
innodb_buffer_pool_chunk_size
is truncated to
innodb_buffer_pool_size
/
innodb_buffer_pool_instances
.
For example, if the buffer pool is initialized with a size
of 2GB
(2147483648 bytes),
4
buffer pool instances, and a chunk
size of 1GB
(1073741824 bytes), chunk
size is truncated to a value equal to
innodb_buffer_pool_size
/
innodb_buffer_pool_instances
,
as shown below:
shell>mysqld --innodb_buffer_pool_size=2147483648 --innodb_buffer_pool_instances=4
--innodb_buffer_pool_chunk_size=1073741824;
mysql>SELECT @@innodb_buffer_pool_size;
+---------------------------+ | @@innodb_buffer_pool_size | +---------------------------+ | 2147483648 | +---------------------------+ mysql>SELECT @@innodb_buffer_pool_instances;
+--------------------------------+ | @@innodb_buffer_pool_instances | +--------------------------------+ | 4 | +--------------------------------+ # Chunk size was set to 1GB (1073741824 bytes) on startup but was # truncated to innodb_buffer_pool_size / innodb_buffer_pool_instances mysql>SELECT @@innodb_buffer_pool_chunk_size;
+---------------------------------+ | @@innodb_buffer_pool_chunk_size | +---------------------------------+ | 536870912 | +---------------------------------+
Buffer pool size must always be equal to or a multiple of
innodb_buffer_pool_chunk_size
*
innodb_buffer_pool_instances
.
If you alter
innodb_buffer_pool_chunk_size
,
innodb_buffer_pool_size
is automatically adjusted to a value that is equal to or a
multiple of
innodb_buffer_pool_chunk_size
*
innodb_buffer_pool_instances
that is not less than current buffer pool size. The
adjustment occurs when the buffer pool is initialized.
This behavior is demonstrated in the following example:
# The buffer pool has a default size of 128MB (134217728 bytes) mysql>SELECT @@innodb_buffer_pool_size;
+---------------------------+ | @@innodb_buffer_pool_size | +---------------------------+ | 134217728 | +---------------------------+ # The chunk size is also 128MB (134217728 bytes) mysql>SELECT @@innodb_buffer_pool_chunk_size;
+---------------------------------+ | @@innodb_buffer_pool_chunk_size | +---------------------------------+ | 134217728 | +---------------------------------+ # There is a single buffer pool instance mysql>SELECT @@innodb_buffer_pool_instances;
+--------------------------------+ | @@innodb_buffer_pool_instances | +--------------------------------+ | 1 | +--------------------------------+ # Chunk size is decreased by 1MB (1048576 bytes) at startup # (134217728 - 1048576 = 133169152): shell>mysqld --innodb_buffer_pool_chunk_size=133169152
mysql>SELECT @@innodb_buffer_pool_chunk_size;
+---------------------------------+ | @@innodb_buffer_pool_chunk_size | +---------------------------------+ | 133169152 | +---------------------------------+ # Buffer pool size increases from 134217728 to 266338304 # Buffer pool size is automatically adjusted to a value that is equal to # or a multiple of innodb_buffer_pool_chunk_size * innodb_buffer_pool_instances # that is not less than current buffer pool size mysql>SELECT @@innodb_buffer_pool_size;
+---------------------------+ | @@innodb_buffer_pool_size | +---------------------------+ | 266338304 | +---------------------------+
This example demonstrates the same behavior but with multiple buffer pool instances:
# The buffer pool has a default size of 2GB (2147483648 bytes) mysql>SELECT @@innodb_buffer_pool_size;
+---------------------------+ | @@innodb_buffer_pool_size | +---------------------------+ | 2147483648 | +---------------------------+ # The chunk size is .5 GB (536870912 bytes) mysql>SELECT @@innodb_buffer_pool_chunk_size;
+---------------------------------+ | @@innodb_buffer_pool_chunk_size | +---------------------------------+ | 536870912 | +---------------------------------+ # There are 4 buffer pool instances mysql>SELECT @@innodb_buffer_pool_instances;
+--------------------------------+ | @@innodb_buffer_pool_instances | +--------------------------------+ | 4 | +--------------------------------+ # Chunk size is decreased by 1MB (1048576 bytes) at startup # (536870912 - 1048576 = 535822336): shell>mysqld --innodb_buffer_pool_chunk_size=535822336
mysql>SELECT @@innodb_buffer_pool_chunk_size;
+---------------------------------+ | @@innodb_buffer_pool_chunk_size | +---------------------------------+ | 535822336 | +---------------------------------+ # Buffer pool size increases from 2147483648 to 4286578688 # Buffer pool size is automatically adjusted to a value that is equal to # or a multiple of innodb_buffer_pool_chunk_size * innodb_buffer_pool_instances # that is not less than current buffer pool size of 2147483648 mysql>SELECT @@innodb_buffer_pool_size;
+---------------------------+ | @@innodb_buffer_pool_size | +---------------------------+ | 4286578688 | +---------------------------+
Care should be taken when changing
innodb_buffer_pool_chunk_size
,
as changing this value can increase the size of the buffer
pool, as shown in the examples above. Before you change
innodb_buffer_pool_chunk_size
,
calculate the effect on
innodb_buffer_pool_size
to ensure that the resulting buffer pool size is
acceptable.
To avoid potential performance issues, the number of chunks
(innodb_buffer_pool_size
/
innodb_buffer_pool_chunk_size
)
should not exceed 1000.
The innodb_buffer_pool_size
configuration option can be set dynamically using a
SET
statement, allowing you to
resize the buffer pool without restarting the server. For
example:
mysql> SET GLOBAL innodb_buffer_pool_size=402653184;
Active transactions and operations performed through
InnoDB
APIs should be completed before
resizing the buffer pool. When initiating a resizing
operation, the operation does not start until all active
transactions are completed. Once the resizing operation is in
progress, new transactions and operations that require access
to the buffer pool must wait until the resizing operation
finishes. The exception to the rule is that concurrent access
to the buffer pool is permitted while the buffer pool is
defragmented and pages are withdrawn when buffer pool size is
decreased. A drawback of allowing concurrent access is that it
could result in a temporary shortage of available pages while
pages are being withdrawn.
Nested transactions could fail if initiated after the buffer pool resizing operation begins.
The
Innodb_buffer_pool_resize_status
reports buffer pool resizing progress. For example:
mysql> SHOW STATUS WHERE Variable_name='InnoDB_buffer_pool_resize_status';
+----------------------------------+----------------------------------+
| Variable_name | Value |
+----------------------------------+----------------------------------+
| Innodb_buffer_pool_resize_status | Resizing also other hash tables. |
+----------------------------------+----------------------------------+
Buffer pool resizing progress is also logged in the server error log. This example shows notes that are logged when increasing the size of the buffer pool:
[Note] InnoDB: Resizing buffer pool from 134217728 to 4294967296. (unit=134217728) [Note] InnoDB: disabled adaptive hash index. [Note] InnoDB: buffer pool 0 : 31 chunks (253952 blocks) was added. [Note] InnoDB: buffer pool 0 : hash tables were resized. [Note] InnoDB: Resized hash tables at lock_sys, adaptive hash index, dictionary. [Note] InnoDB: completed to resize buffer pool from 134217728 to 4294967296. [Note] InnoDB: re-enabled adaptive hash index.
This example shows notes that are logged when decreasing the size of the buffer pool:
[Note] InnoDB: Resizing buffer pool from 4294967296 to 134217728. (unit=134217728) [Note] InnoDB: disabled adaptive hash index. [Note] InnoDB: buffer pool 0 : start to withdraw the last 253952 blocks. [Note] InnoDB: buffer pool 0 : withdrew 253952 blocks from free list. tried to relocate 0 pages. (253952/253952) [Note] InnoDB: buffer pool 0 : withdrawn target 253952 blocks. [Note] InnoDB: buffer pool 0 : 31 chunks (253952 blocks) was freed. [Note] InnoDB: buffer pool 0 : hash tables were resized. [Note] InnoDB: Resized hash tables at lock_sys, adaptive hash index, dictionary. [Note] InnoDB: completed to resize buffer pool from 4294967296 to 134217728. [Note] InnoDB: re-enabled adaptive hash index.
The resizing operation is performed by a background thread. When increasing the size of the buffer pool, the resizing operation:
Adds pages in chunks
(chunk size is
defined by
innodb_buffer_pool_chunk_size
)
Coverts hash tables, lists, and pointers to use new addresses in memory
Adds new pages to the free list
While these operations are in progress, other threads are blocked from accessing the buffer pool.
When decreasing the size of the buffer pool, the resizing operation:
Defragments the buffer pool and withdraws (frees) pages
Removes pages in chunks
(chunk size is
defined by
innodb_buffer_pool_chunk_size
)
Converts hash tables, lists, and pointers to use new addresses in memory
Of these operations, only defragmenting the buffer pool and withdrawing pages allow other threads to access to the buffer pool concurrently.
For systems with buffer pools in the multi-gigabyte range,
dividing the buffer pool into separate instances can improve
concurrency, by reducing contention as different threads read
and write to cached pages. This feature is typically intended
for systems with a buffer
pool size in the multi-gigabyte range. Multiple buffer
pool instances are configured using the
innodb_buffer_pool_instances
configuration option, and you might also adjust the
innodb_buffer_pool_size
value.
When the InnoDB
buffer pool is large, many
data requests can be satisfied by retrieving from memory. You
might encounter bottlenecks from multiple threads trying to
access the buffer pool at once. You can enable multiple buffer
pools to minimize this contention. Each page that is stored in
or read from the buffer pool is assigned to one of the buffer
pools randomly, using a hashing function. Each buffer pool
manages its own free lists, flush lists, LRUs, and all other
data structures connected to a buffer pool, and is protected by
its own buffer pool mutex.
To enable multiple buffer pool instances, set the
innodb_buffer_pool_instances
configuration
option to a value greater than 1 (the default) up to 64 (the
maximum). This option takes effect only when you set
innodb_buffer_pool_size
to a size of 1GB or
more. The total size you specify is divided among all the buffer
pools. For best efficiency, specify a combination of
innodb_buffer_pool_instances
and innodb_buffer_pool_size
so
that each buffer pool instance is at least 1GB.
For information about modifying InnoDB
buffer
pool size, see Section 14.6.3.2, “Configuring InnoDB Buffer Pool Size”.
Rather than using a strict LRU
algorithm, InnoDB
uses a technique to
minimize the amount of data that is brought into the
buffer pool and never
accessed again. The goal is to make sure that frequently
accessed (“hot”) pages remain in the buffer pool,
even as read-ahead and
full table scans
bring in new blocks that might or might not be accessed
afterward.
Newly read blocks are inserted into the middle of the LRU list.
All newly read pages are inserted at a location that by default
is 3/8
from the tail of the LRU list. The
pages are moved to the front of the list (the most-recently used
end) when they are accessed in the buffer pool for the first
time. Thus, pages that are never accessed never make it to the
front portion of the LRU list, and “age out” sooner
than with a strict LRU approach. This arrangement divides the
LRU list into two segments, where the pages downstream of the
insertion point are considered “old” and are
desirable victims for LRU eviction.
For an explanation of the inner workings of the
InnoDB
buffer pool and specifics about the
LRU algorithm, see Section 14.6.3.1, “The InnoDB Buffer Pool”.
You can control the insertion point in the LRU list and choose
whether InnoDB
applies the same optimization
to blocks brought into the buffer pool by table or index scans.
The configuration parameter
innodb_old_blocks_pct
controls
the percentage of “old” blocks in the LRU list. The
default value of
innodb_old_blocks_pct
is
37
, corresponding to the original fixed ratio
of 3/8. The value range is 5
(new pages in
the buffer pool age out very quickly) to 95
(only 5% of the buffer pool is reserved for hot pages, making
the algorithm close to the familiar LRU strategy).
The optimization that keeps the buffer pool from being churned
by read-ahead can avoid similar problems due to table or index
scans. In these scans, a data page is typically accessed a few
times in quick succession and is never touched again. The
configuration parameter
innodb_old_blocks_time
specifies the time window (in milliseconds) after the first
access to a page during which it can be accessed without being
moved to the front (most-recently used end) of the LRU list. The
default value of
innodb_old_blocks_time
is
1000
. Increasing this value makes more and
more blocks likely to age out faster from the buffer pool.
Both innodb_old_blocks_pct
and
innodb_old_blocks_time
are
dynamic, global and can be specified in the MySQL option file
(my.cnf
or my.ini
) or
changed at runtime with the SET GLOBAL
command. Changing the setting requires the
SUPER
privilege.
To help you gauge the effect of setting these parameters, the
SHOW ENGINE INNODB STATUS
command reports
buffer pool statistics. For details, see
Section 14.6.3.9, “Monitoring the Buffer Pool Using the InnoDB Standard Monitor”.
Because the effects of these parameters can vary widely based on your hardware configuration, your data, and the details of your workload, always benchmark to verify the effectiveness before changing these settings in any performance-critical or production environment.
In mixed workloads where most of the activity is OLTP type with
periodic batch reporting queries which result in large scans,
setting the value of
innodb_old_blocks_time
during
the batch runs can help keep the working set of the normal
workload in the buffer pool.
When scanning large tables that cannot fit entirely in the
buffer pool, setting
innodb_old_blocks_pct
to a
small value keeps the data that is only read once from consuming
a significant portion of the buffer pool. For example, setting
innodb_old_blocks_pct=5
restricts this data
that is only read once to 5% of the buffer pool.
When scanning small tables that do fit into memory, there is
less overhead for moving pages around within the buffer pool, so
you can leave
innodb_old_blocks_pct
at its
default value, or even higher, such as
innodb_old_blocks_pct=50
.
The effect of the
innodb_old_blocks_time
parameter is harder to predict than the
innodb_old_blocks_pct
parameter, is relatively small, and varies more with the
workload. To arrive at an optimal value, conduct your own
benchmarks if the performance improvement from adjusting
innodb_old_blocks_pct
is not
sufficient.
A read-ahead request is
an I/O request to prefetch multiple pages in the
buffer pool
asynchronously, in anticipation that these pages will be needed
soon. The requests bring in all the pages in one
extent.
InnoDB
uses two read-ahead algorithms to
improve I/O performance:
Linear read-ahead is a
technique that predicts what pages might be needed soon based on
pages in the buffer pool being accessed sequentially. You
control when InnoDB
performs a read-ahead
operation by adjusting the number of sequential page accesses
required to trigger an asynchronous read request, using the
configuration parameter
innodb_read_ahead_threshold
.
Before this parameter was added, InnoDB
would
only calculate whether to issue an asynchronous prefetch request
for the entire next extent when it read in the last page of the
current extent.
The configuration parameter
innodb_read_ahead_threshold
controls how sensitive InnoDB
is in detecting
patterns of sequential page access. If the number of pages read
sequentially from an extent is greater than or equal to
innodb_read_ahead_threshold
,
InnoDB
initiates an asynchronous read-ahead
operation of the entire following extent.
innodb_read_ahead_threshold
can
be set to any value from 0-64. The default value is 56. The
higher the value, the more strict the access pattern check. For
example, if you set the value to 48, InnoDB
triggers a linear read-ahead request only when 48 pages in the
current extent have been accessed sequentially. If the value is
8, InnoDB
triggers an asynchronous read-ahead
even if as few as 8 pages in the extent are accessed
sequentially. You can set the value of this parameter in the
MySQL configuration
file, or change it dynamically with the SET
GLOBAL
command, which requires the
SUPER
privilege.
Random read-ahead is a
technique that predicts when pages might be needed soon based on
pages already in the buffer pool, regardless of the order in
which those pages were read. If 13 consecutive pages from the
same extent are found in the buffer pool,
InnoDB
asynchronously issues a request to
prefetch the remaining pages of the extent. To enable this
feature, set the configuration variable
innodb_random_read_ahead
to
ON
.
The SHOW ENGINE INNODB STATUS
command
displays statistics to help you evaluate the effectiveness of
the read-ahead algorithm. Statistics include counter information
for the following global status variables:
This information can be useful when fine-tuning the
innodb_random_read_ahead
setting.
For more information about I/O performance, see Section 8.5.8, “Optimizing InnoDB Disk I/O” and Section 8.12.2, “Optimizing Disk I/O”.
InnoDB
performs certain tasks in the
background, including flushing
of dirty pages (those
pages that have been changed but are not yet written to the
database files) from the buffer
pool.
InnoDB
starts flushing buffer pool pages when
the percentage of dirty pages in the buffer pool reaches the low
water mark setting defined by
innodb_max_dirty_pages_pct_lwm
.
This option is intended to control the ratio of dirty pages in
the buffer pool and ideally prevent the percentage of dirty
pages from reaching
innodb_max_dirty_pages_pct
. If
the percentage of dirty pages in the buffer pool exceeds
innodb_max_dirty_pages_pct
,
InnoDB
begins to aggressively flush buffer
pool pages.
InnoDB
uses an algorithm to estimate the
required rate of flushing, based on the speed of redo log
generation and the current rate of flushing. The intent is to
smooth overall performance by ensuring that buffer flush
activity keeps up with the need to keep the buffer pool
“clean”. Automatically adjusting the rate of
flushing can help to avoid sudden dips in throughput, when
excessive buffer pool flushing limits the I/O capacity available
for ordinary read and write activity.
InnoDB
uses its log files in a circular
fashion. Before reusing a portion of a log file,
InnoDB
flushes to disk all dirty buffer pool
pages whose redo entries are contained in that portion of the
log file, a process known as a
sharp checkpoint.
If a workload is write-intensive, it generates a lot of redo
information, all written to the log file. If all available space
in the log files is used up, a sharp checkpoint occurs, causing
a temporary reduction in throughput. This situation can happen
even if
innodb_max_dirty_pages_pct
is
not reached.
InnoDB
uses a heuristic-based algorithm to
avoid such a scenario, by measuring the number of dirty pages in
the buffer pool and the rate at which redo is being generated.
Based on these numbers, InnoDB
decides how
many dirty pages to flush from the buffer pool each second. This
self-adapting algorithm is able to deal with sudden changes in
workload.
Internal benchmarking has shown that this algorithm not only maintains throughput over time, but can also improve overall throughput significantly.
Because adaptive flushing can significantly affect the I/O
pattern of a workload, the
innodb_adaptive_flushing
configuration parameter lets you turn off this feature. The
default value for
innodb_adaptive_flushing
is
ON
, enabling the adaptive flushing algorithm.
You can set the value of this parameter in the MySQL option file
(my.cnf
or my.ini
) or
change it dynamically with the SET GLOBAL
command, which requires the SUPER
privilege.
For information about fine-tuning InnoDB
buffer pool flushing behavior, see
Section 14.6.3.7, “Fine-tuning InnoDB Buffer Pool Flushing”.
For more information about InnoDB
I/O
performance, see Section 8.5.8, “Optimizing InnoDB Disk I/O”.
The configuration options
innodb_flush_neighbors
and
innodb_lru_scan_depth
let you
fine-tune aspects of the
flushing process for the
InnoDB
buffer pool.
Specifies whether flushing a page from the buffer pool also flushes other dirty pages in the same extent. When the table data is stored on a traditional HDD storage device, flushing neighbor pages in one operation reduces I/O overhead (primarily for disk seek operations) compared to flushing individual pages at different times. For table data stored on SSD, seek time is not a significant factor and you can disable this setting to spread out write operations.
Specifies, per buffer pool instance, how far down the buffer pool LRU list the page cleaner thread scans looking for dirty pages to flush. This is a background operation performed once per second.
These options primarily help write-intensive workloads. With heavy DML activity, flushing can fall behind if it is not aggressive enough, resulting in excessive memory use in the buffer pool; or, disk writes due to flushing can saturate your I/O capacity if that mechanism is too aggressive. The ideal settings depend on your workload, data access patterns, and storage configuration (for example, whether data is stored on HDD or SSD devices).
For systems with constant heavy
workloads, or workloads
that fluctuate widely, several configuration options let you
fine-tune the flushing
behavior for InnoDB
tables:
These options feed into the formula used by the
innodb_adaptive_flushing
option.
The innodb_adaptive_flushing
,
innodb_io_capacity
and
innodb_max_dirty_pages_pct
options are limited or extended by the following options:
The InnoDB
adaptive flushing
mechanism is not appropriate in all cases. It gives the most
benefit when the redo log
is in danger of filling up. The
innodb_adaptive_flushing_lwm
option specifies a “low water mark” percentage of
redo log capacity; when that threshold is crossed,
InnoDB
turns on adaptive flushing even if not
specified by the
innodb_adaptive_flushing
option.
If flushing activity falls far behind, InnoDB
can flush more aggressively than specified by
innodb_io_capacity
.
innodb_io_capacity_max
represents an upper limit on the I/O capacity used in such
emergency situations, so that the spike in I/O does not consume
all the capacity of the server.
InnoDB
tries to flush data from the buffer
pool so that the percentage of dirty pages does not exceed the
value of
innodb_max_dirty_pages_pct
. The
default value for
innodb_max_dirty_pages_pct
is
75.
The
innodb_max_dirty_pages_pct
setting establishes a target for flushing activity. It does
not affect the rate of flushing. For information about
managing the rate of flushing, see
Section 14.6.3.6, “Configuring InnoDB Buffer Pool Flushing”.
The
innodb_max_dirty_pages_pct_lwm
option specifies a “low water mark” value that
represents the percentage of dirty pages where pre-flushing is
enabled to control the dirty page ratio and ideally prevent the
percentage of dirty pages from reaching
innodb_max_dirty_pages_pct
. A
value of
innodb_max_dirty_pages_pct_lwm=0
disables the “pre-flushing” behavior.
Most of the options referenced above are most applicable to servers that run write-heavy workloads for long periods of time and have little reduced load time to catch up with changes waiting to be written to disk.
innodb_flushing_avg_loops
defines the number of iterations for which
InnoDB
keeps the previously calculated
snapshot of the flushing state, which controls how quickly
adaptive flushing responds to foreground load changes. Setting a
high value for
innodb_flushing_avg_loops
means
that InnoDB
keeps the previously calculated
snapshot longer, so adaptive flushing responds more slowly. A
high value also reduces positive feedback between foreground and
background work, but when setting a high value it is important
to ensure that InnoDB
redo log utilization
does not reach 75% (the hardcoded limit at which async flushing
starts) and that the
innodb_max_dirty_pages_pct
setting keeps the number of dirty pages to a level that is
appropriate for the workload.
Systems with consistent workloads, a large
innodb_log_file_size
, and small
spikes that do not reach 75% redo log space utilization should
use a high
innodb_flushing_avg_loops
value
to keep flushing as smooth as possible. For systems with extreme
load spikes or log files that do not provide a lot of space,
consider a smaller
innodb_flushing_avg_loops
value. A smaller value allows flushing to closely track the load
and helps avoid reaching 75% redo log space utilization.
To reduce the warmup period
after restarting the server, InnoDB
saves a
percentage of the most recently used pages for each buffer pool
at server shutdown and restores these pages at server startup.
The percentage of recently used pages that is stored is defined
by the
innodb_buffer_pool_dump_pct
configuration option.
After restarting a busy server, there is typically a warmup period with steadily increasing throughput, as disk pages that were in the buffer pool are brought back into memory (as the same data is queried, updated, and so on). The ability to restore the buffer pool at startup shortens the warmup period by reloading disk pages that were in the buffer pool before the restart rather than waiting for DML operations to access corresponding rows. Also, I/O requests can be performed in large batches, making the overall I/O faster. Page loading happens in the background, and does not delay database startup.
In addition to saving the buffer pool state at shutdown and restoring it at startup, you can save and restore the buffer pool state at any time, while the server is running. For example, you can save the state of the buffer pool after reaching a stable throughput under a steady workload. You could also restore the previous buffer pool state after running reports or maintenance jobs that bring data pages into the buffer pool that are only requited for those operations, or after running some other non-typical workload.
Even though a buffer pool can be many gigabytes in size, the
buffer pool data that InnoDB
saves to disk is
tiny by comparison. Only tablespace IDs and page IDs necessary
to locate the appropriate pages are saved to disk. This
information is derived from the
INNODB_BUFFER_PAGE_LRU
INFORMATION_SCHEMA
table. By default,
tablespace ID and page ID data is saved in a file named
ib_buffer_pool
, which is saved to the
InnoDB
data directory. The file name and
location can be modified using the
innodb_buffer_pool_filename
configuration parameter.
Because data is cached in and aged out of the buffer pool as it is with regular database operations, there is no problem if the disk pages are recently updated, or if a DML operation involves data that has not yet been loaded. The loading mechanism skips requested pages that no longer exist.
The underlying mechanism involves a background thread that is dispatched to perform the dump and load operations.
Disk pages from compressed tables are loaded into the buffer pool in their compressed form. Pages are uncompressed as usual when page contents are accessed during DML operations. Because uncompressing pages is a CPU-intensive process, it is more efficient for concurrency to perform the operation in a connection thread rather than in the single thread that performs the buffer pool restore operation.
Operations related to saving and restoring the buffer pool state are described in the following topics:
Before dumping pages from the buffer pool, you can configure
the percentage of most-recently-used buffer pool pages that
you want to dump by setting the
innodb_buffer_pool_dump_pct
option. If you plan to dump buffer pool pages while the server
is running, you can configure the option dynamically:
SET GLOBAL innodb_buffer_pool_dump_pct=40;
If you plan to dump buffer pool pages at server shutdown, set
innodb_buffer_pool_dump_pct
in your configuration file.
[mysqld] innodb_buffer_pool_dump_pct=40
The
innodb_buffer_pool_dump_pct
default value was changed from 100 (dump all pages) to 25
(dump 25% of most-recently-used pages) in MySQL
5.7 when
innodb_buffer_pool_dump_at_shutdown
and
innodb_buffer_pool_load_at_startup
were enabled by default.
To save the state of the buffer pool at server shutdown, issue the following statement prior to shutting down the server:
SET GLOBAL innodb_buffer_pool_dump_at_shutdown=ON;
innodb_buffer_pool_dump_at_shutdown
is enabled by default.
To restore the buffer pool state at server startup, specify
the --innodb_buffer_pool_load_at_startup
option when starting the server:
mysqld --innodb_buffer_pool_load_at_startup=ON;
innodb_buffer_pool_load_at_startup
is enabled by default.
To save the state of the buffer pool while MySQL server is running, issue the following statement:
SET GLOBAL innodb_buffer_pool_dump_now=ON;
To restore the buffer pool state while MySQL is running, issue the following statement:
SET GLOBAL innodb_buffer_pool_load_now=ON;
To display progress when saving the buffer pool state to disk, issue the following statement:
SHOW STATUS LIKE 'Innodb_buffer_pool_dump_status';
If the operation has not yet started, “not started” is returned. If the operation is complete, the completion time is printed (e.g. Finished at 110505 12:18:02). If the operation is in progress, status information is provided (e.g. Dumping buffer pool 5/7, page 237/2873).
To display progress when loading the buffer pool, issue the following statement:
SHOW STATUS LIKE 'Innodb_buffer_pool_load_status';
If the operation has not yet started, “not started” is returned. If the operation is complete, the completion time is printed (e.g. Finished at 110505 12:23:24). If the operation is in progress, status information is provided (e.g. Loaded 123/22301 pages).
To abort a buffer pool load operation, issue the following statement:
SET GLOBAL innodb_buffer_pool_load_abort=ON;
You can monitor buffer pool load progress using Performance Schema.
The following example demonstrates how to enable the
stage/innodb/buffer pool load
stage event
instrument and related consumer tables to monitor buffer pool
load progress.
For information about buffer pool dump and load procedures used in this example, see Section 14.6.3.8, “Saving and Restoring the Buffer Pool State”. For information about Performance Schema stage event instruments and related consumers, see Section 25.11.5, “Performance Schema Stage Event Tables”.
Enable the stage/innodb/buffer pool
load
instrument:
mysql>UPDATE performance_schema.setup_instruments SET ENABLED = 'YES'
WHERE NAME LIKE 'stage/innodb/buffer%';
Enable the stage event consumer tables, which include
events_stages_current
,
events_stages_history
, and
events_stages_history_long
.
mysql>UPDATE performance_schema.setup_consumers SET ENABLED = 'YES'
WHERE NAME LIKE '%stages%';
Dump the current buffer pool state by enabling
innodb_buffer_pool_dump_now
.
mysql> SET GLOBAL innodb_buffer_pool_dump_now=ON;
Check the buffer pool dump status to ensure that the operation has completed.
mysql> SHOW STATUS LIKE 'Innodb_buffer_pool_dump_status'\G
*************************** 1. row ***************************
Variable_name: Innodb_buffer_pool_dump_status
Value: Buffer pool(s) dump completed at 150202 16:38:58
Load the buffer pool by enabling
innodb_buffer_pool_load_now
:
mysql> SET GLOBAL innodb_buffer_pool_load_now=ON;
Check the current status of the buffer pool load operation
by querying the Performance Schema
events_stages_current
table.
The WORK_COMPLETED
column shows the
number of buffer pool pages loaded. The
WORK_ESTIMATED
column provides an
estimate of the remaining work, in pages.
mysql>SELECT EVENT_NAME, WORK_COMPLETED, WORK_ESTIMATED
FROM performance_schema.events_stages_current;
+-------------------------------+----------------+----------------+ | EVENT_NAME | WORK_COMPLETED | WORK_ESTIMATED | +-------------------------------+----------------+----------------+ | stage/innodb/buffer pool load | 5353 | 7167 | +-------------------------------+----------------+----------------+
The events_stages_current
table returns an empty set if the buffer pool load
operation has completed. In this case, you can check the
events_stages_history
table
to view data for the completed event. For example:
mysql>SELECT EVENT_NAME, WORK_COMPLETED, WORK_ESTIMATED
FROM performance_schema.events_stages_history;
+-------------------------------+----------------+----------------+ | EVENT_NAME | WORK_COMPLETED | WORK_ESTIMATED | +-------------------------------+----------------+----------------+ | stage/innodb/buffer pool load | 7167 | 7167 | +-------------------------------+----------------+----------------+
You can also monitor buffer pool load progress using
Performance Schema when loading the buffer pool at startup
using
innodb_buffer_pool_load_at_startup
.
In this case, the stage/innodb/buffer pool
load
instrument and related consumers must be
enabled at startup. For more information, see
Section 25.3, “Performance Schema Startup Configuration”.
InnoDB
Standard Monitor output, which can be
accessed using
SHOW
ENGINE INNODB STATUS
, provides metrics that pertain to
operation of the InnoDB
buffer pool. Buffer
pool metrics are located in the BUFFER POOL AND
MEMORY
section of InnoDB
Standard
Monitor output and appear similar to the following:
---------------------- BUFFER POOL AND MEMORY ---------------------- Total large memory allocated 2198863872 Dictionary memory allocated 776332 Buffer pool size 131072 Free buffers 124908 Database pages 5720 Old database pages 2071 Modified db pages 910 Pending reads 0 Pending writes: LRU 0, flush list 0, single page 0 Pages made young 4, not young 0 0.10 youngs/s, 0.00 non-youngs/s Pages read 197, created 5523, written 5060 0.00 reads/s, 190.89 creates/s, 244.94 writes/s Buffer pool hit rate 1000 / 1000, young-making rate 0 / 1000 not 0 / 1000 Pages read ahead 0.00/s, evicted without access 0.00/s, Random read ahead 0.00/s LRU len: 5720, unzip_LRU len: 0 I/O sum[0]:cur[0], unzip sum[0]:cur[0]
The following table describes InnoDB
buffer
pool metrics reported by the InnoDB
Standard
Monitor.
Per second averages provided in InnoDB
Standard Monitor output are based on the elapsed time since
InnoDB
Standard Monitor output was last
printed.
Table 14.2 InnoDB Buffer Pool Metrics
Name | Description |
---|---|
Total memory allocated | The total memory allocated for the buffer pool in bytes. |
Dictionary memory allocated | The total memory allocated for the InnoDB data
dictionary in bytes. |
Buffer pool size | The total size in pages allocated to the buffer pool. |
Free buffers | The total size in pages of the buffer pool free list. |
Database pages | The total size in pages of the buffer pool LRU list. |
Old database pages | The total size in pages of the buffer pool old LRU sublist. |
Modified db pages | The current number of pages modified in the buffer pool. |
Pending reads | The number of buffer pool pages waiting to be read in to the buffer pool. |
Pending writes LRU | The number of old dirty pages within the buffer pool to be written from the bottom of the LRU list. |
Pending writes flush list | The number of buffer pool pages to be flushed during checkpointing. |
Pending writes single page | The number of pending independent page writes within the buffer pool. |
Pages made young | The total number of pages made young in the buffer pool LRU list (moved to the head of sublist of “new” pages). |
Pages made not young | The total number of pages not made young in the buffer pool LRU list (pages that have remained in the “old” sublist without being made young). |
youngs/s | The per second average of accesses to old pages in the buffer pool LRU list that have resulted in making pages young. See the notes that follow this table for more information. |
non-youngs/s | The per second average of accesses to old pages in the buffer pool LRU list that have resulted in not making pages young. See the notes that follow this table for more information. |
Pages read | The total number of pages read from the buffer pool. |
Pages created | The total number of pages created within the buffer pool. |
Pages written | The total number of pages written from the buffer pool. |
reads/s | The per second average number of buffer pool page reads per second. |
creates/s | The per second average number of buffer pool pages created per second. |
writes/s | The per second average number of buffer pool page writes per second. |
Buffer pool hit rate | The buffer pool page hit rate for pages read from the buffer pool memory vs from disk storage. |
young-making rate | The average hit rate at which page accesses have resulted in making pages young. See the notes that follow this table for more information. |
not (young-making rate) | The average hit rate at which page accesses have not resulted in making pages young. See the notes that follow this table for more information. |
Pages read ahead | The per second average of read ahead operations. |
Pages evicted without access | The per second average of the pages evicted without being accessed from the buffer pool. |
Random read ahead | The per second average of random read ahead operations. |
LRU len | The total size in pages of the buffer pool LRU list. |
unzip_LRU len | The total size in pages of the buffer pool unzip_LRU list. |
I/O sum | The total number of buffer pool LRU list pages accessed, for the last 50 seconds. |
I/O cur | The total number of buffer pool LRU list pages accessed. |
I/O unzip sum | The total number of buffer pool unzip_LRU list pages accessed. |
I/O unzip cur | The total number of buffer pool unzip_LRU list pages accessed. |
Notes:
The youngs/s
metric only relates to old
pages. It is based on the number of accesses to pages and
not the number of pages. There can be multiple accesses to a
given page, all of which are counted. If you see very low
youngs/s
values when there are no large
scans occurring, you might need to reduce the delay time or
increase the percentage of the buffer pool used for the old
sublist. Increasing the percentage makes the old sublist
larger, so pages in that sublist take longer to move to the
tail and to be evicted. This increases the likelihood that
the pages will be accessed again and be made young.
The non-youngs/s
metric only relates to
old pages. It is based on the number of accesses to pages
and not the number of pages. There can be multiple accesses
to a given page, all of which are counted. If you do not see
a lot of non-youngs/s
when you are doing
large table scans (and lots of youngs/s
),
increase the delay value.
The young-making
rate accounts for
accesses to all buffer pool pages, not just accesses to
pages in the old sublist. The
young-making
rate and
not
rate do not normally add up to the
overall buffer pool hit rate. Page hits in the old sublist
cause pages to move to the new sublist, but page hits in the
new sublist cause pages to move to the head of the list only
if they are a certain distance from the head.
not (young-making rate)
is the average
hit rate at which page accesses have not resulted in making
pages young due to the delay defined by
innodb_old_blocks_time
not
being met, or due to page hits in the new sublist that did
not result in pages being moved to the head. This rate
accounts for accesses to all buffer pool pages, not just
accesses to pages in the old sublist.
InnoDB
buffer pool
server status
variables and the
INNODB_BUFFER_POOL_STATS
table
provide many of the same buffer pool metrics found in
InnoDB
Standard Monitor output. For more
information about the
INNODB_BUFFER_POOL_STATS
table, see
Example 14.10, “Querying the INNODB_BUFFER_POOL_STATS Table”.
When InnoDB
was developed, the memory
allocators supplied with operating systems and run-time libraries
were often lacking in performance and scalability. At that time,
there were no memory allocator libraries tuned for multi-core
CPUs. Therefore, InnoDB
implemented its own
memory allocator in the mem
subsystem. This
allocator is guarded by a single mutex, which may become a
bottleneck.
InnoDB
also implements a wrapper interface
around the system allocator (malloc
and
free
) that is likewise guarded by a single
mutex.
Today, as multi-core systems have become more widely available,
and as operating systems have matured, significant improvements
have been made in the memory allocators provided with operating
systems. These new memory allocators perform better and are more
scalable than they were in the past. Most workloads, especially
those where memory is frequently allocated and released (such as
multi-table joins), benefit from using a more highly tuned memory
allocator as opposed to the internal,
InnoDB
-specific memory allocator.
You can control whether InnoDB
uses its own
memory allocator or an allocator of the operating system, by
setting the value of the system configuration parameter
innodb_use_sys_malloc
in the
MySQL option file (my.cnf
or
my.ini
). If set to ON
or
1
(the default), InnoDB
uses
the malloc
and free
functions of the underlying system rather than manage memory pools
itself. This parameter is not dynamic, and takes effect only when
the system is started. To continue to use the
InnoDB
memory allocator, set
innodb_use_sys_malloc
to
0
.
When the InnoDB
memory allocator is disabled,
InnoDB
ignores the value of the parameter
innodb_additional_mem_pool_size
.
The InnoDB
memory allocator uses an additional
memory pool for satisfying allocation requests without having to
fall back to the system memory allocator. When the
InnoDB
memory allocator is disabled, all such
allocation requests are fulfilled by the system memory allocator.
On Unix-like systems that use dynamic linking, replacing the
memory allocator may be as easy as making the environment variable
LD_PRELOAD
or
LD_LIBRARY_PATH
point to the dynamic library
that implements the allocator. On other systems, some relinking
may be necessary. Please refer to the documentation of the memory
allocator library of your choice.
Since InnoDB
cannot track all memory use when
the system memory allocator is used
(innodb_use_sys_malloc
is
ON
), the section “BUFFER POOL AND
MEMORY” in the output of the SHOW ENGINE INNODB
STATUS
command only includes the buffer pool statistics
in the “Total memory allocated”. Any memory allocated
using the mem
subsystem or using
ut_malloc
is excluded.
innodb_use_sys_malloc
and
innodb_additional_mem_pool_size
were deprecated in MySQL 5.6 and removed in MySQL
5.7.
For more information about the performance implications of
InnoDB
memory usage, see
Section 8.10, “Buffering and Caching”.
When INSERT
,
UPDATE
, and
DELETE
operations are performed on
a table, the values of indexed columns (particularly the values of
secondary keys) are often in an unsorted order, requiring
substantial I/O to bring secondary indexes up to date.
InnoDB
has a
change buffer that
caches changes to secondary index entries when the relevant
page is not in the
buffer pool, thus avoiding
expensive I/O operations by not immediately reading in the page
from disk. The buffered changes are merged when the page is loaded
to the buffer pool, and the updated page is later flushed to disk.
The InnoDB
main thread merges buffered changes
when the server is nearly idle, and during a
slow shutdown.
Because it can result in fewer disk reads and writes, the change buffer feature is most valuable for workloads that are I/O-bound, for example applications with a high volume of DML operations such as bulk inserts.
However, the change buffer occupies a part of the buffer pool, reducing the memory available to cache data pages. If the working set almost fits in the buffer pool, or if your tables have relatively few secondary indexes, it may be useful to disable change buffering. If the working set fits entirely within the buffer, change buffering does not impose extra overhead, because it only applies to pages that are not in the buffer pool.
You can control the extent to which InnoDB
performs change buffering using the
innodb_change_buffering
configuration parameter. You can enable or disable buffering for
inserts, delete operations (when index records are initially
marked for deletion) and purge operations (when index records are
physically deleted). An update operation is a combination of an
insert and a delete. The default
innodb_change_buffering
value is
all
.
Permitted innodb_change_buffering
values include:
all
The default value: buffer inserts, delete-marking operations, and purges.
none
Do not buffer any operations.
inserts
Buffer insert operations.
deletes
Buffer delete-marking operations.
changes
Buffer both inserts and delete-marking operations.
purges
Buffer the physical deletion operations that happen in the background.
You can set the
innodb_change_buffering
parameter
in the MySQL option file (my.cnf
or
my.ini
) or change it dynamically with the
SET GLOBAL
command, which requires the SUPER
privilege.
Changing the setting affects the buffering of new operations; the
merging of existing buffered entries is not affected.
For related information, see Section 14.4.2, “Change Buffer”. For information about configuring change buffer size, see Section 14.6.5.1, “Configuring the Change Buffer Maximum Size”.
As of MySQL 5.6.2, the
innodb_change_buffer_max_size
configuration option allows you to configure the maximum size of
the change buffer as a percentage of the total size of the
buffer pool. By default,
innodb_change_buffer_max_size
is set to 25. The maximum setting is 50.
You might consider increasing
innodb_change_buffer_max_size
on a MySQL server with heavy insert, update, and delete
activity, where change buffer merging does not keep pace with
new change buffer entries, causing the change buffer to reach
its maximum size limit.
You might consider decreasing
innodb_change_buffer_max_size
on a MySQL server with static data used for reporting, or if the
change buffer consumes too much of the memory space that is
shared with the buffer pool, causing pages to age out of the
buffer pool sooner than desired.
Test different settings with a representative workload to
determine an optimal configuration. The
innodb_change_buffer_max_size
setting is dynamic, which allows you modify the setting without
restarting the server.
InnoDB
uses operating system
threads to process requests
from user transactions. (Transactions may issue many requests to
InnoDB
before they commit or roll back.) On
modern operating systems and servers with multi-core processors,
where context switching is efficient, most workloads run well
without any limit on the number of concurrent threads. Scalability
improvements in MySQL 5.5 and up reduce the need to limit the
number of concurrently executing threads inside
InnoDB
.
In situations where it is helpful to minimize context switching
between threads, InnoDB
can use a number of
techniques to limit the number of concurrently executing operating
system threads (and thus the number of requests that are processed
at any one time). When InnoDB
receives a new
request from a user session, if the number of threads concurrently
executing is at a pre-defined limit, the new request sleeps for a
short time before it tries again. A request that cannot be
rescheduled after the sleep is put in a first-in/first-out queue
and eventually is processed. Threads waiting for locks are not
counted in the number of concurrently executing threads.
You can limit the number of concurrent threads by setting the
configuration parameter
innodb_thread_concurrency
. Once
the number of executing threads reaches this limit, additional
threads sleep for a number of microseconds, set by the
configuration parameter
innodb_thread_sleep_delay
, before
being placed into the queue.
Previously, it required experimentation to find the optimal value
for innodb_thread_sleep_delay
,
and the optimal value could change depending on the workload. In
MySQL 5.6.3 and higher, you can set the configuration option
innodb_adaptive_max_sleep_delay
to the highest value you would allow for
innodb_thread_sleep_delay
, and
InnoDB
automatically adjusts
innodb_thread_sleep_delay
up or
down depending on the current thread-scheduling activity. This
dynamic adjustment helps the thread scheduling mechanism to work
smoothly during times when the system is lightly loaded and when
it is operating near full capacity.
The default value for
innodb_thread_concurrency
and the
implied default limit on the number of concurrent threads has been
changed in various releases of MySQL and
InnoDB
. The default value of
innodb_thread_concurrency
is
0
, so that by default there is no limit on the
number of concurrently executing threads.
InnoDB
causes threads to sleep only when the
number of concurrent threads is limited. When there is no limit on
the number of threads, all contend equally to be scheduled. That
is, if innodb_thread_concurrency
is 0
, the value of
innodb_thread_sleep_delay
is
ignored.
When there is a limit on the number of threads (when
innodb_thread_concurrency
is >
0), InnoDB
reduces context switching overhead
by permitting multiple requests made during the execution of a
single SQL statement to enter
InnoDB
without observing the limit set by
innodb_thread_concurrency
. Since
an SQL statement (such as a join) may comprise multiple row
operations within InnoDB
,
InnoDB
assigns a specified number of
“tickets” that allow a thread to be scheduled
repeatedly with minimal overhead.
When a new SQL statement starts, a thread has no tickets, and it
must observe
innodb_thread_concurrency
. Once
the thread is entitled to enter InnoDB
, it is
assigned a number of tickets that it can use for subsequently
entering InnoDB
to perform row operations. If
the tickets run out, the thread is evicted, and
innodb_thread_concurrency
is
observed again which may place the thread back into the
first-in/first-out queue of waiting threads. When the thread is
once again entitled to enter InnoDB
, tickets
are assigned again. The number of tickets assigned is specified by
the global option
innodb_concurrency_tickets
, which
is 5000 by default. A thread that is waiting for a lock is given
one ticket once the lock becomes available.
The correct values of these variables depend on your environment
and workload. Try a range of different values to determine what
value works for your applications. Before limiting the number of
concurrently executing threads, review configuration options that
may improve the performance of InnoDB
on
multi-core and multi-processor computers, such as
innodb_adaptive_hash_index
.
For general performance information about MySQL thread handling, see Section 8.12.5.1, “How MySQL Uses Threads for Client Connections”.
InnoDB
uses background
threads to service various
types of I/O requests. You can configure the number of background
threads that service read and write I/O on data pages using the
innodb_read_io_threads
and
innodb_write_io_threads
configuration parameters. These parameters signify the number of
background threads used for read and write requests, respectively.
They are effective on all supported platforms. You can set values
for these parameters in the MySQL option file
(my.cnf
or my.ini
); you
cannot change values dynamically. The default value for these
parameters is 4
and permissible values range
from 1-64
.
The purpose of these configuration options to make
InnoDB
more scalable on high end systems. Each
background thread can handle up to 256 pending I/O requests. A
major source of background I/O is
read-ahead requests.
InnoDB
tries to balance the load of incoming
requests in such way that most background threads share work
equally. InnoDB
also attempts to allocate read
requests from the same extent to the same thread, to increase the
chances of coalescing the requests. If you have a high end I/O
subsystem and you see more than 64 ×
innodb_read_io_threads
pending
read requests in SHOW ENGINE INNODB STATUS
output, you might improve performance by increasing the value of
innodb_read_io_threads
.
On Linux systems, InnoDB
uses the asynchronous
I/O subsystem by default to perform read-ahead and write requests
for data file pages, which changes the way that
InnoDB
background threads service these types
of I/O requests. For more information, see
Section 14.6.8, “Using Asynchronous I/O on Linux”.
For more information about InnoDB
I/O
performance, see Section 8.5.8, “Optimizing InnoDB Disk I/O”.
InnoDB
uses the asynchronous I/O subsystem
(native AIO) on Linux to perform readahead and write requests for
data file pages. This behavior is controlled by the
innodb_use_native_aio
configuration option, which applies to Linux systems only and is
enabled by default. On other Unix-like systems,
InnoDB
uses synchronous I/O only. Historically,
InnoDB
only used asynchronous I/O on Windows
systems. Using the asynchronous I/O subsystem on Linux requires
the libaio
library.
With synchronous I/O, query threads queue I/O requests, and
InnoDB
background threads retrieve the queued
requests one at a time, issuing a synchronous I/O call for each.
When an I/O request is completed and the I/O call returns, the
InnoDB
background thread that is handling the
request calls an I/O completion routine and returns to process the
next request. The number of requests that can be processed in
parallel is n
, where
n
is the number of
InnoDB
background threads. The number of
InnoDB
background threads is controlled by
innodb_read_io_threads
and
innodb_write_io_threads
. See
Section 14.6.7, “Configuring the Number of Background InnoDB I/O Threads”.
With native AIO, query threads dispatch I/O requests directly to
the operating system, thereby removing the limit imposed by the
number of background threads. InnoDB
background
threads wait for I/O events to signal completed requests. When a
request is completed, a background thread calls an I/O completion
routine and resumes waiting for I/O events.
The advantage of native AIO is scalability for heavily I/O-bound
systems that typically show many pending reads/writes in
SHOW ENGINE INNODB STATUS\G
output. The
increase in parallel processing when using native AIO means that
the type of I/O scheduler or properties of the disk array
controller have a greater influence on I/O performance.
A potential disadvantage of native AIO for heavily I/O-bound systems is lack of control over the number of I/O write requests dispatched to the operating system at once. Too many I/O write requests dispatched to the operating system for parallel processing could, in some cases, result in I/O read starvation, depending on the amount of I/O activity and system capabilities.
If a problem with the asynchronous I/O subsystem in the OS
prevents InnoDB
from starting, you can start
the server with
innodb_use_native_aio=0
. This
option may also be disabled automatically during startup if
InnoDB
detects a potential problem such as a
combination of tmpdir
location,
tmpfs
file system, and Linux kernel that does
not support asynchronous I/O on tmpfs
.
The master thread in InnoDB is a thread that performs various tasks in the background. Most of these tasks are I/O related, such as flushing dirty pages from the buffer pool or writing changes from the insert buffer to the appropriate secondary indexes. The master thread attempts to perform these tasks in a way that does not adversely affect the normal working of the server. It tries to estimate the free I/O bandwidth available and tune its activities to take advantage of this free capacity. Historically, InnoDB has used a hard coded value of 100 IOPs (input/output operations per second) as the total I/O capacity of the server.
The parameter innodb_io_capacity
indicates the overall I/O capacity available to InnoDB. This
parameter should be set to approximately the number of I/O
operations that the system can perform per second. The value
depends on your system configuration. When
innodb_io_capacity
is set, the
master threads estimates the I/O bandwidth available for
background tasks based on the set value. Setting the value to
100
reverts to the old behavior.
You can set the value of
innodb_io_capacity
to any number
100 or greater. The default value is 200
,
reflecting that the performance of typical modern I/O devices is
higher than in the early days of MySQL. Typically, values around
the previous default of 100 are appropriate for consumer-level
storage devices, such as hard drives up to 7200 RPMs. Faster hard
drives, RAID configurations, and SSDs benefit from higher values.
The innodb_io_capacity
setting is
a total limit for all buffer pool instances. When dirty pages are
flushed, the innodb_io_capacity
limit is divided equally among buffer pool instances. For more
information, see the
innodb_io_capacity
system
variable description.
You can set the value of this parameter in the MySQL option file
(my.cnf
or my.ini
) or change
it dynamically with the SET GLOBAL
command,
which requires the SUPER
privilege.
The innodb_flush_sync
configuration option causes the
innodb_io_capacity
setting to be
ignored during bursts of I/O activity that occur at checkpoints.
innodb_flush_sync
is enabled by
default.
Formerly, the InnoDB
master thread also
performed any needed purge
operations. In MySQL 5.6.5 and higher, those I/O operations are
moved to other background threads, whose number is controlled by
the innodb_purge_threads
configuration option.
For more information about InnoDB I/O performance, see Section 8.5.8, “Optimizing InnoDB Disk I/O”.
Many InnoDB mutexes and rw-locks are reserved for a short time. On a multi-core system, it can be more efficient for a thread to continuously check if it can acquire a mutex or rw-lock for a while before sleeping. If the mutex or rw-lock becomes available during this polling period, the thread can continue immediately, in the same time slice. However, too-frequent polling by multiple threads of a shared object can cause “cache ping pong”, different processors invalidating portions of each others' cache. InnoDB minimizes this issue by waiting a random time between subsequent polls. The delay is implemented as a busy loop.
You can control the maximum delay between testing a mutex or
rw-lock using the parameter
innodb_spin_wait_delay
. The
duration of the delay loop depends on the C compiler and the
target processor. (In the 100MHz Pentium era, the unit of delay
was one microsecond.) On a system where all processor cores share
a fast cache memory, you might reduce the maximum delay or disable
the busy loop altogether by setting
innodb_spin_wait_delay=0
. On a system with
multiple processor chips, the effect of cache invalidation can be
more significant and you might increase the maximum delay.
The default value of
innodb_spin_wait_delay
is
6
. The spin wait delay is a dynamic, global
parameter that you can specify in the MySQL option file
(my.cnf
or my.ini
) or change
at runtime with the command SET GLOBAL
innodb_spin_wait_delay=
,
where delay
is the
desired maximum delay. Changing the setting requires the
delay
SUPER
privilege.
For performance considerations for InnoDB locking operations, see Section 8.11, “Optimizing Locking Operations”.
The purge operations (a type of garbage collection) that InnoDB performs automatically may be performed by one or more separate threads rather than as part of the master thread. The use of separate threads improves scalability by allowing the main database operations to run independently from maintenance work happening in the background.
To control this feature, increase the value of the configuration
option innodb_purge_threads
. If
DML action is concentrated on a single table or a few tables, keep
the setting low so that the threads do not contend with each other
for access to the busy tables. If DML operations are spread across
many tables, increase the setting. Its maximum is 32.
innodb_purge_threads
is a
non-dynamic configuration option, which means it cannot be
configured at runtime.
There is another related configuration option,
innodb_purge_batch_size
with a
default value of 300 and maximum value of 5000. This option is
mainly intended for experimentation and tuning of purge
operations, and should not be interesting to typical users.
For more information about InnoDB I/O performance, see Section 8.5.8, “Optimizing InnoDB Disk I/O”.
This section describes how to configure persistent and
non-persistent optimizer statistics for InnoDB
tables.
Persistent optimizer statistics are persisted across server restarts, allowing for greater plan stability and more consistent query performance. Persistent optimizer statistics also provide control and flexibility with these additional benefits:
You can use the
innodb_stats_auto_recalc
configuration option to control whether statistics are updated
automatically after substantial changes to a table.
You can use the STATS_PERSISTENT
,
STATS_AUTO_RECALC
, and
STATS_SAMPLE_PAGES
clauses with
CREATE TABLE
and
ALTER TABLE
statements to
configure optimizer statistics for individual tables.
You can query optimizer statistics data in the
mysql.innodb_table_stats
and
mysql.innodb_index_stats
tables.
You can view the last_update
column of the
mysql.innodb_table_stats
and
mysql.innodb_index_stats
tables to see when
statistics were last updated.
You can manually modify the
mysql.innodb_table_stats
and
mysql.innodb_index_stats
tables to force a
specific query optimization plan or to test alternative plans
without modifying the database.
The persistent optimizer statistics feature is enabled by default
(innodb_stats_persistent=ON
).
Non-persistent optimizer statistics are cleared on each server restart and after some other operations, and recomputed on the next table access. As a result, different estimates could be produced when recomputing statistics, leading to different choices in execution plans and variations in query performance.
This section also provides information about estimating
ANALYZE TABLE
complexity, which may
be useful when attempting to achieve a balance between accurate
statistics and ANALYZE TABLE
execution time.
The persistent optimizer statistics feature improves plan stability by storing statistics to disk and making them persistent across server restarts so that the optimizer is more likely to make consistent choices each time for a given query.
Optimizer statistics are persisted to disk when
innodb_stats_persistent=ON
or
when individual tables are created or altered with
STATS_PERSISTENT=1
.
innodb_stats_persistent
is
enabled by default.
Formerly, optimizer statistics were cleared on each server restart and after some other operations, and recomputed on the next table access. Consequently, different estimates could be produced when recalculating statistics, leading to different choices in query execution plans and thus variations in query performance.
Persistent statistics are stored in the
mysql.innodb_table_stats
and
mysql.innodb_index_stats
tables, as described
in Section 14.6.12.1.5, “InnoDB Persistent Statistics Tables”.
To revert to using non-persistent optimizer statistics, you can
modify tables using an ALTER TABLE
statement. For related information, see
Section 14.6.12.2, “Configuring Non-Persistent Optimizer Statistics Parameters”
tbl_name
STATS_PERSISTENT=0
The innodb_stats_auto_recalc
configuration option, which is enabled by default, determines
whether statistics are calculated automatically whenever a
table undergoes substantial changes (to more than 10% of the
rows). You can also configure automatic statistics
recalculation for individual tables using a
STATS_AUTO_RECALC
clause in a
CREATE TABLE
or
ALTER TABLE
statement.
innodb_stats_auto_recalc
is
enabled by default.
Because of the asynchronous nature of automatic statistics
recalculation (which occurs in the background), statistics may
not be recalculated instantly after running a DML operation
that affects more than 10% of a table, even when
innodb_stats_auto_recalc
is
enabled. In some cases, statistics recalculation may be
delayed by a few seconds. If up-to-date statistics are
required immediately after changing significant portions of a
table, run ANALYZE TABLE
to
initiate a synchronous (foreground) recalculation of
statistics.
If innodb_stats_auto_recalc
is disabled, ensure the accuracy of optimizer statistics by
issuing the ANALYZE TABLE
statement for each applicable table after making substantial
changes to indexed columns. You might run this statement in
your setup scripts after representative data has been loaded
into the table, and run it periodically after DML operations
significantly change the contents of indexed columns, or on a
schedule at times of low activity. When a new index is added
to an existing table, index statistics are calculated and
added to the innodb_index_stats
table
regardless of the value of
innodb_stats_auto_recalc
.
To ensure statistics are gathered when a new index is
created, either enable the
innodb_stats_auto_recalc
option, or run ANALYZE TABLE
after creating each new index when the persistent statistics
mode is enabled.
innodb_stats_persistent
,
innodb_stats_auto_recalc
, and
innodb_stats_persistent_sample_pages
are global configuration options. To override these
system-wide settings and configure optimizer statistics
parameters for individual tables, you can define
STATS_PERSISTENT
,
STATS_AUTO_RECALC
, and
STATS_SAMPLE_PAGES
clauses in
CREATE TABLE
or
ALTER TABLE
statements.
STATS_PERSISTENT
specifies whether to
enable
persistent
statistics for an InnoDB
table.
The value DEFAULT
causes the persistent
statistics setting for the table to be determined by the
innodb_stats_persistent
configuration option. The value 1
enables persistent statistics for the table, while the
value 0
turns off this feature. After
enabling persistent statistics through a CREATE
TABLE
or ALTER TABLE
statement, issue an ANALYZE
TABLE
statement to calculate the statistics,
after loading representative data into the table.
STATS_AUTO_RECALC
specifies whether to
automatically recalculate
persistent
statistics for an InnoDB
table.
The value DEFAULT
causes the persistent
statistics setting for the table to be determined by the
innodb_stats_auto_recalc
configuration option. The value 1
causes statistics to be recalculated when 10% of the data
in the table has changed. The value 0
prevents automatic recalculation for this table; with this
setting, issue an ANALYZE
TABLE
statement to recalculate the statistics
after making substantial changes to the table.
STATS_SAMPLE_PAGES
specifies the number
of index pages to sample when estimating cardinality and
other statistics for an indexed column, such as those
calculated by ANALYZE
TABLE
.
All three clauses are specified in the following
CREATE TABLE
example:
CREATE TABLE `t1` ( `id` int(8) NOT NULL auto_increment, `data` varchar(255), `date` datetime, PRIMARY KEY (`id`), INDEX `DATE_IX` (`date`) ) ENGINE=InnoDB, STATS_PERSISTENT=1, STATS_AUTO_RECALC=1, STATS_SAMPLE_PAGES=25;
The MySQL query optimizer uses estimated
statistics about key
distributions to choose the indexes for an execution plan,
based on the relative
selectivity of the
index. Operations such as ANALYZE
TABLE
cause InnoDB
to sample
random pages from each index on a table to estimate the
cardinality of the
index. (This technique is known as
random dives.)
To give you control over the quality of the statistics
estimate (and thus better information for the query
optimizer), you can change the number of sampled pages using
the parameter
innodb_stats_persistent_sample_pages
,
which can be set at runtime.
innodb_stats_persistent_sample_pages
has a default value of 20. As a general guideline, consider
modifying this parameter when encountering the following
issues:
Statistics are not accurate enough and the
optimizer chooses suboptimal plans, as shown by
EXPLAIN
output. The
accuracy of statistics can be checked by comparing the
actual cardinality of an index (as returned by running
SELECT
DISTINCT
on the index columns) with the
estimates provided in the
mysql.innodb_index_stats
persistent
statistics table.
If it is determined that statistics are not accurate
enough, the value of
innodb_stats_persistent_sample_pages
should be increased until the statistics estimates are
sufficiently accurate. Increasing
innodb_stats_persistent_sample_pages
too much, however, could cause
ANALYZE TABLE
to run
slowly.
ANALYZE TABLE
is
too slow. In this case
innodb_stats_persistent_sample_pages
should be decreased until ANALYZE
TABLE
execution time is acceptable. Decreasing
the value too much, however, could lead to the first
problem of inaccurate statistics and suboptimal query
execution plans.
If a balance cannot be achieved between accurate
statistics and ANALYZE
TABLE
execution time, consider decreasing the
number of indexed columns in the table or limiting the
number of partitions to reduce
ANALYZE TABLE
complexity.
The number of columns in the table's primary key is also
important to consider, as primary key columns are appended
to each nonunique index.
For related information, see Section 14.6.12.3, “Estimating ANALYZE TABLE Complexity for InnoDB Tables”.
By default, InnoDB
reads uncommitted data
when calculating statistics. In the case of an uncommitted
transaction that deletes rows from a table,
InnoDB
excludes records that are
delete-marked when calculating row estimates and index
statistics, which can lead to non-optimal execution plans for
other transactions that are operating on the table
concurrently using a transaction isolation level other than
READ UNCOMMITTED
. To avoid
this scenario,
innodb_stats_include_delete_marked
can be enabled to ensure that InnoDB
includes delete-marked records when calculating persistent
optimizer statistics.
When
innodb_stats_include_delete_marked
is enabled, ANALYZE TABLE
considers delete-marked records when recalculating statistics.
innodb_stats_include_delete_marked
is a global setting that affects all InnoDB
tables, and it is only applicable to persistent optimizer
statistics.
innodb_stats_include_delete_marked
was introduced in MySQL 5.7.16.
The persistent statistics feature relies on the internally
managed tables in the mysql
database, named
innodb_table_stats
and
innodb_index_stats
. These tables are set up
automatically in all install, upgrade, and build-from-source
procedures.
Table 14.3 Columns of innodb_table_stats
Column name | Description |
---|---|
database_name |
Database name |
table_name |
Table name, partition name, or subpartition name |
last_update |
A timestamp indicating the last time that InnoDB
updated this row |
n_rows |
The number of rows in the table |
clustered_index_size |
The size of the primary index, in pages |
sum_of_other_index_sizes |
The total size of other (non-primary) indexes, in pages |
Table 14.4 Columns of innodb_index_stats
Column name | Description |
---|---|
database_name |
Database name |
table_name |
Table name, partition name, or subpartition name |
index_name |
Index name |
last_update |
A timestamp indicating the last time that InnoDB
updated this row |
stat_name |
The name of the statistic, whose value is reported in the
stat_value column |
stat_value |
The value of the statistic that is named in stat_name
column |
sample_size |
The number of pages sampled for the estimate provided in the
stat_value column |
stat_description |
Description of the statistic that is named in the
stat_name column |
Both the innodb_table_stats
and
innodb_index_stats
tables include a
last_update
column showing when
InnoDB
last updated index statistics, as
shown in the following example:
mysql> SELECT * FROM innodb_table_stats \G
*************************** 1. row ***************************
database_name: sakila
table_name: actor
last_update: 2014-05-28 16:16:44
n_rows: 200
clustered_index_size: 1
sum_of_other_index_sizes: 1
...
mysql> SELECT * FROM innodb_index_stats \G
*************************** 1. row ***************************
database_name: sakila
table_name: actor
index_name: PRIMARY
last_update: 2014-05-28 16:16:44
stat_name: n_diff_pfx01
stat_value: 200
sample_size: 1
...
The innodb_table_stats
and
innodb_index_stats
tables are ordinary
tables and can be updated manually. The ability to update
statistics manually makes it possible to force a specific
query optimization plan or test alternative plans without
modifying the database. If you manually update statistics,
issue the FLUSH TABLE
command to make
MySQL reload the updated statistics.
tbl_name
Persistent statistics are considered local information,
because they relate to the server instance. The
innodb_table_stats
and
innodb_index_stats
tables are therefore not
replicated when automatic statistics recalculation takes
place. If you run ANALYZE TABLE
to initiate a synchronous recalculation of statistics, this
statement is replicated (unless you suppressed logging for
it), and recalculation takes place on the replication slaves.
The innodb_table_stats
table contains one
row per table. The data collected is demonstrated in the
following example.
Table t1
contains a primary index (columns
a
, b
) secondary index
(columns c
, d
), and
unique index (columns e
,
f
):
CREATE TABLE t1 ( a INT, b INT, c INT, d INT, e INT, f INT, PRIMARY KEY (a, b), KEY i1 (c, d), UNIQUE KEY i2uniq (e, f) ) ENGINE=INNODB;
After inserting five rows of sample data, the table appears as follows:
mysql> SELECT * FROM t1;
+---+---+------+------+------+------+
| a | b | c | d | e | f |
+---+---+------+------+------+------+
| 1 | 1 | 10 | 11 | 100 | 101 |
| 1 | 2 | 10 | 11 | 200 | 102 |
| 1 | 3 | 10 | 11 | 100 | 103 |
| 1 | 4 | 10 | 12 | 200 | 104 |
| 1 | 5 | 10 | 12 | 100 | 105 |
+---+---+------+------+------+------+
To immediately update statistics, run
ANALYZE TABLE
(if
innodb_stats_auto_recalc
is
enabled, statistics are updated automatically within a few
seconds assuming that the 10% threshold for changed table rows
is reached):
mysql> ANALYZE TABLE t1;
+---------+---------+----------+----------+
| Table | Op | Msg_type | Msg_text |
+---------+---------+----------+----------+
| test.t1 | analyze | status | OK |
+---------+---------+----------+----------+
Table statistics for table t1
show the last
time InnoDB
updated the table statistics
(2014-03-14 14:36:34
), the number of rows
in the table (5
), the clustered index size
(1
page), and the combined size of the
other indexes (2
pages).
mysql> SELECT * FROM mysql.innodb_table_stats WHERE table_name like 't1'\G
*************************** 1. row ***************************
database_name: test
table_name: t1
last_update: 2014-03-14 14:36:34
n_rows: 5
clustered_index_size: 1
sum_of_other_index_sizes: 2
The innodb_index_stats
table contains
multiple rows for each index. Each row in the
innodb_index_stats
table provides data
related to a particular index statistic which is named in the
stat_name
column and described in the
stat_description
column. For example:
mysql>SELECT index_name, stat_name, stat_value, stat_description
FROM mysql.innodb_index_stats WHERE table_name like 't1';
+------------+--------------+------------+-----------------------------------+ | index_name | stat_name | stat_value | stat_description | +------------+--------------+------------+-----------------------------------+ | PRIMARY | n_diff_pfx01 | 1 | a | | PRIMARY | n_diff_pfx02 | 5 | a,b | | PRIMARY | n_leaf_pages | 1 | Number of leaf pages in the index | | PRIMARY | size | 1 | Number of pages in the index | | i1 | n_diff_pfx01 | 1 | c | | i1 | n_diff_pfx02 | 2 | c,d | | i1 | n_diff_pfx03 | 2 | c,d,a | | i1 | n_diff_pfx04 | 5 | c,d,a,b | | i1 | n_leaf_pages | 1 | Number of leaf pages in the index | | i1 | size | 1 | Number of pages in the index | | i2uniq | n_diff_pfx01 | 2 | e | | i2uniq | n_diff_pfx02 | 5 | e,f | | i2uniq | n_leaf_pages | 1 | Number of leaf pages in the index | | i2uniq | size | 1 | Number of pages in the index | +------------+--------------+------------+-----------------------------------+
The stat_name
column shows the following
types of statistics:
size
: Where
stat_name
=size
, the
stat_value
column displays the total
number of pages in the index.
n_leaf_pages
: Where
stat_name
=n_leaf_pages
,
the stat_value
column displays the
number of leaf pages in the index.
n_diff_pfx
:
Where
NN
stat_name
=n_diff_pfx01
,
the stat_value
column displays the
number of distinct values in the first column of the
index. Where
stat_name
=n_diff_pfx02
,
the stat_value
column displays the
number of distinct values in the first two columns of the
index, and so on. Additionally, where
stat_name
=n_diff_pfx
,
the NN
stat_description
column shows a
comma separated list of the index columns that are
counted.
To further illustrate the
n_diff_pfx
statistic, which provides cardinality data, consider once
again the NN
t1
table example that was
introduced previously. As shown below, the
t1
table is created with a primary index
(columns a
, b
), a
secondary index (columns c
,
d
), and a unique index (columns
e
, f
):
CREATE TABLE t1 ( a INT, b INT, c INT, d INT, e INT, f INT, PRIMARY KEY (a, b), KEY i1 (c, d), UNIQUE KEY i2uniq (e, f) ) ENGINE=INNODB;
After inserting five rows of sample data, the table appears as follows:
mysql> SELECT * FROM t1;
+---+---+------+------+------+------+
| a | b | c | d | e | f |
+---+---+------+------+------+------+
| 1 | 1 | 10 | 11 | 100 | 101 |
| 1 | 2 | 10 | 11 | 200 | 102 |
| 1 | 3 | 10 | 11 | 100 | 103 |
| 1 | 4 | 10 | 12 | 200 | 104 |
| 1 | 5 | 10 | 12 | 100 | 105 |
+---+---+------+------+------+------+
When you query the index_name
,
stat_name
, stat_value
,
and stat_description
where
stat_name LIKE 'n_diff%'
, the following
result set is returned:
mysql>SELECT index_name, stat_name, stat_value, stat_description
FROM mysql.innodb_index_stats
WHERE table_name like 't1' AND stat_name LIKE 'n_diff%';
+------------+--------------+------------+------------------+ | index_name | stat_name | stat_value | stat_description | +------------+--------------+------------+------------------+ | PRIMARY | n_diff_pfx01 | 1 | a | | PRIMARY | n_diff_pfx02 | 5 | a,b | | i1 | n_diff_pfx01 | 1 | c | | i1 | n_diff_pfx02 | 2 | c,d | | i1 | n_diff_pfx03 | 2 | c,d,a | | i1 | n_diff_pfx04 | 5 | c,d,a,b | | i2uniq | n_diff_pfx01 | 2 | e | | i2uniq | n_diff_pfx02 | 5 | e,f | +------------+--------------+------------+------------------+
For the PRIMARY
index, there are two
n_diff%
rows. The number of rows is equal
to the number of columns in the index.
For nonunique indexes, InnoDB
appends the
columns of the primary key.
Where
index_name
=PRIMARY
and
stat_name
=n_diff_pfx01
,
the stat_value
is 1
,
which indicates that there is a single distinct value in
the first column of the index (column
a
). The number of distinct values in
column a
is confirmed by viewing the
data in column a
in table
t1
, in which there is a single distinct
value (1
). The counted column
(a
) is shown in the
stat_description
column of the result
set.
Where
index_name
=PRIMARY
and
stat_name
=n_diff_pfx02
,
the stat_value
is 5
,
which indicates that there are five distinct values in the
two columns of the index (a,b
). The
number of distinct values in columns a
and b
is confirmed by viewing the data
in columns a
and b
in table t1
, in which there are five
distinct values: (1,1
),
(1,2
), (1,3
),
(1,4
) and (1,5
). The
counted columns (a,b
) are shown in the
stat_description
column of the result
set.
For the secondary index (i1
), there are
four n_diff%
rows. Only two columns are
defined for the secondary index (c,d
) but
there are four n_diff%
rows for the
secondary index because InnoDB
suffixes all
nonunique indexes with the primary key. As a result, there are
four n_diff%
rows instead of two to account
for the both the secondary index columns
(c,d
) and the primary key columns
(a,b
).
Where index_name
=i1
and
stat_name
=n_diff_pfx01
,
the stat_value
is 1
,
which indicates that there is a single distinct value in
the first column of the index (column
c
). The number of distinct values in
column c
is confirmed by viewing the
data in column c
in table
t1
, in which there is a single distinct
value: (10
). The counted column
(c
) is shown in the
stat_description
column of the result
set.
Where index_name
=i1
and
stat_name
=n_diff_pfx02
,
the stat_value
is 2
,
which indicates that there are two distinct values in the
first two columns of the index (c,d
).
The number of distinct values in columns
c
an d
is confirmed
by viewing the data in columns c
and
d
in table t1
, in
which there are two distinct values:
(10,11
) and (10,12
).
The counted columns (c,d
) are shown in
the stat_description
column of the
result set.
Where index_name
=i1
and
stat_name
=n_diff_pfx03
,
the stat_value
is 2
,
which indicates that there are two distinct values in the
first three columns of the index
(c,d,a
). The number of distinct values
in columns c
, d
, and
a
is confirmed by viewing the data in
column c
, d
, and
a
in table t1
, in
which there are two distinct values:
(10,11,1
) and
(10,12,1
). The counted columns
(c,d,a
) are shown in the
stat_description
column of the result
set.
Where index_name
=i1
and
stat_name
=n_diff_pfx04
,
the stat_value
is 5
,
which indicates that there are five distinct values in the
four columns of the index (c,d,a,b
).
The number of distinct values in columns
c
, d
,
a
and b
is confirmed
by viewing the data in columns c
,
d
, a
, and
b
in table t1
, in
which there are five distinct values:
(10,11,1,1
),
(10,11,1,2
),
(10,11,1,3
),
(10,12,1,4
) and
(10,12,1,5
). The counted columns
(c,d,a,b
) are shown in the
stat_description
column of the result
set.
For the unique index (i2uniq
), there are
two n_diff%
rows.
Where
index_name
=i2uniq
and
stat_name
=n_diff_pfx01
,
the stat_value
is 2
,
which indicates that there are two distinct values in the
first column of the index (column e
).
The number of distinct values in column
e
is confirmed by viewing the data in
column e
in table
t1
, in which there are two distinct
values: (100
) and
(200
). The counted column
(e
) is shown in the
stat_description
column of the result
set.
Where
index_name
=i2uniq
and
stat_name
=n_diff_pfx02
,
the stat_value
is 5
,
which indicates that there are five distinct values in the
two columns of the index (e,f
). The
number of distinct values in columns e
and f
is confirmed by viewing the data
in columns e
and f
in table t1
, in which there are five
distinct values: (100,101
),
(200,102
),
(100,103
), (200,104
)
and (100,105
). The counted columns
(e,f
) are shown in the
stat_description
column of the result
set.
The size of indexes for tables, partitions, or subpartitions
can be retrieved using the
innodb_index_stats
table. In the following
example, index sizes are retrieved for table
t1
. For a definition of table
t1
and corresponding index statistics, see
Section 14.6.12.1.6, “InnoDB Persistent Statistics Tables Example”.
mysql>SELECT SUM(stat_value) pages, index_name,
SUM(stat_value)*@@innodb_page_size size
FROM mysql.innodb_index_stats WHERE table_name='t1'
AND stat_name = 'size' GROUP BY index_name;
+-------+------------+-------+ | pages | index_name | size | +-------+------------+-------+ | 1 | PRIMARY | 16384 | | 1 | i1 | 16384 | | 1 | i2uniq | 16384 | +-------+------------+-------+
For partitions or subpartitions, the same query with a
modified WHERE
clause can be used to
retrieve index sizes. For example, the following query
retrieves index sizes for partitions of table
t1
:
mysql>SELECT SUM(stat_value) pages, index_name,
SUM(stat_value)*@@innodb_page_size size
FROM mysql.innodb_index_stats WHERE table_name like 't1#P%'
AND stat_name = 'size' GROUP BY index_name;
This section describes how to configure non-persistent optimizer
statistics. Optimizer statistics are not persisted to disk when
innodb_stats_persistent=OFF
or
when individual tables are created or altered with
STATS_PERSISTENT=0
.
Instead, statistics are stored in memory, and are lost when the
server is shut down. Statistics are also updated periodically by
certain operations and under certain conditions.
As of MySQL 5.6.6, optimizer statistics are persisted to disk by
default, enabled by the
innodb_stats_persistent
configuration option. For information about persistent optimizer
statistics, see Section 14.6.12.1, “Configuring Persistent Optimizer Statistics Parameters”.
Non-persistent optimizer statistics are updated when:
Running ANALYZE TABLE
.
Running SHOW TABLE STATUS
,
SHOW INDEX
, or querying the
INFORMATION_SCHEMA.TABLES
or
INFORMATION_SCHEMA.STATISTICS
tables with the
innodb_stats_on_metadata
option enabled.
The default setting for
innodb_stats_on_metadata
was changed to OFF
when persistent
optimizer statistics were enabled by default in MySQL 5.6.6.
Enabling
innodb_stats_on_metadata
may reduce access speed for schemas that have a large number
of tables or indexes, and reduce stability of execution
plans for queries that involve InnoDB
tables.
innodb_stats_on_metadata
is
configured globally using a
SET
statement.
SET GLOBAL innodb_stats_on_metadata=ON
innodb_stats_on_metadata
only applies when optimizer
statistics are
configured to be non-persistent (when
innodb_stats_persistent
is disabled).
Starting a mysql client with the
--auto-rehash
option enabled,
which is the default. The
auto-rehash
option causes all
InnoDB
tables to be opened, and the open
table operations cause statistics to be recalculated.
To improve the start up time of the mysql
client and to updating statistics, you can turn off
auto-rehash
using the
--disable-auto-rehash
option. The auto-rehash
feature enables automatic name completion of database,
table, and column names for interactive users.
A table is first opened.
InnoDB
detects that 1 / 16 of table has
been modified since the last time statistics were updated.
The MySQL query optimizer uses estimated
statistics about key
distributions to choose the indexes for an execution plan, based
on the relative
selectivity of the
index. When InnoDB
updates optimizer
statistics, it samples random pages from each index on a table
to estimate the
cardinality of the
index. (This technique is known as
random dives.)
To give you control over the quality of the statistics estimate
(and thus better information for the query optimizer), you can
change the number of sampled pages using the parameter
innodb_stats_transient_sample_pages
.
The default number of sampled pages is 8, which could be
insufficient to produce an accurate estimate, leading to poor
index choices by the query optimizer. This technique is
especially important for large tables and tables used in
joins. Unnecessary
full table scans for
such tables can be a substantial performance issue. See
Section 8.2.1.19, “Avoiding Full Table Scans” for tips on tuning such
queries.
innodb_stats_transient_sample_pages
is a global parameter that can be set at runtime.
The value of
innodb_stats_transient_sample_pages
affects the index sampling for all InnoDB
tables and indexes when
innodb_stats_persistent=0
. Be
aware of the following potentially significant impacts when you
change the index sample size:
Small values like 1 or 2 can result in inaccurate estimates of cardinality.
Increasing the
innodb_stats_transient_sample_pages
value might require more disk reads. Values much larger
than 8 (say, 100), can cause a significant slowdown in the
time it takes to open a table or execute SHOW
TABLE STATUS
.
The optimizer might choose very different query plans based on different estimates of index selectivity.
Whatever value of
innodb_stats_transient_sample_pages
works best for a system, set the option and leave it at that
value. Choose a value that results in reasonably accurate
estimates for all tables in your database without requiring
excessive I/O. Because the statistics are automatically
recalculated at various times other than on execution of
ANALYZE TABLE
, it does not make
sense to increase the index sample size, run
ANALYZE TABLE
, then decrease
sample size again.
Smaller tables generally require fewer index samples than larger
tables. If your database has many large tables, consider using a
higher value for
innodb_stats_transient_sample_pages
than if you have mostly smaller tables.
ANALYZE TABLE
complexity for
InnoDB
tables is dependent on:
The number of pages sampled, as defined by
innodb_stats_persistent_sample_pages
.
The number of indexed columns in a table
The number of partitions. If a table has no partitions, the number of partitions is considered to be 1.
Using these parameters, an approximate formula for estimating
ANALYZE TABLE
complexity would
be:
The value of
innodb_stats_persistent_sample_pages
* number of indexed columns in a table * the number of
partitions
Typically, the greater the resulting value, the greater the
execution time for ANALYZE TABLE
.
innodb_stats_persistent_sample_pages
defines the number of pages sampled at a global level. To set
the number of pages sampled for an individual table, use the
STATS_SAMPLE_PAGES
option with
CREATE TABLE
or
ALTER TABLE
. For more
information, see Section 14.6.12.1, “Configuring Persistent Optimizer Statistics Parameters”.
If
innodb_stats_persistent=OFF
,
the number of pages sampled is defined by
innodb_stats_transient_sample_pages
.
See Section 14.6.12.2, “Configuring Non-Persistent Optimizer Statistics Parameters” for
additional information.
For a more in-depth approach to estimating ANALYZE
TABLE
complexity, consider the following example.
In Big
O notation, ANALYZE TABLE
complexity is described as:
O(n_sample * (n_cols_in_uniq_i + n_cols_in_non_uniq_i + n_cols_in_pk * (1 + n_non_uniq_i)) * n_part)
where:
n_sample
is the number of pages sampled
(defined by
innodb_stats_persistent_sample_pages
)
n_cols_in_uniq_i
is total number of all
columns in all unique indexes (not counting the primary key
columns)
n_cols_in_non_uniq_i
is the total number
of all columns in all nonunique indexes
n_cols_in_pk
is the number of columns in
the primary key (if a primary key is not defined,
InnoDB
creates a single column primary
key internally)
n_non_uniq_i
is the number of nonunique
indexes in the table
n_part
is the number of partitions. If no
partitions are defined, the table is considered to be a
single partition.
Now, consider the following table (table t
),
which has a primary key (2 columns), a unique index (2 columns),
and two nonunique indexes (two columns each):
CREATE TABLE t ( a INT, b INT, c INT, d INT, e INT, f INT, g INT, h INT, PRIMARY KEY (a, b), UNIQUE KEY i1uniq (c, d), KEY i2nonuniq (e, f), KEY i3nonuniq (g, h) );
For the column and index data required by the algorithm
described above, query the
mysql.innodb_index_stats
persistent index
statistics table for table t
. The
n_diff_pfx%
statistics show the columns that
are counted for each index. For example, columns
a
and b
are counted for
the primary key index. For the nonunique indexes, the primary
key columns (a,b) are counted in addition to the user defined
columns.
For additional information about the InnoDB
persistent statistics tables, see
Section 14.6.12.1, “Configuring Persistent Optimizer Statistics Parameters”
mysql>SELECT index_name, stat_name, stat_description
FROM mysql.innodb_index_stats WHERE
database_name='test' AND
table_name='t' AND
stat_name like 'n_diff_pfx%';
+------------+--------------+------------------+ | index_name | stat_name | stat_description | +------------+--------------+------------------+ | PRIMARY | n_diff_pfx01 | a | | PRIMARY | n_diff_pfx02 | a,b | | i1uniq | n_diff_pfx01 | c | | i1uniq | n_diff_pfx02 | c,d | | i2nonuniq | n_diff_pfx01 | e | | i2nonuniq | n_diff_pfx02 | e,f | | i2nonuniq | n_diff_pfx03 | e,f,a | | i2nonuniq | n_diff_pfx04 | e,f,a,b | | i3nonuniq | n_diff_pfx01 | g | | i3nonuniq | n_diff_pfx02 | g,h | | i3nonuniq | n_diff_pfx03 | g,h,a | | i3nonuniq | n_diff_pfx04 | g,h,a,b | +------------+--------------+------------------+
Based on the index statistics data shown above and the table definition, the following values can be determined:
n_cols_in_uniq_i
, the total number of all
columns in all unique indexes not counting the primary key
columns, is 2 (c
and
d
)
n_cols_in_non_uniq_i
, the total number of
all columns in all nonunique indexes, is 4
(e
, f
,
g
and h
)
n_cols_in_pk
, the number of columns in
the primary key, is 2 (a
and
b
)
n_non_uniq_i
, the number of nonunique
indexes in the table, is 2 (i2nonuniq
and
i3nonuniq
))
n_part
, the number of partitions, is 1.
You can now calculate
innodb_stats_persistent_sample_pages
* (2 + 4
+ 2 * (1 + 2)) * 1 to determine the number of leaf pages that
are scanned. With
innodb_stats_persistent_sample_pages
set to
the default value of 20
, and with a default
page size of 16 KiB
(innodb_page_size
=16384), you
can then estimate that 20 * 12 * 16384 bytes
are read for table t
, or about 4
MiB
.
All 4 MiB
may not be read from disk, as
some leaf pages may already be cached in the buffer pool.
You can configure the MERGE_THRESHOLD
value for
index pages. If the “page-full” percentage for an
index page falls below the MERGE_THRESHOLD
value when a row is deleted or when a row is shortened by an
UPDATE
operation,
InnoDB
attempts to merge the index page with a
neighboring index page. The default
MERGE_THRESHOLD
value is 50, which is the
previously hardcoded value. The minimum
MERGE_THRESHOLD
value is 1 and the maximum
value is 50.
When the “page-full” percentage for an index page
falls below 50%, which is the default
MERGE_THRESHOLD
setting,
InnoDB
attempts to merge the index page with a
neighboring page. If both pages are close to 50% full, a page
split can occur soon after the pages are merged. If this
merge-split behavior occurs frequently, it can have an adverse
affect on performance. To avoid frequent merge-splits, you can
lower the MERGE_THRESHOLD
value so that
InnoDB
attempts page merges at a lower
“page-full” percentage. Merging pages at a lower
page-full percentage leaves more room in index pages and helps
reduce merge-split behavior.
The MERGE_THRESHOLD
for index pages can be
defined for a table or for individual indexes. A
MERGE_THRESHOLD
value defined for an individual
index takes priority over a MERGE_THRESHOLD
value defined for the table. If undefined, the
MERGE_THRESHOLD
value defaults to 50.
You can set the MERGE_THRESHOLD
value for a
table using the table_option
COMMENT
clause of the
CREATE TABLE
statement. For
example:
CREATE TABLE t1 ( id INT, KEY id_index (id) ) COMMENT='MERGE_THRESHOLD=45';
You can also set the MERGE_THRESHOLD
value for
an existing table using the
table_option
COMMENT
clause with ALTER TABLE
:
CREATE TABLE t1 ( id INT, KEY id_index (id) ); ALTER TABLE t1 COMMENT='MERGE_THRESHOLD=40';
To set the MERGE_THRESHOLD
value for an
individual index, you can use the
index_option
COMMENT
clause with CREATE TABLE
,
ALTER TABLE
, or
CREATE INDEX
, as shown in the
following examples:
Setting MERGE_THRESHOLD
for an individual
index using CREATE TABLE
:
CREATE TABLE t1 ( id INT, KEY id_index (id) COMMENT 'MERGE_THRESHOLD=40' );
Setting MERGE_THRESHOLD
for an individual
index using ALTER TABLE
:
CREATE TABLE t1 ( id INT, KEY id_index (id) ); ALTER TABLE t1 DROP KEY id_index; ALTER TABLE t1 ADD KEY id_index (id) COMMENT 'MERGE_THRESHOLD=40';
Setting MERGE_THRESHOLD
for an individual
index using CREATE INDEX
:
CREATE TABLE t1 (id INT); CREATE INDEX id_index ON t1 (id) COMMENT 'MERGE_THRESHOLD=40';
You cannot modify the MERGE_THRESHOLD
value
at the index level for GEN_CLUST_INDEX
, which
is the clustered index created by InnoDB
when
an InnoDB
table is created without a primary
key or unique key index. You can only modify the
MERGE_THRESHOLD
value for
GEN_CLUST_INDEX
by setting
MERGE_THRESHOLD
for the table.
The current MERGE_THRESHOLD
value for an index
can be obtained by querying the
INNODB_SYS_INDEXES
table. For
example:
mysql> SELECT * FROM INFORMATION_SCHEMA.INNODB_SYS_INDEXES WHERE NAME='id_index' \G
*************************** 1. row ***************************
INDEX_ID: 91
NAME: id_index
TABLE_ID: 68
TYPE: 0
N_FIELDS: 1
PAGE_NO: 4
SPACE: 57
MERGE_THRESHOLD: 40
You can use SHOW CREATE TABLE
to
view the MERGE_THRESHOLD
value for a table, if
explicitly defined using the
table_option
COMMENT
clause:
mysql> SHOW CREATE TABLE t2 \G
*************************** 1. row ***************************
Table: t2
Create Table: CREATE TABLE `t2` (
`id` int(11) DEFAULT NULL,
KEY `id_index` (`id`) COMMENT 'MERGE_THRESHOLD=40'
) ENGINE=InnoDB DEFAULT CHARSET=latin1
A MERGE_THRESHOLD
value defined at the index
level takes priority over a MERGE_THRESHOLD
value defined for the table. If undefined,
MERGE_THRESHOLD
defaults to 50%
(MERGE_THRESHOLD=50
, which is the previously
hardcoded value.
Likewise, you can use SHOW INDEX
to
view the MERGE_THRESHOLD
value for an index, if
explicitly defined using the
index_option
COMMENT
clause:
mysql> SHOW INDEX FROM t2 \G
*************************** 1. row ***************************
Table: t2
Non_unique: 1
Key_name: id_index
Seq_in_index: 1
Column_name: id
Collation: A
Cardinality: 0
Sub_part: NULL
Packed: NULL
Null: YES
Index_type: BTREE
Comment:
Index_comment: MERGE_THRESHOLD=40
The INNODB_METRICS
table provides two
counters that can be used to measure the effect of a
MERGE_THRESHOLD
setting on index page merges.
mysql>SELECT NAME, COMMENT FROM INFORMATION_SCHEMA.INNODB_METRICS
WHERE NAME like '%index_page_merge%';
+-----------------------------+----------------------------------------+ | NAME | COMMENT | +-----------------------------+----------------------------------------+ | index_page_merge_attempts | Number of index page merge attempts | | index_page_merge_successful | Number of successful index page merges | +-----------------------------+----------------------------------------+
When lowering the MERGE_THRESHOLD
value, the
objectives are:
A smaller number of page merge attempts and successful page merges
A similar number of page merge attempts and successful page merges
A MERGE_THRESHOLD
setting that is too small
could result in large data files due to an excessive amount of
empty page space.
For information about using
INNODB_METRICS
counters, see
Section 14.15.6, “InnoDB INFORMATION_SCHEMA Metrics Table”.
This section covers topics related to InnoDB
tablespaces.
This section describes how to increase or decrease the size of the
InnoDB
system tablespace.
The easiest way to increase the size of the
InnoDB
system 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 64MB 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 megabytes.
You can expand the system tablespace by a defined amount by adding another data file:
Shut down the MySQL server.
If the previous last data file is defined with the keyword
autoextend
, change its definition to use a
fixed size, based on how large it has actually grown. Check
the size of the data file, round it down to the closest
multiple of 1024 × 1024 bytes (= 1MB), and specify this
rounded size explicitly in
innodb_data_file_path
.
Add a new data file to the end of
innodb_data_file_path
,
optionally making that file auto-extending. Only the last data
file in the
innodb_data_file_path
can be
specified as auto-extending.
Start the MySQL server again.
For example, this 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 use a fixed size and adding a new auto-extending data file:
innodb_data_home_dir = innodb_data_file_path = /ibdata/ibdata1:988M;/disk2/ibdata2:50M:autoextend
When you add a new data file to the system tablespace
configuration, make sure that the filename does not refer to an
existing file. InnoDB
creates and initializes
the file when you restart the server.
You cannot remove a data file from the system tablespace. To decrease the system tablespace size, use this procedure:
Use mysqldump to dump all your
InnoDB
tables, including
InnoDB
tables located in the MySQL
database. As of 5.6, there are five InnoDB
tables included in the MySQL database:
mysql> SELECT TABLE_NAME from INFORMATION_SCHEMA.TABLES WHERE TABLE_SCHEMA='mysql' and ENGINE='InnoDB';
+---------------------------+
| TABLE_NAME |
+---------------------------+
| engine_cost |
| gtid_executed |
| help_category |
| help_keyword |
| help_relation |
| help_topic |
| innodb_index_stats |
| innodb_table_stats |
| plugin |
| server_cost |
| servers |
| slave_master_info |
| slave_relay_log_info |
| slave_worker_info |
| time_zone |
| time_zone_leap_second |
| time_zone_name |
| time_zone_transition |
| time_zone_transition_type |
+---------------------------+
Stop the server.
Remove all the existing tablespace files
(*.ibd
), including the
ibdata
and ib_log
files. Do not forget to remove *.ibd
files for tables located in the MySQL database.
Remove any .frm
files for
InnoDB
tables.
Configure a new tablespace.
Restart the server.
Import the dump files.
If your databases only use the InnoDB
engine,
it may be simpler to dump all
databases, stop the server, remove all databases and
InnoDB
log files, restart the server, and
import the dump files.
To change the number or the size of your InnoDB
redo log files, perform the
following steps:
Stop the MySQL server and make sure that it shuts down without errors.
Edit my.cnf
to change the log file
configuration. To change the log file size, configure
innodb_log_file_size
. To
increase the number of log files, configure
innodb_log_files_in_group
.
Start the MySQL server again.
If InnoDB
detects that the
innodb_log_file_size
differs from
the redo log file size, it writes a log checkpoint, closes and
removes the old log files, creates new log files at the requested
size, and opens the new log files.
You can use raw disk partitions as data files in the
InnoDB
system tablespace.
This technique enables nonbuffered I/O on Windows and on some
Linux and Unix systems without file system overhead. Perform tests
with and without raw partitions to verify whether this change
actually improves performance on your system.
When you use a raw disk partition, ensure that the user ID that
runs the MySQL server has read and write privileges for that
partition. For example, if you run the server as the
mysql
user, the partition must be readable and
writeable by mysql
. If you run the server with
the --memlock
option, the server
must be run as root
, so the partition must be
readable and writeable by root
.
The procedures described below involve option file modification. For additional information, see Section 4.2.6, “Using Option Files”.
When you create a new data file, specify the keyword
newraw
immediately after the data file size
for the innodb_data_file_path
option. 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
Restart 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/hdd1:3Graw;/dev/hdd2:2Graw
Restart the server. InnoDB
now permits
changes to be made.
On Windows systems, the same steps and accompanying guidelines
described for Linux and Unix systems apply except that the
innodb_data_file_path
setting
differs slightly on Windows.
When you create a new data file, specify the keyword
newraw
immediately after the data file size
for the innodb_data_file_path
option:
[mysqld] innodb_data_home_dir= innodb_data_file_path=//./D::10Gnewraw
The //./
corresponds to the Windows
syntax of \\.\
for accessing physical
drives. In the example above, D:
is the
drive letter of the partition.
Restart the server. InnoDB
notices the
newraw
keyword and initializes the new
partition.
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=//./D::10Graw
Restart the server. InnoDB
now permits
changes to be made.
Historically, all InnoDB
tables and indexes
were stored in the system
tablespace. This monolithic approach was targeted at
machines dedicated entirely to database processing, with carefully
planned data growth, where any disk storage allocated to MySQL
would never be needed for other purposes.
InnoDB
's
file-per-table
tablespace feature provides a more flexible alternative,
where each InnoDB
table and its indexes are
stored in a separate
.ibd
data
file. Each such
.ibd
data
file represents an individual
tablespace. This feature is
controlled by the
innodb_file_per_table
configuration option, which is enabled by default in MySQL 5.6.6
and higher.
You can reclaim disk space when truncating or dropping a table
stored in a file-per-table tablepace. Truncating or dropping
tables stored in the shared
system
tablespace creates free space internally in the system
tablespace data files (ibdata
files) which can only be used for new
InnoDB
data.
Similarly, a table-copying ALTER
TABLE
operation on table that resides in a shared
tablespace can increase the amount of space used by the
tablespace. Such operations may require as much additional
space as the data in the table plus indexes. The additional
space required for the table-copying
ALTER TABLE
operation is not
released back to the operating system as it is for
file-per-table tablespaces.
The TRUNCATE TABLE
operation is
faster when run on tables stored in file-per-table tablepaces.
You can store specific tables on separate storage devices, for
I/O optimization, space management, or backup purposes. In
previous releases, you had to move entire database directories
to other drives and create symbolic links in the MySQL data
directory, as described in Section 8.12.3, “Using Symbolic Links”.
In MySQL 5.6.6 and higher, you can specify the location of
each table using the syntax CREATE TABLE ... DATA
DIRECTORY =
,
as explained in Section 14.7.5, “Creating File-Per-Table Tablespaces Outside the Data Directory”.
absolute_path_to_directory
You can run OPTIMIZE TABLE
to
compact or recreate a file-per-table tablespace. When you run
an OPTIMIZE TABLE
,
InnoDB
creates a new
.ibd
file with a temporary name, using
only the space required to store actual data. When the
optimization is complete, InnoDB
removes
the old .ibd
file and replaces it with
the new one. If the previous .ibd
file
grew significantly but the actual data only accounted for a
portion of its size, running OPTIMIZE
TABLE
can reclaim the unused space.
You can move individual InnoDB
tables
rather than entire databases.
You can copy individual InnoDB
tables from
one MySQL instance to another (known as the
transportable
tablespace feature).
Tables created in file-per-table tablespaces use the Barracuda file format. The Barracuda file format enables features such as compressed and dynamic row formats.
You can enable more efficient storage for tables with large
BLOB
or TEXT
columns
using the dynamic row
format.
File-per-table tablespaces may improve chances for a successful recovery and save time when a corruption occurs, when a server cannot be restarted, or when backup and binary logs are unavailable.
File-per-table tablespaces are convenient for per-table status reporting when copying or backing up tables.
You can monitor table size at a file system level, without accessing MySQL.
Common Linux file systems do not permit concurrent writes to a
single file when
innodb_flush_method
is set to
O_DIRECT
. As a result, there are possible
performance improvements when using file-per-table tablespaces
in conjunction with
innodb_flush_method
.
The system tablespace stores the data dictionary and undo
logs, and is limited in size by InnoDB
tablespace size limits. See
Section 14.8.1.7, “Limits on InnoDB Tables”. With file-per-table
tablespaces, each table has its own tablespace, which provides
room for growth.
With file-per-table tablespaces, each table may have unused space, which can only be utilized by rows of the same table. This could lead to wasted space if not properly managed.
fsync
operations must run on each open
table rather than on a single file. Because there is a
separate fsync
operation for each file,
write operations on multiple tables cannot be combined into a
single I/O operation. This may require
InnoDB
to perform a higher total number of
fsync
operations.
mysqld must keep one open file handle per table, which may impact performance if you have numerous tables in file-per-table tablespaces.
More file descriptors are used.
innodb_file_per_table
is
enabled by default in MySQL 5.6.6 and higher. You may consider
disabling it if backward compatibility with MySQL 5.5 or 5.1
is a concern. Disabling
innodb_file_per_table
prevents ALTER TABLE
from
moving an InnoDB
table from the system
tablespace to an individual .ibd
file in
cases where ALTER TABLE
recreates the table (ALGORITHM=COPY
).
For example, when restructuring the clustered index for an
InnoDB
table, the table is re-created using
the current setting for
innodb_file_per_table
. This
behavior does not apply when adding or dropping
InnoDB
secondary indexes. When a secondary
index is created without rebuilding the table, the index is
stored in the same file as the table data, regardless of the
current innodb_file_per_table
setting. This behavior also does not apply to tables added to
the system tablespace using
CREATE TABLE ...
TABLESPACE
or
ALTER TABLE ...
TABLESPACE
syntax. These tables are not affected by
the innodb_file_per_table
setting.
If many tables are growing there is potential for more
fragmentation which can impede DROP
TABLE
and table scan performance. However, when
fragmentation is managed, having files in their own tablespace
can improve performance.
The buffer pool is scanned when dropping a file-per-table tablespace, which can take several seconds for buffer pools that are tens of gigabytes in size. The scan is performed with a broad internal lock, which may delay other operations. Tables in the system tablespace are not affected.
The
innodb_autoextend_increment
variable, which defines increment size (in MB) for extending
the size of an auto-extending shared tablespace file when it
becomes full, does not apply to file-per-table tablespace
files, which are auto-extending regardless of the
innodb_autoextend_increment
setting. The initial extensions are by small amounts, after
which extensions occur in increments of 4MB.
The innodb_file_per_table
option is enabled by default.
To set the
innodb_file_per_table
option at
startup, start the server with the
--innodb_file_per_table
command-line option, or add this line to the
[mysqld]
section of
my.cnf
:
[mysqld] innodb_file_per_table=1
You can also set
innodb_file_per_table
dynamically, while the server is running:
mysql> SET GLOBAL innodb_file_per_table=1;
With innodb_file_per_table
enabled, you can store InnoDB
tables in a
file. Unlike the tbl_name
.ibdMyISAM
storage engine, with
its separate
and
tbl_name
.MYD
files for indexes and data, tbl_name
.MYIInnoDB
stores the
data and the indexes together in a single
.ibd
file. The
file is still created as usual.
tbl_name
.frm
If you disable
innodb_file_per_table
in your
startup options and restart the server, or disable it with the
SET GLOBAL
command, InnoDB
creates new tables inside the system tablespace unless you have
explicitly placed the table in file-per-table tablespace or
general tablespace using the
CREATE TABLE ...
TABLESPACE
option.
You can always read and write any InnoDB
tables, regardless of the file-per-table setting.
To move a table from the system tablespace to its own
tablespace, change the
innodb_file_per_table
setting
and rebuild the table:
mysql>SET GLOBAL innodb_file_per_table=1;
mysql>ALTER TABLE
table_name
ENGINE=InnoDB;
Tables added to the system tablespace using
CREATE TABLE ...
TABLESPACE
or
ALTER TABLE ...
TABLESPACE
syntax are not affected by the
innodb_file_per_table
setting.
To move these tables from the system tablespace to a
file-per-table tablespace, they must be moved explicitly using
ALTER TABLE ...
TABLESPACE
syntax.
InnoDB
always needs the system tablespace
because it puts its internal
data dictionary
and undo logs there. The
.ibd
files are not sufficient for
InnoDB
to operate.
When a table is moved out of the system tablespace into its
own .ibd
file, the data files that make
up the system tablespace remain the same size. The space
formerly occupied by the table can be reused for new
InnoDB
data, but is not reclaimed for use
by the operating system. When moving large
InnoDB
tables out of the system tablespace,
where disk space is limited, you may prefer to enable
innodb_file_per_table
and
recreate the entire instance using the
mysqldump command. As mentioned above,
tables added to the system tablespace using
CREATE TABLE ...
TABLESPACE
or
ALTER TABLE ...
TABLESPACE
syntax are not affected by the
innodb_file_per_table
setting. These tables must be moved individually.
To create a
file-per-table
tablespace in a location outside the MySQL data directory, use the
DATA DIRECTORY =
clause of the absolute_path_to_directory
CREATE TABLE
statement.
Plan the location in advance, because you cannot use the
DATA DIRECTORY
clause with the
ALTER TABLE
statement to change the
location later. The directory you specify could be on another
storage device with particular performance or capacity
characteristics, such as a fast
SSD or a high-capacity
HDD.
Within the target directory, MySQL creates a subdirectory
corresponding to the database name, and within that, a
.ibd file for the new table.
In the database directory beneath the MySQL
DATADIR
directory, MySQL creates
a
file containing the path name for the table. The
.isl file is treated by MySQL
like a symbolic link. (Using actual
symbolic links has never been supported for
table_name
.islInnoDB
tables.)
The following example demonstrates creating a file-per-table
tablespace outside the MySQL data directory. It shows the
.ibd
file created in the specified directory,
and the .isl
file created in the database
directory beneath the MySQL data directory.
mysql>USE test;
Database changed mysql>SHOW VARIABLES LIKE 'innodb_file_per_table';
+-----------------------+-------+ | Variable_name | Value | +-----------------------+-------+ | innodb_file_per_table | ON | +-----------------------+-------+ mysql>CREATE TABLE t1 (c1 INT PRIMARY KEY) DATA DIRECTORY = '
# MySQL creates a .ibd file for the new table in a subdirectory that corresponding # to the database name db_user@ubuntu:~/alternative/directory/test$/alternative/directory
';ls
t1.ibd # MySQL creates a .isl file containing the path name for the table in a directory # beneath the MySQL data directory db_user@ubuntu:~/mysql/data/test$ls
db.opt t1.frm t1.isl
You can also use
CREATE TABLE ...
TABLESPACE
in combination with the DATA
DIRECTORY
clause to create a file-per-table tablespace
outside the MySQL data directory. To do so, you must specify
innodb_file_per_table
as the tablespace name.
mysql>CREATE TABLE t2 (c1 INT PRIMARY KEY) TABLESPACE = innodb_file_per_table
DATA DIRECTORY = '/alternative/directory';
You do not have to enable
innodb_file_per_table
when using
this method.
MySQL initially holds the .ibd
file open,
preventing you from dismounting the device, but might
eventually close the table if the server is busy. Be careful
not to accidentally dismount an external device while MySQL is
running, or start MySQL while the device is disconnected.
Attempting to access a table when the associated
.ibd
file is missing causes a serious error
that requires a server restart.
A server restart might fail if the .ibd
file is still not at the expected path. In this case, manually
remove the
file in the database directory, and after restarting perform a
table_name
.islDROP TABLE
to delete the
.frm
file and remove the information
about the table from the
data dictionary.
Before placing tables on an NFS-mounted volume, review potential issues outlined in Using NFS with MySQL.
If you use an LVM snapshot, file copy, or other file-based
mechanism to back up the .ibd
file, always
use the
FLUSH
TABLES ... FOR EXPORT
statement first to make sure
that all changes buffered in memory are
flushed to disk before the
backup occurs.
The DATA DIRECTORY
clause is a supported
alternative to using symbolic
links, which is not supported for individual
InnoDB
tables.
This section describes how to copy a file-per-table tablespace from one MySQL instance to another, otherwise known as the Transportable Tablespaces feature.
For information about other InnoDB
table
copying methods, see Section 14.8.1.3, “Moving or Copying InnoDB Tables”.
There are many reasons why you might copy an
InnoDB
file-per-table
tablespace to a different instance:
To run reports without putting extra load on a production server.
To set up identical data for a table on a new slave server.
To restore a backed-up version of a table or partition after a problem or mistake.
As a faster way of moving data around than importing the results of a mysqldump command. The data is available immediately, rather than having to be re-inserted and the indexes rebuilt.
To move a file-per-table tablespace to a server with storage medium that better suits system requirements. For example, you may want to have busy tables on an SSD device, or large tables on a high-capacity HDD device.
The tablespace copy procedure is only possible when
innodb_file_per_table
is set
to ON
, which is the default setting. Tables
residing in the shared system tablespace cannot be quiesced.
When a table is quiesced, only read-only transactions are allowed on the affected table.
When importing a tablespace, the page size must match the page size of the importing instance.
DISCARD TABLESPACE
is not supported for
tablespaces with a parent-child (primary key-foreign key)
relationship when
foreign_key_checks
is set to
1
. Before discarding a tablespace for
parent-child tables, set
foreign_key_checks=0
. Partitioned
InnoDB
tables do not support foreign keys.
ALTER TABLE ...
IMPORT TABLESPACE
does not enforce foreign key
constraints on imported data. If there are foreign key
constraints between tables, all tables should be exported at
the same (logical) point in time. Partitioned
InnoDB
tables do not support foreign keys.
ALTER TABLE ...
IMPORT TABLESPACE
and
ALTER TABLE ...
IMPORT PARTITION ... TABLESPACE
do not require a
.cfg
metadata file to import a
tablespace. However, metadata checks are not performed when
importing without a .cfg
file, and a
warning similar to the following is issued:
Message: InnoDB: IO Read error: (2, No such file or directory) Error opening '.\ test\t.cfg', will attempt to import without schema verification 1 row in set (0.00 sec)
The ability to import without a .cfg
file
may be more convenient when no schema mismatches are expected.
Additionally, the ability to import without a
.cfg
file could be useful in crash
recovery scenarios in which metadata cannot be collected from
an .ibd
file.
Due to a .cfg
metadata file limitation,
schema mismatches are not reported for partition type or
partition definition differences when importing tablespace
files for partitioned tables. Column differences are reported.
When running
ALTER TABLE ...
DISCARD PARTITION ... TABLESPACE
and
ALTER TABLE ...
IMPORT PARTITION ... TABLESPACE
on subpartitioned
tables, both partition and subpartition table names are
allowed. When a partition name is specified, subpartitions of
that partition are included in the operation.
Importing a tablespace file from another MySQL server instance works if both instances have GA (General Availability) status and their versions are within the same series. Otherwise, the file must have been created on the same server instance into which it is imported.
In replication scenarios,
innodb_file_per_table
must be
set to ON
on both the master and slave.
On Windows, InnoDB
stores database,
tablespace, and table names internally in lowercase. To avoid
import problems on case-sensitive operating systems such as
Linux and UNIX, create all databases, tablespaces, and tables
using lowercase names. 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 databases,
tablespaces, or tables:
[mysqld] lower_case_table_names=1
ALTER TABLE ...
DISCARD TABLESPACE
and
ALTER TABLE
...IMPORT TABLESPACE
are not supported with tables
that belong to an InnoDB
general
tablespace. For more information, see
CREATE TABLESPACE
.
The default row format for InnoDB
tables is
configurable using the
innodb_default_row_format
configuration option. Attempting to import a table that does
not explicitly define a row format
(ROW_FORMAT
), or that uses
ROW_FORMAT=DEFAULT
, could result in a
schema mismatch error if the
innodb_default_row_format
setting on the source instance differs from the setting on the
destination instance. For related information, see
Section 14.11.2, “Specifying the Row Format for a Table”.
When exporting a tablespace that is encrypted using the
InnoDB
tablespace encryption feature,
InnoDB
generates a
.cfp
file in addition to a
.cfg
metadata file. The
.cfp
file must be copied to the
destination instance together with the
.cfg
file and tablespace file before
performing the
ALTER TABLE ...
IMPORT TABLESPACE
operation on the destination
instance. The .cfp
file contains a
transfer key and an encrypted tablespace key. On import,
InnoDB
uses the transfer key to decrypt the
tablespace key. For related information, see
Section 14.7.10, “InnoDB Tablespace Encryption”.
If you are transporting tables that are encrypted using the
InnoDB
tablespace encryption, see
Limitations and Usage Notes
before you begin for additional procedural information.
This procedure demonstrates how to copy a regular
InnoDB
table from a running MySQL server
instance to another running instance. The same procedure with
minor adjustments can be used to perform a full table restore on
the same instance.
On the source instance, create a table if one does not exist:
mysql>USE test;
mysql>CREATE TABLE t(c1 INT) ENGINE=InnoDB;
On the destination instance, create a table if one does not exist:
mysql>USE test;
mysql>CREATE TABLE t(c1 INT) ENGINE=InnoDB;
On the destination instance, discard the existing
tablespace. (Before a tablespace can be imported,
InnoDB
must discard the tablespace that
is attached to the receiving table.)
mysql> ALTER TABLE t DISCARD TABLESPACE;
On the source instance, run
FLUSH
TABLES ... FOR EXPORT
to quiesce the table and
create the .cfg
metadata file:
mysql>USE test;
mysql>FLUSH TABLES t FOR EXPORT;
The metadata (.cfg
) is created in the
InnoDB
data directory.
FLUSH
TABLES ... FOR EXPORT
is available as of MySQL
5.6.6. The statement ensures that changes to the named
table have been flushed to disk so that a binary table
copy can be made while the instance is running. When
FLUSH
TABLES ... FOR EXPORT
is run,
InnoDB
produces a
.cfg
file in the same database
directory as the table. The .cfg
file
contains metadata used for schema verification when
importing the tablespace file.
Copy the .ibd
file and
.cfg
metadata file from the source
instance to the destination instance. For example:
shell> scp /path/to/datadir
/test/t.{ibd,cfg} destination-server:/path/to/datadir
/test
The .ibd
file and
.cfg
file must be copied before
releasing the shared locks, as described in the next step.
On the source instance, use
UNLOCK
TABLES
to release the locks acquired by
FLUSH
TABLES ... FOR EXPORT
:
mysql>USE test;
mysql>UNLOCK TABLES;
On the destination instance, import the tablespace:
mysql>USE test;
mysql>ALTER TABLE t IMPORT TABLESPACE;
The ALTER
TABLE ... IMPORT TABLESPACE
feature does not
enforce foreign key constraints on imported data. If there
are foreign key constraints between tables, all tables
should be exported at the same (logical) point in time. In
this case you would stop updating the tables, commit all
transactions, acquire shared locks on the tables, and then
perform the export operation.
This procedure demonstrates how to copy a partitioned
InnoDB
table from a running MySQL server
instance to another running instance. The same procedure with
minor adjustments can be used to perform a full restore of a
partitioned InnoDB
table on the same
instance.
On the source instance, create a partitioned table if one does not exist. In the following example, a table with three partitions (p0, p1, p2) is created:
mysql>USE test;
mysql>CREATE TABLE t1 (i int) ENGINE = InnoDB PARTITION BY KEY (i) PARTITIONS 3;
In the
/
directory, there is a separate tablespace
(datadir
/test.ibd
) file for each of the three
partitions.
mysql> \! ls /path/to/datadir
/test/
db.opt t1.frm t1#P#p0.ibd t1#P#p1.ibd t1#P#p2.ibd
On the destination instance, create the same partitioned table:
mysql>USE test;
mysql>CREATE TABLE t1 (i int) ENGINE = InnoDB PARTITION BY KEY (i) PARTITIONS 3;
In the
/
directory, there is a separate tablespace
(datadir
/test.ibd
) file for each of the three
partitions.
mysql> \! ls /path/to/datadir
/test/
db.opt t1.frm t1#P#p0.ibd t1#P#p1.ibd t1#P#p2.ibd
On the destination instance, discard the tablespace for the partitioned table. (Before the tablespace can be imported on the destination instance, the tablespace that is attached to the receiving table must be discarded.)
mysql> ALTER TABLE t1 DISCARD TABLESPACE;
The three .ibd
files that make up the
tablespace for the partitioned table are discarded from the
/
directory, leaving the following files:
datadir
/test
mysql> \! ls /path/to/datadir
/test/
db.opt t1.frm
On the source instance, run
FLUSH
TABLES ... FOR EXPORT
to quiesce the partitioned
table and create the .cfg
metadata
files:
mysql>USE test;
mysql>FLUSH TABLES t1 FOR EXPORT;
Metadata (.cfg
) files, one for each
tablespace (.ibd
) file, are created in
the
/
directory on the source instance:
datadir
/test
mysql> \! ls /path/to/datadir
/test/
db.opt t1#P#p0.ibd t1#P#p1.ibd t1#P#p2.ibd
t1.frm t1#P#p0.cfg t1#P#p1.cfg t1#P#p2.cfg
FLUSH
TABLES ... FOR EXPORT
statement ensures that
changes to the named table have been flushed to disk so
that binary table copy can be made while the instance is
running. When
FLUSH
TABLES ... FOR EXPORT
is run,
InnoDB
produces a
.cfg
metadata file for the table's
tablespace files in the same database directory as the
table. The .cfg
files contain
metadata used for schema verification when importing
tablespace files.
FLUSH
TABLES ... FOR EXPORT
can only be run on the
table, not on individual table partitions.
Copy the .ibd
and
.cfg
files from the source instance
database directory to the destination instance database
directory. For example:
shell>scp /path/to/datadir
/test/t1*.{ibd,cfg} destination-server:/path/to/datadir
/test
The .ibd
and
.cfg
files must be copied before
releasing the shared locks, as described in the next step.
On the source instance, use
UNLOCK
TABLES
to release the locks acquired by
FLUSH
TABLES ... FOR EXPORT
:
mysql>USE test;
mysql>UNLOCK TABLES;
On the destination instance, import the tablespace for the partitioned table:
mysql>USE test;
mysql>ALTER TABLE t1 IMPORT TABLESPACE;
This procedure demonstrates how to copy
InnoDB
table partitions from a running MySQL
server instance to another running instance. The same procedure
with minor adjustments can be used to perform a restore of
InnoDB
table partitions on the same instance.
In the following example, a partitioned table with four
partitions (p0, p1, p2, p3) is created on the source instance.
Two of the partitions (p2 and p3) are copied to the destination
instance.
On the source instance, create a partitioned table if one does not exist. In the following example, a table with four partitions (p0, p1, p2, p3) is created:
mysql>USE test;
mysql>CREATE TABLE t1 (i int) ENGINE = InnoDB PARTITION BY KEY (i) PARTITIONS 4;
In the
/
directory, there is a separate tablespace
(datadir
/test.ibd
) file for each of the four
partitions.
mysql> \! ls /path/to/datadir
/test/
db.opt t1.frm t1#P#p0.ibd t1#P#p1.ibd t1#P#p2.ibd t1#P#p3.ibd
On the destination instance, create the same partitioned table:
mysql>USE test;
mysql>CREATE TABLE t1 (i int) ENGINE = InnoDB PARTITION BY KEY (i) PARTITIONS 4;
In the
/
directory, there is a separate tablespace
(datadir
/test.ibd
) file for each of the four
partitions.
mysql> \! ls /path/to/datadir
/test/
db.opt t1.frm t1#P#p0.ibd t1#P#p1.ibd t1#P#p2.ibd t1#P#p3.ibd
On the destination instance, discard the tablespace partitions that you plan to import from the source instance. (Before tablespace partitions can be imported on the destination instance, the corresponding partitions that are attached to the receiving table must be discarded.)
mysql> ALTER TABLE t1 DISCARD PARTITION p2, p3 TABLESPACE;
The .ibd
files for the two discarded
partitions are removed from the
/
directory on the destination instance, leaving the following
files:
datadir
/test
mysql> \! ls /path/to/datadir
/test/
db.opt t1.frm t1#P#p0.ibd t1#P#p1.ibd
When ALTER
TABLE ... DISCARD PARTITION ... TABLESPACE
is
run on subpartitioned tables, both partition and
subpartition table names are allowed. When a partition
name is specified, subpartitions of that partition are
included in the operation.
On the source instance, run
FLUSH
TABLES ... FOR EXPORT
to quiesce the partitioned
table and create the .cfg
metadata
files.
mysql>USE test;
mysql>FLUSH TABLES t1 FOR EXPORT;
The metadata files (.cfg
files) are
created in the
/
directory on the source instance. There is a
datadir
/test.cfg
file for each tablespace
(.ibd
) file.
mysql> \! ls /path/to/datadir
/test/
db.opt t1#P#p0.ibd t1#P#p1.ibd t1#P#p2.ibd t1#P#p3.ibd
t1.frm t1#P#p0.cfg t1#P#p1.cfg t1#P#p2.cfg t1#P#p3.cfg
FLUSH
TABLES ... FOR EXPORT
statement ensures that
changes to the named table have been flushed to disk so
that binary table copy can be made while the instance is
running. When
FLUSH
TABLES ... FOR EXPORT
is run,
InnoDB
produces a
.cfg
metadata file for the table's
tablespace files in the same database directory as the
table. The .cfg
files contain
metadata used for schema verification when importing
tablespace files.
FLUSH
TABLES ... FOR EXPORT
can only be run on the
table, not on individual table partitions.
Copy the .ibd
and
.cfg
files from the source instance
database directory to the destination instance database
directory. In this example, only the
.ibd
and .cfg
files for partition 2 (p2) and partition 3 (p3) are copied
to the data
directory on the
destination instance. Partition 0 (p0) and partition 1 (p1)
remain on the source instance.
shell> scp t1#P#p2.ibd t1#P#p2.cfg t1#P#p3.ibd t1#P#p3.cfg destination-server:/path/to/datadir
/test
The .ibd
files and
.cfg
files must be copied before
releasing the shared locks, as described in the next step.
On the source instance, use
UNLOCK
TABLES
to release the locks acquired by
FLUSH
TABLES ... FOR EXPORT
:
mysql>USE test;
mysql>UNLOCK TABLES;
On the destination instance, import the tablespace partitions (p2 and p3):
mysql>USE test;
mysql>ALTER TABLE t1 IMPORT PARTITION p2, p3 TABLESPACE;
When ALTER
TABLE ... IMPORT PARTITION ... TABLESPACE
is run
on subpartitioned tables, both partition and subpartition
table names are allowed. When a partition name is
specified, subpartitions of that partition are included in
the operation.
The following information describes internals and error log
messaging for the transportable tablespaces copy procedure for a
regular InnoDB
table.
When ALTER TABLE
... DISCARD TABLESPACE
is run on the destination
instance:
The table is locked in X mode.
The tablespace is detached from the table.
When
FLUSH
TABLES ... FOR EXPORT
is run on the source instance:
The table being flushed for export is locked in shared mode.
The purge coordinator thread is stopped.
Dirty pages are synchronized to disk.
Table metadata is written to the binary
.cfg
file.
Expected error log messages for this operation:
2013-09-24T13:10:19.903526Z 2 [Note] InnoDB: Sync to disk of '"test"."t"' started. 2013-09-24T13:10:19.903586Z 2 [Note] InnoDB: Stopping purge 2013-09-24T13:10:19.903725Z 2 [Note] InnoDB: Writing table metadata to './test/t.cfg' 2013-09-24T13:10:19.904014Z 2 [Note] InnoDB: Table '"test"."t"' flushed to disk
When UNLOCK
TABLES
is run on the source instance:
The binary .cfg file is deleted.
The shared lock on the table or tables being imported is released and the purge coordinator thread is restarted.
Expected error log messages for this operation:
2013-09-24T13:10:21.181104Z 2 [Note] InnoDB: Deleting the meta-data file './test/t.cfg' 2013-09-24T13:10:21.181180Z 2 [Note] InnoDB: Resuming purge
When ALTER TABLE
... IMPORT TABLESPACE
is run on the destination
instance, the import algorithm performs the following operations
for each tablespace being imported:
Each tablespace page is checked for corruption.
The space ID and log sequence numbers (LSNs) on each page are updated
Flags are validated and LSN updated for the header page.
Btree pages are updated.
The page state is set to dirty so that it is written to disk.
Expected error log messages for this operation:
2013-07-18 15:15:01 34960 [Note] InnoDB: Importing tablespace for table 'test/t' that was exported from host 'ubuntu' 2013-07-18 15:15:01 34960 [Note] InnoDB: Phase I - Update all pages 2013-07-18 15:15:01 34960 [Note] InnoDB: Sync to disk 2013-07-18 15:15:01 34960 [Note] InnoDB: Sync to disk - done! 2013-07-18 15:15:01 34960 [Note] InnoDB: Phase III - Flush changes to disk 2013-07-18 15:15:01 34960 [Note] InnoDB: Phase IV - Flush complete
You may also receive a warning that a tablespace is discarded
(if you discarded the tablespace for the destination table)
and a message stating that statistics could not be calculated
due to a missing .ibd
file:
2013-07-18 15:14:38 34960 [Warning] InnoDB: Table "test"."t" tablespace is set as discarded. 2013-07-18 15:14:38 7f34d9a37700 InnoDB: cannot calculate statistics for table "test"."t" because the .ibd file is missing. For help, please refer to http://dev.mysql.com/doc/refman/5.7/en/innodb-troubleshooting.html
Undo logs may be stored in one or more undo tablespaces instead of the system tablespace. This layout differs from the default configuration in which undo logs reside in the system tablespace. The I/O patterns for undo logs make undo tablespaces good candidates for SSD storage, while keeping the system tablespace on hard disk storage. Undo tablespaces or individual segments inside those tablespaces cannot be dropped. However, undo logs stored in undo tablespaces can be truncated. For more information, see Section 14.7.8, “Truncating Undo Tablespaces”.
To configure separate undo tablespaces for a MySQL instance, perform the following steps. It is assumed that you are performing the procedure on a test instance prior to deploying the configuration to a production system.
The number of undo tablespaces may only be configured when
initializing a new MySQL instance, as the
innodb_undo_tablespaces
option
can only be set at initialization time. The specified setting is
fixed for the life of the MySQL instance.
innodb_undo_tablespaces
is
deprecated and will be removed in a future release.
Specify a directory location for undo tablespaces using the
innodb_undo_directory
configuration option. If a directory location is not
specified, undo tablespaces are created in the MySQL data
directory.
Define the number of rollback segments using the
innodb_rollback_segments
configuration option. Start with a relatively low value and
increase it incrementally over time to examine the effect on
performance. The default setting for
innodb_rollback_segments
is
128, which is also the maximum value.
One rollback segment is always assigned to the system
tablespace, and 32 rollback segments are reserved for the
temporary tablespace (ibtmp1
). Therefore,
to allocate rollback segments to undo tablespaces, set
innodb_rollback_segments
to a
value greater than 33. For example, if you have two undo
tablespaces, set
innodb_rollback_segments
to
35 to assign one rollback segment to each of the two undo
tablespaces. Rollback segments are distributed among undo
tablespaces in a circular fashion.
When you configure separate undo tablespaces, the rollback segment in the system tablespace is rendered inactive.
Define the number of undo tablespaces using the
innodb_undo_tablespaces
option. This setting is fixed for the life of the MySQL
instance, so if you are uncertain about the optimal value,
estimate on the high side.
Create a new MySQL test instance using the option values you have chosen.
Use a realistic workload on your test instance with data volume similar to your production servers to test the configuration.
Benchmark the performance of I/O intensive workloads.
Periodically increase the value of
innodb_rollback_segments
and
rerun performance tests until there are no further
improvements in I/O performance.
To truncate undo
tablespaces, the MySQL instance must be configured with a
minimum of two undo tablespaces. A minimum of two undo tablespaces
ensures that one undo tablespace remains active while the other is
taken offline to be truncated. The number of undo tablespaces is
defined by the
innodb_undo_tablespaces
option.
The default value is 0. Use this statement to check the value of
innodb_undo_tablespaces
:
mysql> SELECT @@innodb_undo_tablespaces;
+---------------------------+
| @@innodb_undo_tablespaces |
+---------------------------+
| 2 |
+---------------------------+
innodb_undo_tablespaces
is
deprecated and will be removed in a future release.
For information about configuring undo tablespaces, see Section 14.7.7, “Configuring Undo Tablespaces”.
To truncate undo tablespaces, enable
innodb_undo_log_truncate
.
mysql> SET GLOBAL innodb_undo_log_truncate=ON;
When innodb_undo_log_truncate
is
enabled, undo tablespace files that exceed the size limit defined
by innodb_max_undo_log_size
are
marked for truncation.
innodb_max_undo_log_size
is a
dynamic global variable with a default value of 1024 MiB
(1073741824 bytes).
mysql> SELECT @@innodb_max_undo_log_size;
+----------------------------+
| @@innodb_max_undo_log_size |
+----------------------------+
| 1073741824 |
+----------------------------+
You can configure
innodb_max_undo_log_size
using a
SET GLOBAL
statement:
mysql> SET GLOBAL innodb_max_undo_log_size=2147483648;
When innodb_undo_log_truncate
is
enabled:
Undo tablespaces that exceed the
innodb_max_undo_log_size
setting are marked for truncation. Selection of an undo
tablespace for truncation is performed in a circular fashion
to avoid truncating the same undo tablespace each time.
Rollback segments residing in the selected undo tablespace are made inactive so that they are not assigned to new transactions. Existing transactions that are currently using rollback segments are allowed to complete.
The purge system frees rollback segments that are no longer needed.
After all rollback segments in the undo tablespace are freed,
the truncate operation runs and the undo tablespace is
truncated to its initial size. The initial size of an undo
tablespace file depends on the
innodb_page_size
value. For
the default 16k InnoDB
page size, the
initial undo tablespace file size is 10MiB. For 4k, 8k, 32k,
and 64k page sizes, the initial undo tablespace files sizes
are 7MiB, 8MiB, 20MiB, and 40MiB, respectively.
The size of an undo tablespace after a truncate operation may be larger than the initial size due to immediate use following the completion of the operation.
The innodb_undo_directory
option defines the location of undo tablespace files. The
default value of “.” represents the directory
where InnoDB
creates other log files by
default.
mysql> SELECT @@innodb_undo_directory;
+-------------------------+
| @@innodb_undo_directory |
+-------------------------+
| . |
+-------------------------+
The rollback segments are reactivated so that they can be assigned to new transactions.
An undo tablespace cannot be truncated until its rollback segments
are freed. Normally, the purge system frees rollback segments once
every 128 times that purge is invoked. To expedite the truncation
of undo tablespaces, use the
innodb_purge_rseg_truncate_frequency
option to temporarily increase the frequency with which the purge
system frees rollback segments. The default
innodb_purge_rseg_truncate_frequency
setting is 128, which is also the maximum value.
mysql> SELECT @@innodb_purge_rseg_truncate_frequency;
+----------------------------------------+
| @@innodb_purge_rseg_truncate_frequency |
+----------------------------------------+
| 128 |
+----------------------------------------+
To increase the frequency with which the purge thread frees
rollback segments, decrease the value of
innodb_purge_rseg_truncate_frequency
.
For example:
mysql> SET GLOBAL innodb_purge_rseg_truncate_frequency=32;
While an undo tablespace is truncated, rollback segments in that tablespace are temporarily deactivated. The remaining active rollback segments in the other undo tablespaces assume responsibility for the entire system load, which may result in a slight performance degradation. The degree of performance degradation depends on a number of factors including:
Number of undo tablespaces
Number of undo logs
Undo tablespace size
Speed of the I/O susbsystem
Existing long running transactions
System load
A general tablespace is a shared InnoDB
tablespace that is created using CREATE
TABLESPACE
syntax. General tablespace capabilities and
features are described under the following topics in this section:
The general tablespace feature provides the following capabilities:
Similar to the system tablespace, general tablespaces are shared tablespaces that can store data for multiple tables.
General tablespaces have a potential memory advantage over file-per-table tablespaces. The server keeps tablespace metadata in memory for the lifetime of a tablespace. Multiple tables in fewer general tablespaces consume less memory for tablespace metadata than the same number of tables in separate file-per-table tablespaces.
General tablespace data files may be placed in a directory relative to or independent of the MySQL data directory, which provides you with many of the data file and storage management capabilities of file-per-table tablespaces. As with file-per-table tablespaces, the ability to place data files outside of the MySQL data directory allows you to manage performance of critical tables separately, setup RAID or DRBD for specific tables, or bind tables to particular disks, for example.
General tablespaces support both Antelope and Barracuda file
formats, and therefore support all table row formats and
associated features. With support for both file formats,
general tablespaces have no dependence on
innodb_file_format
or
innodb_file_per_table
settings, nor do these variables have any effect on general
tablespaces.
The TABLESPACE
option can be used with
CREATE TABLE
to create tables
in a general tablespaces, file-per-table tablespace, or in
the system tablespace.
The TABLESPACE
option can be used with
ALTER TABLE
to move tables
between general tablespaces, file-per-table tablespaces, and
the system tablespace. Previously, it was not possible to
move a table from a file-per-table tablespace to the system
tablespace. With the general tablespace feature, you can now
do so.
General tablespaces are created using
CREATE TABLESPACE
syntax.
CREATE TABLESPACE tablespace_name ADD DATAFILE 'file_name' [FILE_BLOCK_SIZE = value] [ENGINE [=] engine_name]
A general tablespace may be created in the MySQL data directory or in a directory outside of the MySQL data directory. To avoid conflicts with implicitly created file-per-table tablespaces, creating a general tablespace in a subdirectory under the MySQL data directory is not supported. Also, when creating a general tablespace outside of the MySQL data directory, the directory must exist prior to creating the tablespace.
An .isl file is created in the MySQL data directory when a general tablespace is created outside of the MySQL data directory.
Examples:
Creating a general tablespace in the MySQL data directory:
mysql> CREATE TABLESPACE `ts1` ADD DATAFILE 'ts1.ibd' Engine=InnoDB;
Creating a general tablespace in a directory outside of the MySQL data directory:
mysql> CREATE TABLESPACE `ts1` ADD DATAFILE '/my/tablespace/directory/ts1.ibd' Engine=InnoDB;
You can specify a path that is relative to the MySQL data
directory as long as the tablespace directory is not under the
MySQL data directory. In this example, the
my_tablespace
directory is at the same
level as the MySQL data directory:
mysql> CREATE TABLESPACE `ts1` ADD DATAFILE '../my_tablespace/ts1.ibd' Engine=InnoDB;
The ENGINE = InnoDB
clause must be defined
as part of the CREATE
TABLESPACE
statement or InnoDB
must be defined as the default storage engine
(default_storage_engine=InnoDB
).
After creating an InnoDB
general tablespace,
you can use CREATE
TABLE
or
tbl_name
... TABLESPACE [=]
tablespace_name
ALTER TABLE
to add
tables to the tablespace, as shown in the following examples:
tbl_name
TABLESPACE [=]
tablespace_name
mysql> CREATE TABLE t1 (c1 INT PRIMARY KEY) TABLESPACE ts1 ROW_FORMAT=COMPACT;
mysql> ALTER TABLE t2 TABLESPACE ts1;
For detailed syntax information, see CREATE
TABLE
and ALTER TABLE
.
General tablespaces support all table row formats
(REDUNDANT
, COMPACT
,
DYNAMIC
, COMPRESSED
) with
the caveat that compressed and uncompressed tables cannot
coexist in the same general tablespace due to different physical
page sizes.
For a general tablespace to contain compressed tables
(ROW_FORMAT=COMPRESSED
),
FILE_BLOCK_SIZE
must be specified, and the
FILE_BLOCK_SIZE
value must be a valid
compressed page size in relation to the
innodb_page_size
value. Also,
the physical page size of the compressed table
(KEY_BLOCK_SIZE
) must be equal to
FILE_BLOCK_SIZE/1024
. For example, if
innodb_page_size=16K
and
FILE_BLOCK_SIZE=8K
, the
KEY_BLOCK_SIZE
of the table must be 8.
The following table shows permitted
innodb_page_size
,
FILE_BLOCK_SIZE
, and
KEY_BLOCK_SIZE
combinations.
FILE_BLOCK_SIZE
values may also be specified
in bytes. To determine a valid KEY_BLOCK_SIZE
value for a given FILE_BLOCK_SIZE
, divide the
FILE_BLOCK_SIZE
value by 1024. Table
compression is not support for 32K and 64K
InnoDB
page sizes. For more information about
KEY_BLOCK_SIZE
, see
CREATE TABLE
, and
Section 14.9.1.2, “Creating Compressed Tables”.
Table 14.5 Permitted Page Size, FILE_BLOCK_SIZE, and KEY_BLOCK_SIZE Combinations for Compressed Tables
InnoDB Page Size (innodb_page_size) | Permitted FILE_BLOCK_SIZE Value | Permitted KEY_BLOCK_SIZE Value |
---|---|---|
64K | 64K (65536) | Compression is not supported |
32K | 32K (32768) | Compression is not supported |
16K | 16K (16384) | N/A: If innodb_page_size is equal to
FILE_BLOCK_SIZE , the tablespace cannot
contain a compressed table. |
16K | 8K (8192) | 8 |
16K | 4K (4096) | 4 |
16K | 2K (2048) | 2 |
16K | 1K (1024) | 1 |
8K | 8K (8192) | N/A: If innodb_page_size is equal to
FILE_BLOCK_SIZE , the tablespace cannot
contain a compressed table. |
8K | 4K (4096) | 4 |
8K | 2K (2048) | 2 |
8K | 1K (1024) | 1 |
4K | 4K (4096) | N/A: If innodb_page_size is equal to
FILE_BLOCK_SIZE , the tablespace cannot
contain a compressed table. |
4K | 2K (2048) | 2 |
4K | 1K (1024) | 1 |
This example demonstrates creating a general tablespace and
adding a compressed table. The example assumes a default
innodb_page_size
of 16K. The
FILE_BLOCK_SIZE
of 8192 requires that the
compressed table have a KEY_BLOCK_SIZE
of 8.
mysql>CREATE TABLESPACE `ts2` ADD DATAFILE 'ts2.ibd' FILE_BLOCK_SIZE = 8192 Engine=InnoDB;
mysql>CREATE TABLE t4 (c1 INT PRIMARY KEY) TABLESPACE ts2 ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;
If you do not specify FILE_BLOCK_SIZE
when
creating a general tablespace,
FILE_BLOCK_SIZE
defaults to
innodb_page_size
. When
FILE_BLOCK_SIZE
is equal to
innodb_page_size
, the
tablespace may only contain tables with an uncompressed row
format (COMPACT
,
REDUNDANT
, and DYNAMIC
row
formats).
You can use ALTER TABLE
with the
TABLESPACE
option to move a non-partitioned
InnoDB
table to an existing general
tablespace, to a new file-per-table tablespace, or to the system
tablespace.
To move a non-partitioned table from a file-per-table tablespace
or from the system tablespace to a general tablespace, specify
the name of the general tablespace. The general tablespace must
exist. See CREATE TABLESPACE
for
more information.
ALTER TABLE tbl_name TABLESPACE [=] tablespace_name
To move a non-partitioned table from a general tablespace or
file-per-table tablespace to the system tablespace, specify
innodb_system
as the tablespace name.
ALTER TABLE tbl_name ... TABLESPACE [=] innodb_system
To move a non-partitioned table from the system tablespace or a
general tablespace to a file-per-table tablespace, specify
innodb_file_per_table
as the tablespace name.
ALTER TABLE tbl_name ... TABLESPACE [=] innodb_file_per_table
ALTER TABLE ... TABLESPACE
operations always
cause a full table rebuild, even if the
TABLESPACE
attribute has not changed from its
previous value.
ALTER TABLE ... TABLESPACE
syntax does not
support moving a table from a temporary tablespace to a
persistent tablespace.
The DATA DIRECTORY
clause is permitted with
CREATE TABLE ...
TABLESPACE=innodb_file_per_table
but is otherwise not
supported for use in combination with the
TABLESPACE
option.
The TABLESPACE
option may be used to assign
individual table partitions or subpartitions to a
general
tablespace, a separate file-per-table tablespace, or the
system tablespace. All partitions must belong to the same
storage engine. Usage is demonstrated in the following examples.
mysql>CREATE TABLESPACE `ts1` ADD DATAFILE 'ts1.ibd' Engine=InnoDB;
mysql>CREATE TABLESPACE `ts2` ADD DATAFILE 'ts2.ibd' Engine=InnoDB;
mysql>CREATE TABLE t1 (a INT, b INT) ENGINE = InnoDB
PARTITION BY RANGE(a) SUBPARTITION BY KEY(b) (
PARTITION p1 VALUES LESS THAN (100) TABLESPACE=`ts1`,
PARTITION p2 VALUES LESS THAN (1000) TABLESPACE=`ts2`,
PARTITION p3 VALUES LESS THAN (10000) TABLESPACE `innodb_file_per_table`,
PARTITION p4 VALUES LESS THAN (100000) TABLESPACE `innodb_system`);
mysql>CREATE TABLE t2 (a INT, b INT) ENGINE = InnoDB
PARTITION BY RANGE(a) SUBPARTITION BY KEY(b) (
PARTITION p1 VALUES LESS THAN (100) TABLESPACE=`ts1`
(SUBPARTITION sp1,
SUBPARTITION sp2),
PARTITION p2 VALUES LESS THAN (1000)
(SUBPARTITION sp3,
SUBPARTITION sp4 TABLESPACE=`ts2`),
PARTITION p3 VALUES LESS THAN (10000)
(SUBPARTITION sp5 TABLESPACE `innodb_system`,
SUBPARTITION sp6 TABLESPACE `innodb_file_per_table`));
The TABLESPACE
option is also supported with
ALTER TABLE
.
mysql> ALTER TABLE t1 ADD PARTITION (PARTITION p5 VALUES LESS THAN (1000000) TABLESPACE = `ts1`);
If the TABLESPACE =
option is
not defined, the
tablespace_name
ALTER TABLE ...
ADD PARTITION
operation adds the partition to the
table's default tablespace, which can be specified at the
table level during CREATE TABLE
or ALTER TABLE
.
An ALTER TABLE
operation
on a partitioned table only modifies the
table's default tablespace. It does not move the table
partitions. However, after changing the default tablespace, an
operation that rebuilds the table, such as an
tbl_name
TABLESPACE [=]
tablespace_name
ALTER TABLE
operation that uses
ALGORITHM=COPY
, moves the partitions to the
default tablespace if another tablespace is not defined
explicitly using the TABLESPACE [=]
clause.
tablespace_name
To verify that partitions were placed in the specified
tablespaces, you can query
INFORMATION_SCHEMA.INNODB_SYS_TABLES
:
mysql>SELECT NAME, SPACE, SPACE_TYPE FROM INFORMATION_SCHEMA.INNODB_SYS_TABLES
WHERE NAME LIKE '%t1%';
+-----------------------+-------+------------+ | NAME | SPACE | SPACE_TYPE | +-----------------------+-------+------------+ | test/t1#P#p1#SP#p1sp0 | 57 | General | | test/t1#P#p2#SP#p2sp0 | 58 | General | | test/t1#P#p3#SP#p3sp0 | 59 | Single | | test/t1#P#p4#SP#p4sp0 | 0 | System | | test/t1#P#p5#SP#p5sp0 | 57 | General | +-----------------------+-------+------------+ mysql>SELECT NAME, SPACE, SPACE_TYPE FROM INFORMATION_SCHEMA.INNODB_SYS_TABLES
WHERE NAME LIKE '%t2%';
+---------------------+-------+------------+ | NAME | SPACE | SPACE_TYPE | +---------------------+-------+------------+ | test/t2#P#p1#SP#sp1 | 57 | General | | test/t2#P#p1#SP#sp2 | 57 | General | | test/t2#P#p2#SP#sp3 | 60 | Single | | test/t2#P#p2#SP#sp4 | 58 | General | | test/t2#P#p3#SP#sp5 | 0 | System | | test/t2#P#p3#SP#sp6 | 61 | Single | +---------------------+-------+------------+
To move table partitions to a different tablespace, you must
move each partition using an ALTER TABLE
statement.
tbl_name
REORGANIZE
PARTITION
The following example demonstrates how to move table partitions
to a different tablespace.
INFORMATION_SCHEMA.INNODB_SYS_TABLES
and
INFORMATION_SCHEMA.INNODB_SYS_TABLESPACES
are queried to verify that partitions are placed in the expected
tablespace.
If the TABLESPACE =
option is
not defined in the tablespace_name
REORGANIZE PARTITION
statement, InnoDB
moves the partition to
the table's default tablespace. In the example that follows,
tablespace ts1
, which is defined at the
table level, is the default tablespace for table
t1
. Partition P3
is
moved from the system tablespace to tablespace
ts1
since no TABLESPACE
option is specified in the
ALTER TABLE t1
REORGANIZE PARTITION
statement for partition
P3
.
An operation that rebuilds the table, such as an
ALTER TABLE
operation that uses
ALGORITHM=COPY
, moves partitions to the
default tablespace if partitions reside in a different
tablespace that is not defined explicitly using the
TABLESPACE [=]
clause.
tablespace_name
mysql>CREATE TABLESPACE ts1 ADD DATAFILE 'ts1.ibd';
mysql>CREATE TABLESPACE ts2 ADD DATAFILE 'ts2.ibd';
mysql>CREATE TABLE t1 ( a INT NOT NULL, PRIMARY KEY (a))
ENGINE=InnoDB TABLESPACE ts1
PARTITION BY RANGE (a) PARTITIONS 3 (
PARTITION P1 VALUES LESS THAN (2),
PARTITION P2 VALUES LESS THAN (4) TABLESPACE `innodb_file_per_table`,
PARTITION P3 VALUES LESS THAN (6) TABLESPACE `innodb_system`);
mysql>SELECT A.NAME as partition_name, A.SPACE_TYPE as space_type, B.NAME as space_name
FROM INFORMATION_SCHEMA.INNODB_SYS_TABLES A
LEFT JOIN INFORMATION_SCHEMA.INNODB_SYS_TABLESPACES B
ON A.SPACE = B.SPACE WHERE A.NAME LIKE '%t1%' ORDER BY A.NAME;
+----------------+------------+--------------+ | partition_name | space_type | space_name | +----------------+------------+--------------+ | test/t1#P#P1 | General | ts1 | | test/t1#P#P2 | Single | test/t1#P#P2 | | test/t1#P#P3 | System | NULL | +----------------+------------+--------------+ mysql>ALTER TABLE t1 REORGANIZE PARTITION P1
INTO (PARTITION P1 VALUES LESS THAN (2) TABLESPACE = `ts2`);
mysql>ALTER TABLE t1 REORGANIZE PARTITION P2
INTO (PARTITION P2 VALUES LESS THAN (4) TABLESPACE = `ts2`);
mysql>ALTER TABLE t1 REORGANIZE PARTITION P3
INTO (PARTITION P3 VALUES LESS THAN (6));
mysql>SELECT A.NAME AS partition_name, A.SPACE_TYPE AS space_type, B.NAME AS space_name
FROM INFORMATION_SCHEMA.INNODB_SYS_TABLES A
LEFT JOIN INFORMATION_SCHEMA.INNODB_SYS_TABLESPACES B
ON A.SPACE = B.SPACE WHERE A.NAME LIKE '%t1%' ORDER BY A.NAME;
+----------------+------------+------------+ | partition_name | space_type | space_name | +----------------+------------+------------+ | test/t1#P#P1 | General | ts2 | | test/t1#P#P2 | General | ts2 | | test/t1#P#P3 | General | ts1 | +----------------+------------+------------+
The DROP TABLESPACE
statement is
used to drop an InnoDB
general tablespace.
All tables must be dropped from the tablespace prior to a
DROP TABLESPACE
operation. If the
tablespace is not empty, DROP
TABLESPACE
returns an error.
If a DROP TABLESPACE
operation on
an empty general tablespace returns an
error, the tablespace may contain an orphan temporary or
intermediate table that was left by an
ALTER TABLE
operation that was
interrupted by a server exit. For more information, see
Section 14.21.3, “Troubleshooting InnoDB Data Dictionary Operations”.
A general InnoDB
tablespace is not deleted
automatically when the last table in the tablespace is dropped.
The tablespace must be dropped explicitly using
DROP TABLESPACE
.
tablespace_name
A general tablespace does not belong to any particular database.
A DROP DATABASE
operation can
drop tables that belong to a general tablespace but it cannot
drop the tablespace, even if the DROP
DATABASE
operation drops all tables that belong to the
tablespace. A general tablespace must be dropped explicitly
using DROP
TABLESPACE
.
tablespace_name
Similar to the system tablespace, truncating or dropping tables
stored in a general tablespace creates free space internally in
the general tablespace .ibd data
file which can only be used for new
InnoDB
data. Space is not released back to
the operating system as it is when a file-per-table tablespace
is deleted during a DROP TABLE
operation.
This example demonstrates how to drop an
InnoDB
general tablespace. The general
tablespace ts1
is created with a single
table. The table must be dropped before dropping the tablespace.
mysql>CREATE TABLESPACE `ts1` ADD DATAFILE 'ts1.ibd' Engine=InnoDB;
mysql>CREATE TABLE t1 (c1 INT PRIMARY KEY) TABLESPACE ts10 Engine=InnoDB;
mysql>DROP TABLE t1;
mysql>DROP TABLESPACE ts1;
is a case-sensitive identifier in MySQL.
tablespace_name
A generated or existing tablespace cannot be changed to a general tablespace.
Creation of temporary general tablespaces is not supported.
General tablespaces do not support temporary tables.
Tables stored in a general tablespace may only be opened in MySQL releases that support general tablespaces.
Similar to the system tablespace, truncating or dropping
tables stored in a general tablespace creates free space
internally in the general tablespace
.ibd data file which
can only be used for new InnoDB
data.
Space is not released back to the operating system as it is
for
file-per-table
tablespaces.
Additionally, a table-copying ALTER
TABLE
operation on table that resides in a shared
tablespace (a general tablespace or the system tablespace)
can increase the amount of space used by the tablespace.
Such operations require as much additional space as the data
in the table plus indexes. The additional space required for
the table-copying ALTER TABLE
operation is not released back to the operating system as it
is for file-per-table tablespaces.
ALTER TABLE ...
DISCARD TABLESPACE
and
ALTER TABLE
...IMPORT TABLESPACE
are not supported for tables
that belong to a general tablespace.
For more information see Section 13.1.19, “CREATE TABLESPACE Syntax”.
InnoDB
supports data encryption for
InnoDB
tables stored in
file-per-table
tablespaces. This feature provides at-rest encryption for physical
tablespace data files.
InnoDB
tablespace encryption uses a two tier
encryption key architecture, consisting of a master encryption key
and tablespace keys. When an InnoDB
table is
encrypted, a tablespace key is encrypted and stored in the
tablespace header. When an application or authenticated user wants
to access encrypted tablespace data, InnoDB
uses a master encryption key to decrypt the tablespace key. The
decrypted version of a tablespace key never changes, but the
master encryption key may be changed as required. This action is
referred to as master key rotation.
The InnoDB
tablespace encryption feature relies
on a keyring plugin for master encryption key management.
All MySQL editions provide a keyring_file
plugin, which stores master encryption key data in a file in the
location specified by the
keyring_file_data
configuration
option.
The InnoDB
tablespace encryption feature in
non-enterprise editions of MySQL uses the
keyring_file
plugin for encryption key
management. The keyring_file
plugin, and
keyring_encrypted_file
plugin, which is
available in MySQL Enterprise Edition, are not intended as a regulatory compliance
solution. Security standards such as PCI, FIPS, and others
require use of key management systems to secure, manage, and
protect encryption keys in key vaults or hardware security
modules (HSMs).
MySQL Enterprise Edition offers the keyring_okv
plugin, which
includes a KMIP client (KMIP 1.1) that works with Oracle Key Vault
(OKV) to provide encryption key management. When
InnoDB
tablespace encryption uses OKV for
encryption key management, the feature is referred to as
“MySQL Enterprise Transparent Data Encryption (TDE)”.
A secure and robust encryption key management solution such as OKV is critical for security and for compliance with various security standards. Among other benefits, using a key vault ensures that keys are stored securely, never lost, and only known to authorized key administrators. A key vault also maintains an encryption key history.
InnoDB
tablespace encryption supports the
Advanced Encryption Standard (AES) block-based encryption
algorithm. It uses Electronic Codebook (ECB) block encryption mode
for tablespace key encryption and Cipher Block Chaining (CBC)
block encryption mode for data encryption.
For frequently asked questions about the InnoDB
tablespace encryption feature, see
Section A.16, “MySQL 5.7 FAQ: InnoDB Tablespace Encryption”.
A keyring plugin (the keyring_file
plugin
or keyring_okv
plugin) must be installed
and configured. Keyring plugin installation is performed at
startup using the
--early-plugin-load
option.
Early loading ensures that the plugin is available prior to
initialization of the InnoDB
storage
engine. For keyring plugin installation and configuration
instructions, see Section 6.5.4, “The MySQL Keyring”.
Only one keyring plugin should be enabled at a time. Enabling multiple keyring plugins is not supported.
Once encrypted tables are created in a MySQL instance, the
keyring plugin that was loaded when creating the encrypted
tables must continue to be loaded using the
--early-plugin-load
option,
prior to InnoDB
initialization. Failing
to do so results in errors on startup and during
InnoDB
recovery.
To verify that a keyring plugin is active, use the
SHOW PLUGINS
statement or
query the
INFORMATION_SCHEMA.PLUGINS
table. For example:
mysql>SELECT PLUGIN_NAME, PLUGIN_STATUS
FROM INFORMATION_SCHEMA.PLUGINS
WHERE PLUGIN_NAME LIKE 'keyring%';
+--------------+---------------+ | PLUGIN_NAME | PLUGIN_STATUS | +--------------+---------------+ | keyring_file | ACTIVE | +--------------+---------------+
The innodb_file_per_table
option must be enabled (the default).
InnoDB
tablespace encryption only
supports
file-per-table
tablespaces. Alternatively, you can specify the
TABLESPACE='innodb_file_per_table'
option
when creating an encrypted table or altering an existing
table to enable encryption.
Before using the InnoDB
tablespace
encryption feature with production data, ensure that you
have taken steps to prevent loss of the master encryption
key. If the master encryption key is lost, data
stored in encrypted tablespace files is
unrecoverable. If you are using the
keyring_file
plugin, it is recommended
that you create a backup of the keyring data file
immediately after creating the first encrypted table and
before and after master key rotation. The keyring data file
location is defined by the
keyring_file_data
configuration option. If you are using the
keyring_okv
plugin, ensure that you have
performed the necessary keyring_okv
plugin and Oracle Key Vault (OKV) configuration. For keyring
plugin configuration, see Section 6.5.4, “The MySQL Keyring”. For OKV
configuration, refer to the OKV documentation available at
the
Oracle
Key Vault site.
To enable encryption for a new InnoDB
table,
specify the ENCRYPTION
option in a
CREATE TABLE
statement.
mysql> CREATE TABLE t1 (c1 INT) ENCRYPTION='Y';
To enable encryption for an existing InnoDB
table, specify the ENCRYPTION
option in an
ALTER TABLE
statement.
mysql> ALTER TABLE t1 ENCRYPTION='Y';
To disable encryption for an InnoDB
table,
set ENCRYPTION='N'
using
ALTER TABLE
.
mysql> ALTER TABLE t1 ENCRYPTION='N';
Plan appropriately when altering an existing table with the
ENCRYPTION
option.
ALTER TABLE ...
ENCRYPTION
operations rebuild the table using
ALGORITHM=COPY
.
ALGORITHM=INPLACE
is not supported.
The master encryption key should be rotated periodically and whenever you suspect that the key may have been compromised.
Master key rotation is an atomic, instance-level operation. Each
time the master encryption key is rotated, all tablespace keys
in the MySQL instance are re-encrypted and saved back to their
respective tablespace headers. As an atomic operation,
re-encryption must succeed for all tablespace keys once a
rotation operation is initiated. If master key rotation is
interrupted by a server failure, InnoDB
rolls
the operation forward on server restart. For more information,
see InnoDB Tablespace Encryption and Recovery.
Rotating the master encryption key only changes the master encryption key and re-encrypts tablespace keys. It does not decrypt or re-encrypt associated tablespace data.
Rotating the master encryption key requires the
SUPER
privilege.
To rotate the master encryption key, run:
mysql> ALTER INSTANCE ROTATE INNODB MASTER KEY;
ALTER INSTANCE
ROTATE INNODB MASTER KEY
supports concurrent DML.
However, it cannot be run concurrently with
CREATE TABLE ...
ENCRYPTED
or
ALTER TABLE ...
ENCRYPTED
operations, and locks are taken to prevent
conflicts that could arise from concurrent execution of these
statements. If one of the conflicting statements is running, it
must complete before another can proceed.
If a server failure occurs during master key rotation,
InnoDB
continues the operation on server
restart.
The keyring plugin that was installed when tables were encrypted
must be loaded prior to storage engine initialization so that
the information necessary to decrypt tablespace data pages can
be retrieved from tablespace headers before
InnoDB
initialization and recovery activities
access tablespace data. (See
InnoDB Tablespace Encryption Prerequisites.)
When InnoDB
initialization and recovery
begin, the master key rotation operation resumes. Due to the
server failure, some tablespaces keys may already be encrypted
using the new master encryption key. InnoDB
reads the encryption data from each tablespace header, and if
the data indicates that the tablespace key is encrypted using
the old master encryption key, InnoDB
retrieves the old key from the keyring and uses it to decrypt
the tablepace key. InnoDB
then re-encrypts
the tablespace key using the new master encryption key and saves
the re-encrypted tablespace key back to the tablespace header.
When an encrypted table is exported, InnoDB
generates a transfer key that is used to
encrypt the tablespace key. The encrypted tablespace key and
transfer key are stored in a
file. This file together with the encrypted tablespace file is
required to perform an import operation. On import,
tablespace_name
.cfpInnoDB
uses the transfer key to decrypt the
tablespace key in the
file. For related information, see
Section 14.7.6, “Copying File-Per-Table Tablespaces to Another Instance”.
tablespace_name
.cfp
The ALTER
INSTANCE ROTATE INNODB MASTER KEY
statement is
only supported in replication environments where the master
and slaves run a version of MySQL that supports the
tablespace encryption feature.
Successful
ALTER
INSTANCE ROTATE INNODB MASTER KEY
statements are
written to the binary log for replication on slaves.
If an ALTER
INSTANCE ROTATE INNODB MASTER KEY
statement fails,
it is not logged to the binary log and is not replicated on
slaves.
Replication of an
ALTER
INSTANCE ROTATE INNODB MASTER KEY
operation fails
if the keyring plugin is installed on the master but not on
the slave.
If the keyring_file
plugin is installed
on both the master and a slave but the slave does not have a
keyring data file, the replicated
ALTER
INSTANCE ROTATE INNODB MASTER KEY
statement
creates the keyring data file on the slave, assuming the
keyring file data is not cached in memory.
ALTER
INSTANCE ROTATE INNODB MASTER KEY
uses keyring
file data that is cached in memory, if available.
When the ENCRYPTION
option is specified in a
CREATE TABLE
or
ALTER TABLE
statement, it is
recorded in the CREATE_OPTIONS
field of
INFORMATION_SCHEMA.TABLES
. This
field may be queried to identify encrypted tables in a MySQL
instance.
mysql>SELECT TABLE_SCHEMA, TABLE_NAME, CREATE_OPTIONS FROM INFORMATION_SCHEMA.TABLES
WHERE CREATE_OPTIONS LIKE '%ENCRYPTION="Y"%';
+--------------+------------+----------------+ | TABLE_SCHEMA | TABLE_NAME | CREATE_OPTIONS | +--------------+------------+----------------+ | test | t1 | ENCRYPTION="Y" | +--------------+------------+----------------+
If the server exits or is stopped during normal operation, it is recommended to restart the server using the same encryption settings that were configured previously.
The first master encryption key is generated when the first new or existing table is encrypted.
Master key rotation re-encrypts tablespaces keys but does
not change the tablespace key itself. To change a tablespace
key, you must disable and re-enable table encryption using
ALTER TABLE
,
which is an tbl_name
ENCRYPTIONALGORITHM=COPY
operation that
rebuilds the table.
If a table is created with both the
COMPRESSION
and
ENCRYPTION
options, compression is performed before tablespace data is
encrypted.
keyring_file
plugin usage notes:
If a keyring data file (the file named by the
keyring_file_data
system variable) is empty or missing, the first
execution of
ALTER
INSTANCE ROTATE INNODB MASTER KEY
creates a
master encryption key.
Uninstalling the keyring_file
plugin
does not remove an existing keyring data file.
It is recommended that you not place the keyring data file under the same directory as tablespace data files.
Modifying the
keyring_file_data
system variable at runtime or restarting the server with
a new keyring_file_data
setting can cause previously encrypted tables to become
inaccessible, resulting in the loss of data.
Advanced Encryption Standard (AES) is the only supported
encryption algorithm. InnoDB
tablespace
encryption uses Electronic Codebook (ECB) block encryption
mode for tablespace key encryption and Cipher Block Chaining
(CBC) block encryption mode for data encryption.
Altering the ENCRYPTION
attribute of a
table is an ALGORITHM=COPY
operation.
ALGORITHM=INPLACE
is not supported.
InnoDB
tablespace encryption only
supports InnoDB
tables that are stored in
a file-per-table
tablespaces. Encryption is not supported for tables stored
in other InnoDB
tablespace types
including general
tablespaces, the
system
tablespace, undo log tablespaces, and the temporary
tablespace.
You cannot move or copy an encrypted table from a
file-per-table
tablespace to an unsupported InnoDB
tablespace type.
Tablespace encryption only applies to data in the tablespace. Data is not encrypted in the redo log, undo log, or binary log.
Direct migration from the keyring_file
plugin to the keyring_okv
plugin, or
vice-versa, is currently unsupported. Changing keyring
plugins requires decrypting tables, uninstalling the current
keyring plugin, installing and configuring the other keyring
plugin, and re-encrypting tables.
This section covers topics related to InnoDB
tables and indexes.
This section covers topics related to InnoDB
tables.
To create an InnoDB
table, use the
CREATE TABLE
statement.
CREATE TABLE t1 (a INT, b CHAR (20), PRIMARY KEY (a)) ENGINE=InnoDB;
You do not need to specify the ENGINE=InnoDB
clause if InnoDB
is defined as the default
storage engine, which it is by default. To check the default
storage engine, issue the following statement:
mysql> SELECT @@default_storage_engine;
+--------------------------+
| @@default_storage_engine |
+--------------------------+
| InnoDB |
+--------------------------+
You might still use ENGINE=InnoDB
clause if
you plan to use mysqldump or replication to
replay the CREATE TABLE
statement
on a server where the default storage engine is not
InnoDB
.
An InnoDB
table and its indexes can be
created in the system
tablespace, in a
file-per-table
tablespace, or in a
general
tablespace. When
innodb_file_per_table
is
enabled, which is the default, an InnoDB
table is implicitly created in an individual file-per-table
tablespace. Conversely, when
innodb_file_per_table
is
disabled, an InnoDB
table is implicitly
created in the InnoDB
system tablespace. To
create a table in a general tablespace, use
CREATE TABLE ...
TABLESPACE
syntax. For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
When you create an InnoDB
table, MySQL
creates a .frm file in the
database directory under the MySQL data directory. For more
information about .frm
files, see
InnoDB Tables and .frm Files. For a table created in a
file-per-table tablespace, MySQL also creates an
.ibd tablespace file in the
database directory, by default. A table created in the
InnoDB
system tablespace is created in an
existing ibdata file, which
resides in the MySQL data directory. A table created in a
general tablespace is created in an existing general tablespace
.ibd file. General
tablespace files can be created inside or outside of the MySQL
data directory. For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
Internally, InnoDB
adds an entry for each
table to the InnoDB
data dictionary. The
entry includes the database name. For example, if table
t1
is created in the test
database, the data dictionary entry for the database name is
'test/t1'
. This means you can create a table
of the same name (t1
) in a different
database, and the table names do not collide inside
InnoDB
.
MySQL stores data dictionary information for tables in
.frm files in database
directories. Unlike other MySQL storage engines,
InnoDB
also encodes information about the
table in its own internal data dictionary inside the system
tablespace. When MySQL drops a table or a database, it deletes
one or more .frm
files as well as the
corresponding entries inside the InnoDB
data dictionary. You cannot move InnoDB
tables between databases simply by moving the
.frm
files. For information about moving
InnoDB
tables, see
Section 14.8.1.3, “Moving or Copying InnoDB Tables”.
The default row format for InnoDB
tables is
defined by the
innodb_default_row_format
configuration option, which has a default value of
DYNAMIC
.
Dynamic
and
Compressed
row format allow you to take advantage of
InnoDB
features such as table compression
and efficient off-page storage of long column values. To use
these row formats,
innodb_file_per_table
must be
enabled (the default as of MySQL 5.6.6) and
innodb_file_format
must be
set to Barracuda.
SET GLOBAL innodb_file_per_table=1; SET GLOBAL innodb_file_format=barracuda; CREATE TABLE t3 (a INT, b CHAR (20), PRIMARY KEY (a)) ROW_FORMAT=DYNAMIC; CREATE TABLE t4 (a INT, b CHAR (20), PRIMARY KEY (a)) ROW_FORMAT=COMPRESSED;
Alternatively, you can use
CREATE TABLE ...
TABLESPACE
syntax to create an
InnoDB
table in a general tablespace.
General tablespaces support all row formats. For more
information, see Section 14.7.9, “InnoDB General Tablespaces”.
CREATE TABLE t1 (c1 INT PRIMARY KEY) TABLESPACE ts1 ROW_FORMAT=DYNAMIC;
CREATE TABLE ...
TABLESPACE
syntax can also be used to create
InnoDB
tables with a
Dynamic
row format in the system
tablespace, alongside tables with a Compact
or Redundant
row format.
CREATE TABLE t1 (c1 INT PRIMARY KEY) TABLESPACE = innodb_system ROW_FORMAT=DYNAMIC;
For more information about InnoDB
row
formats, see Section 14.11, “InnoDB Row Storage and Row Formats”. For how to
determine the row format of an InnoDB
table
and the physical characteristics of InnoDB
row formats, see Section 14.8.1.2, “The Physical Row Structure of an InnoDB Table”.
Always define a primary
key for an InnoDB
table, specifying
the column or columns that:
Are referenced by the most important queries.
Are never left blank.
Never have duplicate values.
Rarely if ever change value once inserted.
For example, in a table containing information about people,
you would not create a primary key on (firstname,
lastname)
because more than one person can have the
same name, some people have blank last names, and sometimes
people change their names. With so many constraints, often
there is not an obvious set of columns to use as a primary
key, so you create a new column with a numeric ID to serve as
all or part of the primary key. You can declare an
auto-increment
column so that ascending values are filled in automatically as
rows are inserted:
# The value of ID can act like a pointer between related items in different tables. CREATE TABLE t5 (id INT AUTO_INCREMENT, b CHAR (20), PRIMARY KEY (id)); # The primary key can consist of more than one column. Any autoinc column must come first. CREATE TABLE t6 (id INT AUTO_INCREMENT, a INT, b CHAR (20), PRIMARY KEY (id,a));
Although the table works correctly without defining a primary
key, the primary key is involved with many aspects of
performance and is a crucial design aspect for any large or
frequently used table. It is recommended that you always
specify a primary key in the CREATE
TABLE
statement. If you create the table, load data,
and then run ALTER TABLE
to add
a primary key later, that operation is much slower than
defining the primary key when creating the table.
To view the properties of an InnoDB
table,
issue a SHOW TABLE STATUS
statement:
mysql> SHOW TABLE STATUS FROM test LIKE 't%' \G;
*************************** 1. row ***************************
Name: t1
Engine: InnoDB
Version: 10
Row_format: Compact
Rows: 0
Avg_row_length: 0
Data_length: 16384
Max_data_length: 0
Index_length: 0
Data_free: 0
Auto_increment: NULL
Create_time: 2015-03-16 15:13:31
Update_time: NULL
Check_time: NULL
Collation: latin1_swedish_ci
Checksum: NULL
Create_options:
Comment:
1 row in set (0.00 sec)
For information about SHOW TABLE
STATUS
output, see
Section 13.7.5.36, “SHOW TABLE STATUS Syntax”.
InnoDB
table properties may also be queried
using the InnoDB
Information Schema system
tables:
mysql> SELECT * FROM INFORMATION_SCHEMA.INNODB_SYS_TABLES WHERE NAME='test/t1' \G
*************************** 1. row ***************************
TABLE_ID: 45
NAME: test/t1
FLAG: 1
N_COLS: 5
SPACE: 35
FILE_FORMAT: Antelope
ROW_FORMAT: Compact
ZIP_PAGE_SIZE: 0
SPACE_TYPE: Single
1 row in set (0.00 sec)
For more information, see Section 14.15.3, “InnoDB INFORMATION_SCHEMA System Tables”.
The physical row structure of an InnoDB
table
depends on the row format specified when the table is created.
If a row format is not specified, the default row format is
used. The default row format for InnoDB
tables is defined by the
innodb_default_row_format
configuration option, which has a default value of
DYNAMIC
.
The following sections describe the characteristics of
InnoDB
row formats.
For more information about InnoDB
row
formats, see Section 14.11, “InnoDB Row Storage and Row Formats”.
To determine the row format of an InnoDB
table, use SHOW TABLE STATUS
.
For example:
mysql> SHOW TABLE STATUS IN test1\G
*************************** 1. row ***************************
Name: t1
Engine: InnoDB
Version: 10
Row_format: Dynamic
Rows: 0
Avg_row_length: 0
Data_length: 16384
Max_data_length: 0
Index_length: 16384
Data_free: 0
Auto_increment: 1
Create_time: 2016-09-14 16:29:38
Update_time: NULL
Check_time: NULL
Collation: latin1_swedish_ci
Checksum: NULL
Create_options:
Comment:
You can also determine the row format of an
InnoDB
table by querying
INFORMATION_SCHEMA.INNODB_SYS_TABLES
.
mysql> SELECT NAME, ROW_FORMAT FROM INFORMATION_SCHEMA.INNODB_SYS_TABLES WHERE NAME='test1/t1';
+----------+------------+
| NAME | ROW_FORMAT |
+----------+------------+
| test1/t1 | Dynamic |
+----------+------------+
The REDUNDANT
format is available to retain
compatibility with older versions of MySQL.
Rows in InnoDB
tables that use
REDUNDANT
row format have the following
characteristics:
Each index record contains a 6-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 6-byte transaction ID field and a 7-byte roll pointer field.
If no primary key was defined for a table, each clustered index record also contains a 6-byte row ID field.
Each secondary index record also contains all the primary key fields defined for the clustered index key that are not in the secondary index.
A record contains 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
does not truncate
trailing spaces from
VARCHAR
columns.
InnoDB
encodes fixed-length fields
greater than or equal to 768 bytes in length as
variable-length fields, which can be stored off-page. For
example, a CHAR(255)
column can exceed
768 bytes if the maximum byte length of the character set
is greater than 3, as it is with
utf8mb4
.
An SQL NULL
value reserves one or two
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.
Reserving the fixed space for NULL
values 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.
The COMPACT
row format decreases row
storage space by about 20% compared to the
REDUNDANT
format at the cost of increasing
CPU use for some operations. If your workload is a typical one
that is limited by cache hit rates and disk speed,
COMPACT
format is likely to be faster. If
the workload is a rare case that is limited by CPU speed,
compact format might be slower.
Rows in InnoDB
tables that use
COMPACT
row format have the following
characteristics:
Each index record contains a 5-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 variable-length part of the record header contains a
bit vector for indicating NULL
columns.
If the number of columns in the index that can be
NULL
is N
,
the bit vector occupies
CEILING(
bytes. (For example, if there are anywhere from 9 to 16
columns that can be N
/8)NULL
, the bit
vector uses two bytes.) Columns that are
NULL
do not occupy space other than the
bit in this vector. The variable-length part of the header
also contains the lengths of variable-length columns. Each
length takes one or two bytes, depending on the maximum
length of the column. If all columns in the index are
NOT NULL
and have a fixed length, the
record header has no variable-length part.
For each non-NULL
variable-length
field, the record header contains the length of the column
in one or two bytes. Two bytes are only needed if part of
the column is stored externally in overflow pages or the
maximum length exceeds 255 bytes and the actual length
exceeds 127 bytes. For an externally stored column, the
2-byte length indicates the length of the internally
stored part plus the 20-byte pointer to the externally
stored part. The internal part is 768 bytes, so the length
is 768+20. The 20-byte pointer stores the true length of
the column.
The record header is followed by the data contents of the
non-NULL
columns.
Records in the clustered index contain fields for all user-defined columns. In addition, there is a 6-byte transaction ID field and a 7-byte roll pointer field.
If no primary key was defined for a table, each clustered index record also contains a 6-byte row ID field.
Each secondary index record also contains all the primary key fields defined for the clustered index key that are not in the secondary index. If any of these primary key fields are variable length, the record header for each secondary index has a variable-length part to record their lengths, even if the secondary index is defined on fixed-length columns.
Internally, for nonvariable-length character sets,
InnoDB
stores fixed-length character
columns such as CHAR(10)
in
a fixed-length format.
InnoDB
does not truncate trailing
spaces from VARCHAR
columns.
Internally, for variable-length character sets such as
utf8mb3
and utf8mb4
,
InnoDB
attempts to store
CHAR(
in N
)N
bytes by trimming trailing
spaces. If the byte length of a
CHAR(
column value exceeds N
)N
bytes,
InnoDB
trims trailing spaces to a
minimum of the column value byte length. The maximum
length of a
CHAR(
column is the maximum character byte length ×
N
)N
.
InnoDB
reserves a minimum of
N
bytes for
CHAR(
.
Reserving the minimum space N
)N
in many cases enables column updates to be done in place
without causing fragmentation of the index page. By
comparison, for ROW_FORMAT=REDUNDANT
,
CHAR(
columns occupy the maximum character byte length ×
N
)N
.
InnoDB
encodes fixed-length fields
greater than or equal to 768 bytes in length as
variable-length fields, which can be stored off-page. For
example, a CHAR(255)
column can exceed
768 bytes if the maximum byte length of the character set
is greater than 3, as it is with
utf8mb4
.
ROW_FORMAT=DYNAMIC
and
ROW_FORMAT=COMPRESSED
handle
CHAR
storage in the same
way as ROW_FORMAT=COMPACT
.
DYNAMIC
and COMPRESSED
row formats are variations of the COMPACT
row format. For information about these row formats, see
Section 14.11.3, “DYNAMIC and COMPRESSED Row Formats”.
This section describes techniques for moving or copying some or all
InnoDB
tables to a different server or instance.
For example, you might move an entire MySQL instance to a larger,
faster server; you might clone an entire MySQL instance to a new
replication slave server; you might copy individual tables to
another instance to develop and test an application, or to a data
warehouse server to produce reports.
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, create all
databases and tables using lowercase names. 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
Techniques for moving or copying InnoDB
tables
include:
The transportable tablespaces feature uses
FLUSH
TABLES ... FOR EXPORT
to ready InnoDB
tables for copying from one server instance to another. To use this
feature, InnoDB
tables must be created with
innodb_file_per_table
set to
ON
so that each InnoDB
table
has its own tablespace. For usage information, see
Section 14.7.6, “Copying File-Per-Table Tablespaces to Another Instance”.
The MySQL Enterprise Backup product lets you back up a running MySQL database with minimal disruption to operations while producing a consistent snapshot of the database. When MySQL Enterprise Backup is copying tables, reads and writes can continue. In addition, MySQL Enterprise Backup can create compressed backup files, and back up subsets of tables. In conjunction with the MySQL binary log, you can perform point-in-time recovery. MySQL Enterprise Backup is included as part of the MySQL Enterprise subscription.
For more details about MySQL Enterprise Backup, see Section 29.2, “MySQL Enterprise Backup Overview”.
You can move an InnoDB
database simply by copying
all the relevant files listed under "Cold Backups" in
Section 14.18.1, “InnoDB Backup”.
InnoDB
data and log files are binary-compatible
on all platforms having the same floating-point number format. 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.
When you move or copy file-per-table .ibd
files, the database directory name must be the same on the source
and destination systems. The table definition stored in the
InnoDB
shared tablespace includes the database
name. The transaction IDs and log sequence numbers stored in the
tablespace files also differ between databases.
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:
The table must not have been dropped or truncated since you
copied the .ibd
file, because doing so
changes the table ID stored inside the tablespace.
Issue this ALTER TABLE
statement
to delete the current .ibd
file:
ALTER TABLE tbl_name
DISCARD TABLESPACE;
Copy the backup .ibd
file to the proper
database directory.
Issue this ALTER TABLE
statement
to tell InnoDB
to use the new
.ibd
file for the table:
ALTER TABLE tbl_name
IMPORT TABLESPACE;
The ALTER TABLE
... IMPORT TABLESPACE
feature does not enforce
foreign key constraints on imported data.
In this context, a “clean” .ibd
file backup is one for which the following requirements are
satisfied:
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 MySQL Enterprise Backup
product:
Use MySQL Enterprise 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 mysqldump to dump your tables on one machine and then import the dump files on the other machine. Using this method, it does not matter whether the formats differ or if your tables contain floating-point data.
One way to increase the performance of this method 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.
If you have MyISAM
tables that you want
to convert to InnoDB
for better
reliability and scalability, review the following guidelines and
tips before converting.
As you transition away from MyISAM
tables,
lower the value of the
key_buffer_size
configuration
option to free memory no longer needed for caching results.
Increase the value of the
innodb_buffer_pool_size
configuration option, which performs a similar role of allocating
cache memory for InnoDB
tables. The
InnoDB
buffer
pool caches both table data and index data, speeding up
lookups for queries and keeping query results in memory for reuse.
For guidance regarding buffer pool size configuration, see
Section 8.12.4.1, “How MySQL Uses Memory”.
On a busy server, run benchmarks with the query cache turned off.
The InnoDB
buffer pool provides similar
benefits, so the query cache might be tying up memory
unnecessarily. For information about the query cache, see
Section 8.10.3, “The MySQL Query Cache”.
Because MyISAM
tables do not support
transactions, you might
not have paid much attention to the
autocommit
configuration option
and the COMMIT
and
ROLLBACK
statements. These keywords are important to allow multiple
sessions to read and write InnoDB
tables
concurrently, providing substantial scalability benefits in
write-heavy workloads.
While a transaction is open, the system keeps a snapshot of the data as seen at the beginning of the transaction, which can cause substantial overhead if the system inserts, updates, and deletes millions of rows while a stray transaction keeps running. Thus, take care to avoid transactions that run for too long:
If you are using a mysql session for
interactive experiments, always
COMMIT
(to finalize the
changes) or
ROLLBACK
(to
undo the changes) when finished. Close down interactive
sessions rather than leave them open for long periods, to
avoid keeping transactions open for long periods by accident.
Make sure that any error handlers in your application also
ROLLBACK
incomplete changes or COMMIT
completed changes.
ROLLBACK
is
a relatively expensive operation, because
INSERT
,
UPDATE
, and
DELETE
operations are written
to InnoDB
tables prior to the
COMMIT
, with the expectation
that most changes are committed successfully and rollbacks are
rare. When experimenting with large volumes of data, avoid
making changes to large numbers of rows and then rolling back
those changes.
When loading large volumes of data with a sequence of
INSERT
statements, periodically
COMMIT
the results to avoid
having transactions that last for hours. In typical load
operations for data warehousing, if something goes wrong, you
truncate the table (using TRUNCATE
TABLE
) and start over from the beginning rather than
doing a
ROLLBACK
.
The preceding tips save memory and disk space that can be wasted
during too-long transactions. When transactions are shorter than
they should be, the problem is excessive I/O. With each
COMMIT
, MySQL makes sure each
change is safely recorded to disk, which involves some I/O.
For most operations on InnoDB
tables, you
should use the setting
autocommit=0
. From an
efficiency perspective, this avoids unnecessary I/O when you
issue large numbers of consecutive
INSERT
,
UPDATE
, or
DELETE
statements. From a
safety perspective, this allows you to issue a
ROLLBACK
statement to recover lost or garbled data if you make a
mistake on the mysql command line, or in an
exception handler in your application.
The time when autocommit=1
is
suitable for InnoDB
tables is when running
a sequence of queries for generating reports or analyzing
statistics. In this situation, there is no I/O penalty related
to COMMIT
or
ROLLBACK
,
and InnoDB
can
automatically
optimize the read-only workload.
If you make a series of related changes, finalize all the
changes at once with a single
COMMIT
at the end. For example,
if you insert related pieces of information into several
tables, do a single COMMIT
after making all the changes. Or if you run many consecutive
INSERT
statements, do a single
COMMIT
after all the data is
loaded; if you are doing millions of
INSERT
statements, perhaps
split up the huge transaction by issuing a
COMMIT
every ten thousand or
hundred thousand records, so the transaction does not grow too
large.
Remember that even a SELECT
statement opens a transaction, so after running some report or
debugging queries in an interactive mysql
session, either issue a COMMIT
or close the mysql session.
You might see warning messages referring to
“deadlocks” in the MySQL error log, or the output of
SHOW ENGINE INNODB
STATUS
. Despite the scary-sounding name, a
deadlock is not a serious
issue for InnoDB
tables, and often does not
require any corrective action. When two transactions start
modifying multiple tables, accessing the tables in a different
order, they can reach a state where each transaction is waiting
for the other and neither can proceed. When
deadlock detection
is enabled (the default), MySQL immediately detects this condition
and cancels (rolls back) the
“smaller” transaction, allowing the other to proceed.
If deadlock detection is disabled using the
innodb_deadlock_detect
configuration option, InnoDB
relies on the
innodb_lock_wait_timeout
setting
to roll back transactions in case of a deadlock.
Either way, your applications need error-handling logic to restart a transaction that is forcibly cancelled due to a deadlock. When you re-issue the same SQL statements as before, the original timing issue no longer applies. Either the other transaction has already finished and yours can proceed, or the other transaction is still in progress and your transaction waits until it finishes.
If deadlock warnings occur constantly, you might review the
application code to reorder the SQL operations in a consistent
way, or to shorten the transactions. You can test with the
innodb_print_all_deadlocks
option
enabled to see all deadlock warnings in the MySQL error log,
rather than only the last warning in the
SHOW ENGINE INNODB
STATUS
output.
For more information, see Section 14.5.5, “Deadlocks in InnoDB”.
To get the best performance from InnoDB
tables,
you can adjust a number of parameters related to storage layout.
When you convert MyISAM
tables that are large,
frequently accessed, and hold vital data, investigate and consider
the innodb_file_per_table
,
innodb_file_format
, and
innodb_page_size
configuration
options, and the
ROW_FORMAT
and KEY_BLOCK_SIZE
clauses of the
CREATE TABLE
statement.
During your initial experiments, the most important setting is
innodb_file_per_table
. When this
setting is enabled, which is the default as of MySQL 5.6.6, new
InnoDB
tables are implicitly created in
file-per-table
tablespaces. In contrast with the InnoDB
system
tablespace, file-per-table tablespaces allow disk space to be
reclaimed by the operating system when a table is truncated or
dropped. File-per-table tablespaces also support the
Barracuda file format and
associated features such as table compression, efficient off-page
storage for long variable-length columns, and large index
prefixes. For more information, see
Section 14.7.4, “InnoDB File-Per-Table Tablespaces”.
You can also store InnoDB
tables in a shared
general tablespace. General tablespaces support the Barracuda file
format and can contain multiple tables. For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
To convert a non-InnoDB
table to use
InnoDB
use ALTER
TABLE
:
ALTER TABLE table_name
ENGINE=InnoDB;
Do not convert MySQL system tables in the
mysql
database from MyISAM
to the InnoDB
type. This is an unsupported
operation. type.
You might make an InnoDB
table that is a clone
of a MyISAM table, rather than using ALTER
TABLE
to perform conversion, to test the old and new
table side-by-side before switching.
Create an empty InnoDB
table with identical
column and index definitions. Use SHOW CREATE TABLE
to see the full
table_name
\GCREATE TABLE
statement to use.
Change the ENGINE
clause to
ENGINE=INNODB
.
To transfer a large volume of data into an empty
InnoDB
table created as shown in the previous
section, insert the rows with INSERT INTO
.
innodb_table
SELECT * FROM
myisam_table
ORDER BY
primary_key_columns
You can also create the indexes for the InnoDB
table after inserting the data. Historically, creating new
secondary indexes was a slow operation for InnoDB, but now you can
create the indexes after the data is loaded with relatively little
overhead from the index creation step.
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 disk I/O because
InnoDB
can use its
change buffer to write
secondary index records as a batch. Be certain that the data
contains no duplicate keys.
unique_checks
permits but does
not require storage engines to ignore duplicate keys.
For better control over the insertion process, you can insert big tables in pieces:
INSERT INTO newtable SELECT * FROM oldtable WHERE yourkey >something
AND yourkey <=somethingelse
;
After all records are inserted, you can rename the tables.
During the conversion of big tables, increase the size of the
InnoDB
buffer pool to reduce disk I/O, to a
maximum of 80% of physical memory. You can also increase the size
of InnoDB
log files.
If you intend to make several temporary copies of your data in
InnoDB
tables during the conversion process, it
is recommended that you create the tables in file-per-table
tablespaces so that you can reclaim the disk space when you drop
the tables. When the
innodb_file_per_table
configuration option is enabled (the default), newly created
InnoDB
tables are implicitly created in
file-per-table tablespaces.
Whether you convert the MyISAM
table directly
or create a cloned InnoDB
table, make sure that
you have sufficient disk space to hold both the old and new tables
during the process.
InnoDB
tables require
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 14.21.2, “Forcing InnoDB Recovery”.
The PRIMARY KEY
clause is a critical factor
affecting the performance of MySQL queries and the space usage for
tables and indexes. The primary key uniquely identifies a row in a
table. Every row in the table must have a primary key value, and
no two rows can have the same primary key value.
These are guidelines for the primary key, followed by more detailed explanations.
Declare a PRIMARY KEY
for each table.
Typically, it is the most important column that you refer to
in WHERE
clauses when looking up a single
row.
Declare the PRIMARY KEY
clause in the
original CREATE TABLE
statement, rather than adding it later through an
ALTER TABLE
statement.
Choose the column and its data type carefully. Prefer numeric columns over character or string ones.
Consider using an auto-increment column if there is not another stable, unique, non-null, numeric column to use.
An auto-increment column is also a good choice if there is any doubt whether the value of the primary key column could ever change. Changing the value of a primary key column is an expensive operation, possibly involving rearranging data within the table and within each secondary index.
Consider adding a primary key to any table that does not already have one. Use the smallest practical numeric type based on the maximum projected size of the table. This can make each row slightly more compact, which can yield substantial space savings for large tables. The space savings are multiplied if the table has any secondary indexes, because the primary key value is repeated in each secondary index entry. In addition to reducing data size on disk, a small primary key also lets more data fit into the buffer pool, speeding up all kinds of operations and improving concurrency.
If the table already has a primary key on some longer column, such
as a VARCHAR
, consider adding a new unsigned
AUTO_INCREMENT
column and switching the primary
key to that, even if that column is not referenced in queries.
This design change can produce substantial space savings in the
secondary indexes. You can designate the former primary key
columns as UNIQUE NOT NULL
to enforce the same
constraints as the PRIMARY KEY
clause, that is,
to prevent duplicate or null values across all those columns.
If you spread related information across multiple tables, typically each table uses the same column for its primary key. For example, a personnel database might have several tables, each with a primary key of employee number. A sales database might have some tables with a primary key of customer number, and other tables with a primary key of order number. Because lookups using the primary key are very fast, you can construct efficient join queries for such tables.
If you leave the PRIMARY KEY
clause out
entirely, MySQL creates an invisible one for you. It is a 6-byte
value that might be longer than you need, thus wasting space.
Because it is hidden, you cannot refer to it in queries.
The reliability and scalability features of
InnoDB
require more disk storage than
equivalent MyISAM
tables. You might change the
column and index definitions slightly, for better space
utilization, reduced I/O and memory consumption when processing
result sets, and better query optimization plans making efficient
use of index lookups.
If you do set up a numeric ID column for the primary key, use that
value to cross-reference with related values in any other tables,
particularly for join queries.
For example, rather than accepting a country name as input and
doing queries searching for the same name, do one lookup to
determine the country ID, then do other queries (or a single join
query) to look up relevant information across several tables.
Rather than storing a customer or catalog item number as a string
of digits, potentially using up several bytes, convert it to a
numeric ID for storing and querying. A 4-byte unsigned
INT
column can index over 4 billion
items (with the US meaning of billion: 1000 million). For the
ranges of the different integer types, see
Section 11.2.1, “Integer Types (Exact Value) - INTEGER, INT, SMALLINT, TINYINT,
MEDIUMINT, BIGINT”.
InnoDB
files require more care and planning
than MyISAM
files do.
You must not delete the
ibdata files that
represent the InnoDB
system
tablespace.
Methods of moving or copying InnoDB
tables
to a different server are described in
Section 14.8.1.3, “Moving or Copying InnoDB Tables”.
InnoDB
provides a configurable locking
mechanism that can significantly improve scalability and
performance of SQL statements that add rows to tables with
AUTO_INCREMENT
columns. To use the
AUTO_INCREMENT
mechanism with an
InnoDB
table, an
AUTO_INCREMENT
column must be defined as part
of an index such that it is possible to perform the equivalent
of an indexed SELECT
MAX(
lookup on the
table to obtain the maximum column value. Typically, this is
achieved by making the column the first column of some table
index.
ai_col
)
This section describes the behavior of
AUTO_INCREMENT
lock modes, usage implications
for different AUTO_INCREMENT
lock mode
settings, and how InnoDB
initializes the
AUTO_INCREMENT
counter.
This section describes the behavior of
AUTO_INCREMENT
lock modes used to generate
auto-increment values, and how each lock mode affects
replication. Auto-increment lock modes are configured at
startup using the
innodb_autoinc_lock_mode
configuration parameter.
The following terms are used in describing
innodb_autoinc_lock_mode
settings:
“INSERT
-like”
statements
All statements that generate new rows in a table,
including INSERT
,
INSERT ...
SELECT
, REPLACE
,
REPLACE ...
SELECT
, and LOAD
DATA
. Includes “simple-inserts”,
“bulk-inserts”, and “mixed-mode”
inserts.
“Simple inserts”
Statements for which the number of rows to be inserted can
be determined in advance (when the statement is initially
processed). This includes single-row and multiple-row
INSERT
and
REPLACE
statements that do
not have a nested subquery, but not
INSERT
... ON DUPLICATE KEY UPDATE
.
“Bulk inserts”
Statements for which the number of rows to be inserted
(and the number of required auto-increment values) is not
known in advance. This includes
INSERT ...
SELECT
,
REPLACE ...
SELECT
, and LOAD
DATA
statements, but not plain
INSERT
. InnoDB
assigns new values for the
AUTO_INCREMENT
column one at a time as
each row is processed.
“Mixed-mode inserts”
These are “simple insert” statements that
specify the auto-increment value for some (but not all) of
the new rows. An example follows, where
c1
is an
AUTO_INCREMENT
column of table
t1
:
INSERT INTO t1 (c1,c2) VALUES (1,'a'), (NULL,'b'), (5,'c'), (NULL,'d');
Another type of “mixed-mode insert” is
INSERT
... ON DUPLICATE KEY UPDATE
, which in the worst
case is in effect an INSERT
followed by a UPDATE
, where
the allocated value for the
AUTO_INCREMENT
column may or may not be
used during the update phase.
There are three possible settings for the
innodb_autoinc_lock_mode
configuration parameter. The settings are 0, 1, or 2, for
“traditional”, “consecutive”, or
“interleaved” lock mode, respectively.
innodb_autoinc_lock_mode = 0
(“traditional” lock mode)
The traditional lock mode provides the same behavior that
existed before the
innodb_autoinc_lock_mode
configuration parameter was introduced in MySQL 5.1. The
traditional lock mode option is provided for backward
compatibility, performance testing, and working around
issues with “mixed-mode inserts”, due to possible
differences in semantics.
In this lock mode, all “INSERT-like”
statements obtain a special table-level
AUTO-INC
lock for inserts into tables
with AUTO_INCREMENT
columns. This lock
is normally held to the end of the statement (not to the
end of the transaction) to ensure that auto-increment
values are assigned in a predictable and repeatable order
for a given sequence of
INSERT
statements, and to
ensure that auto-increment values assigned by any given
statement are consecutive.
In the case of statement-based replication, this means
that when an SQL statement is replicated on a slave
server, the same values are used for the auto-increment
column as on the master server. The result of execution of
multiple INSERT
statements
is deterministic, and the slave reproduces the same data
as on the master. If auto-increment values generated by
multiple INSERT
statements
were interleaved, the result of two concurrent
INSERT
statements would be
nondeterministic, and could not reliably be propagated to
a slave server using statement-based replication.
To make this clear, consider an example that uses this table:
CREATE TABLE t1 ( c1 INT(11) NOT NULL AUTO_INCREMENT, c2 VARCHAR(10) DEFAULT NULL, PRIMARY KEY (c1) ) ENGINE=InnoDB;
Suppose that there are two transactions running, each
inserting rows into a table with an
AUTO_INCREMENT
column. One transaction
is using an
INSERT ...
SELECT
statement that inserts 1000 rows, and
another is using a simple
INSERT
statement that
inserts one row:
Tx1: INSERT INTO t1 (c2) SELECT 1000 rows from another table ... Tx2: INSERT INTO t1 (c2) VALUES ('xxx');
InnoDB
cannot tell in advance how many
rows are retrieved from the
SELECT
in the
INSERT
statement in Tx1,
and it assigns the auto-increment values one at a time as
the statement proceeds. With a table-level lock, held to
the end of the statement, only one
INSERT
statement referring
to table t1
can execute at a time, and
the generation of auto-increment numbers by different
statements is not interleaved. The auto-increment value
generated by the Tx1
INSERT ...
SELECT
statement is consecutive, and the
(single) auto-increment value used by the
INSERT
statement in Tx2 is
either be smaller or larger than all those used for Tx1,
depending on which statement executes first.
As long as the SQL statements execute in the same order
when replayed from the binary log (when using
statement-based replication, or in recovery scenarios),
the results are the same as they were when Tx1 and Tx2
first ran. Thus, table-level locks held until the end of a
statement make INSERT
statements using auto-increment safe for use with
statement-based replication. However, those table-level
locks limit concurrency and scalability when multiple
transactions are executing insert statements at the same
time.
In the preceding example, if there were no table-level
lock, the value of the auto-increment column used for the
INSERT
in Tx2 depends on
precisely when the statement executes. If the
INSERT
of Tx2 executes
while the INSERT
of Tx1 is
running (rather than before it starts or after it
completes), the specific auto-increment values assigned by
the two INSERT
statements
are nondeterministic, and may vary from run to run.
Under the
consecutive
lock mode, InnoDB
can avoid using
table-level AUTO-INC
locks for
“simple insert” statements where the number
of rows is known in advance, and still preserve
deterministic execution and safety for statement-based
replication.
If you are not using the binary log to replay SQL
statements as part of recovery or replication, the
interleaved
lock mode can be used to eliminate all use of table-level
AUTO-INC
locks for even greater
concurrency and performance, at the cost of permitting
gaps in auto-increment numbers assigned by a statement and
potentially having the numbers assigned by concurrently
executing statements interleaved.
innodb_autoinc_lock_mode = 1
(“consecutive” lock mode)
This is the default lock mode. In this mode, “bulk
inserts” use the special
AUTO-INC
table-level lock and hold it
until the end of the statement. This applies to all
INSERT ...
SELECT
,
REPLACE ...
SELECT
, and LOAD
DATA
statements. Only one statement holding the
AUTO-INC
lock can execute at a time. If
the source table of the bulk insert operation is different
from the target table, the AUTO-INC
lock on the target table is taken after a shared lock is
taken on the first row selected from the source table. If
the source and target of the bulk insert operation are the
same table, the AUTO-INC
lock is taken
after shared locks are taken on all selected rows.
“Simple inserts” (for which the number of
rows to be inserted is known in advance) avoid table-level
AUTO-INC
locks by obtaining the
required number of auto-increment values under the control
of a mutex (a light-weight lock) that is only held for the
duration of the allocation process,
not until the statement completes. No
table-level AUTO-INC
lock is used
unless an AUTO-INC
lock is held by
another transaction. If another transaction holds an
AUTO-INC
lock, a “simple
insert” waits for the AUTO-INC
lock, as if it were a “bulk insert”.
This lock mode ensures that, in the presence of
INSERT
statements where the
number of rows is not known in advance (and where
auto-increment numbers are assigned as the statement
progresses), all auto-increment values assigned by any
“INSERT
-like”
statement are consecutive, and operations are safe for
statement-based replication.
Simply put, this lock mode significantly improves scalability while being safe for use with statement-based replication. Further, as with “traditional” lock mode, auto-increment numbers assigned by any given statement are consecutive. There is no change in semantics compared to “traditional” mode for any statement that uses auto-increment, with one important exception.
The exception is for “mixed-mode inserts”,
where the user provides explicit values for an
AUTO_INCREMENT
column for some, but not
all, rows in a multiple-row “simple insert”.
For such inserts, InnoDB
allocates more
auto-increment values than the number of rows to be
inserted. However, all values automatically assigned are
consecutively generated (and thus higher than) the
auto-increment value generated by the most recently
executed previous statement. “Excess” numbers
are lost.
innodb_autoinc_lock_mode = 2
(“interleaved” lock mode)
In this lock mode, no
“INSERT
-like”
statements use the table-level AUTO-INC
lock, and multiple statements can execute at the same
time. This is the fastest and most scalable lock mode, but
it is not safe when using
statement-based replication or recovery scenarios when SQL
statements are replayed from the binary log.
In this lock mode, auto-increment values are guaranteed to
be unique and monotonically increasing across all
concurrently executing
“INSERT
-like”
statements. However, because multiple statements can be
generating numbers at the same time (that is, allocation
of numbers is interleaved across
statements), the values generated for the rows inserted by
any given statement may not be consecutive.
If the only statements executing are “simple inserts” where the number of rows to be inserted is known ahead of time, there are no gaps in the numbers generated for a single statement, except for “mixed-mode inserts”. However, when “bulk inserts” are executed, there may be gaps in the auto-increment values assigned by any given statement.
Using auto-increment with replication
If you are using statement-based replication, set
innodb_autoinc_lock_mode
to 0 or 1 and use the same value on the master and its
slaves. Auto-increment values are not ensured to be the
same on the slaves as on the master if you use
innodb_autoinc_lock_mode
= 2 (“interleaved”) or configurations where
the master and slaves do not use the same lock mode.
If you are using row-based or mixed-format replication, all of the auto-increment lock modes are safe, since row-based replication is not sensitive to the order of execution of the SQL statements (and the mixed format uses row-based replication for any statements that are unsafe for statement-based replication).
“Lost” auto-increment values and sequence gaps
In all lock modes (0, 1, and 2), if a transaction that
generated auto-increment values rolls back, those
auto-increment values are “lost”. Once a
value is generated for an auto-increment column, it cannot
be rolled back, whether or not the
“INSERT
-like”
statement is completed, and whether or not the containing
transaction is rolled back. Such lost values are not
reused. Thus, there may be gaps in the values stored in an
AUTO_INCREMENT
column of a table.
Specifying NULL or 0 for the
AUTO_INCREMENT
column
In all lock modes (0, 1, and 2), if a user specifies NULL
or 0 for the AUTO_INCREMENT
column in
an INSERT
,
InnoDB
treats the row as if the value
was not specified and generates a new value for it.
Assigning a negative value to the
AUTO_INCREMENT
column
In all lock modes (0, 1, and 2), the behavior of the
auto-increment mechanism is not defined if you assign a
negative value to the AUTO_INCREMENT
column.
If the AUTO_INCREMENT
value becomes
larger than the maximum integer for the specified integer
type
In all lock modes (0, 1, and 2), the behavior of the auto-increment mechanism is not defined if the value becomes larger than the maximum integer that can be stored in the specified integer type.
Gaps in auto-increment values for “bulk inserts”
With
innodb_autoinc_lock_mode
set to 0 (“traditional”) or 1
(“consecutive”), the auto-increment values
generated by any given statement are consecutive, without
gaps, because the table-level AUTO-INC
lock is held until the end of the statement, and only one
such statement can execute at a time.
With
innodb_autoinc_lock_mode
set to 2 (“interleaved”), there may be gaps
in the auto-increment values generated by “bulk
inserts,” but only if there are concurrently
executing
“INSERT
-like”
statements.
For lock modes 1 or 2, gaps may occur between successive statements because for bulk inserts the exact number of auto-increment values required by each statement may not be known and overestimation is possible.
Auto-increment values assigned by “mixed-mode inserts”
Consider a “mixed-mode insert,” where a
“simple insert” specifies the auto-increment
value for some (but not all) resulting rows. Such a
statement behaves differently in lock modes 0, 1, and 2.
For example, assume c1
is an
AUTO_INCREMENT
column of table
t1
, and that the most recent
automatically generated sequence number is 100.
mysql>CREATE TABLE t1 (
->c1 INT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY,
->c2 CHAR(1)
->) ENGINE = INNODB;
Now, consider the following “mixed-mode insert” statement:
mysql> INSERT INTO t1 (c1,c2) VALUES (1,'a'), (NULL,'b'), (5,'c'), (NULL,'d');
With
innodb_autoinc_lock_mode
set to 0 (“traditional”), the four new rows
are:
mysql> SELECT c1, c2 FROM t1 ORDER BY c2;
+-----+------+
| c1 | c2 |
+-----+------+
| 1 | a |
| 101 | b |
| 5 | c |
| 102 | d |
+-----+------+
The next available auto-increment value is 103 because the
auto-increment values are allocated one at a time, not all
at once at the beginning of statement execution. This
result is true whether or not there are concurrently
executing
“INSERT
-like”
statements (of any type).
With
innodb_autoinc_lock_mode
set to 1 (“consecutive”), the four new rows
are also:
mysql> SELECT c1, c2 FROM t1 ORDER BY c2;
+-----+------+
| c1 | c2 |
+-----+------+
| 1 | a |
| 101 | b |
| 5 | c |
| 102 | d |
+-----+------+
However, in this case, the next available auto-increment
value is 105, not 103 because four auto-increment values
are allocated at the time the statement is processed, but
only two are used. This result is true whether or not
there are concurrently executing
“INSERT
-like”
statements (of any type).
With
innodb_autoinc_lock_mode
set to mode 2 (“interleaved”), the four new
rows are:
mysql>SELECT c1, c2 FROM t1 ORDER BY c2;
+-----+------+ | c1 | c2 | +-----+------+ | 1 | a | |x
| b | | 5 | c | |y
| d | +-----+------+
The values of x
and
y
are unique and larger than
any previously generated rows. However, the specific
values of x
and
y
depend on the number of
auto-increment values generated by concurrently executing
statements.
Finally, consider the following statement, issued when the most-recently generated sequence number is 100:
mysql> INSERT INTO t1 (c1,c2) VALUES (1,'a'), (NULL,'b'), (101,'c'), (NULL,'d');
With any
innodb_autoinc_lock_mode
setting, this statement generates a duplicate-key error
23000 (Can't write; duplicate key in
table
) because 101 is allocated for the row
(NULL, 'b')
and insertion of the row
(101, 'c')
fails.
Modifying AUTO_INCREMENT
column values
in the middle of a sequence of
INSERT
statements
In all lock modes (0, 1, and 2), modifying an
AUTO_INCREMENT
column value in the
middle of a sequence of
INSERT
statements could
lead to “Duplicate entry” errors. For
example, if you perform an
UPDATE
operation that
changes an AUTO_INCREMENT
column value
to a value larger than the current maximum auto-increment
value, subsequent INSERT
operations that do not specify an unused auto-increment
value could encounter “Duplicate entry”
errors. This behavior is demonstrated in the following
example.
mysql>CREATE TABLE t1 (
->c1 INT NOT NULL AUTO_INCREMENT,
->PRIMARY KEY (c1)
->) ENGINE = InnoDB;
mysql>INSERT INTO t1 VALUES(0), (0), (3);
mysql>SELECT c1 FROM t1;
+----+ | c1 | +----+ | 1 | | 2 | | 3 | +----+ mysql>UPDATE t1 SET c1 = 4 WHERE c1 = 1;
mysql>SELECT c1 FROM t1;
+----+ | c1 | +----+ | 2 | | 3 | | 4 | +----+ mysql>INSERT INTO t1 VALUES(0);
ERROR 1062 (23000): Duplicate entry '4' for key 'PRIMARY'
This section describes how InnoDB
initializes AUTO_INCREMENT
counters.
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.
To initialize an auto-increment counter after a server
restart, InnoDB
executes the equivalent of
the following statement on the first insert into a table
containing an AUTO_INCREMENT
column.
SELECT MAX(ai_col) FROM table_name
FOR UPDATE;
InnoDB
increments the value retrieved by
the statement and assigns it to the column and to the
auto-increment counter for the table. By default, the value is
incremented by 1. This default can be overridden by the
auto_increment_increment
configuration setting.
If the table is empty, InnoDB
uses the
value 1
. This default can be overridden by
the auto_increment_offset
configuration setting.
If a SHOW TABLE STATUS
statement examines the table before the auto-increment counter
is initialized, InnoDB
initializes but does
not increment the value. The value is stored 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
newly created table.
After the auto-increment counter has been initialized, if you
do not explicitly specify a value for an
AUTO_INCREMENT
column,
InnoDB
increments the counter and assigns
the new value to the column. If you insert a row that
explicitly specifies the column value, and the value is
greater than the current counter value, the counter is set to
the specified column value.
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.
A server restart also cancels the effect of the
AUTO_INCREMENT =
table option in
N
CREATE TABLE
and
ALTER TABLE
statements, which
you can use with InnoDB
tables to set the
initial counter value or alter the current counter value.
How the InnoDB
storage engine handles foreign
key constraints is described under the following topics in this
section:
For foreign key usage information and examples, see Section 13.1.18.6, “Using FOREIGN KEY Constraints”.
Foreign key definitions for InnoDB
tables
are subject to the following conditions:
InnoDB
permits a foreign key to
reference any index column or group of columns. However,
in the referenced table, there must be an index where the
referenced columns are listed as the
first columns in the same order.
InnoDB
does not currently
support foreign keys for tables with user-defined
partitioning. This means that no user-partitioned
InnoDB
table may contain foreign key
references or columns referenced by foreign keys.
InnoDB
allows a foreign key constraint
to reference a nonunique key. This is an
InnoDB
extension to standard
SQL.
Referential actions for foreign keys of
InnoDB
tables are subject to the following
conditions:
While SET DEFAULT
is allowed by the
MySQL Server, it is rejected as invalid by
InnoDB
. CREATE
TABLE
and ALTER
TABLE
statements using this clause are not
allowed for InnoDB tables.
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 permit 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.
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.
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. 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. 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 are impossible, such as deleting a
record that refers to itself using a foreign key.
A foreign key constraint on a
stored
generated column cannot use ON UPDATE
CASCADE
, ON DELETE SET NULL
,
ON UPDATE SET NULL
, ON DELETE
SET DEFAULT
, or ON UPDATE SET
DEFAULT
.
A foreign key constraint cannot reference a virtual generated column.
Prior to 5.7.16, a foreign key constraint cannot reference a secondary index defined on a virtual generated column.
In MySQL 5.7.13 and earlier, InnoDB
does not permit defining a foreign key constraint with a
cascading referential action on the
base column of an
indexed virtual generated column. This restriction is
lifted in MySQL 5.7.14.
In MySQL 5.7.13 and earlier, InnoDB
does not permit defining cascading referential actions on
non-virtual foreign key columns that are explicitly
included in a virtual
index. This restriction is lifted in MySQL 5.7.14.
You can obtain general information about foreign keys and
their usage from querying the
INFORMATION_SCHEMA.KEY_COLUMN_USAGE
table, and more information more specific to
InnoDB
tables can be found in the
INNODB_SYS_FOREIGN
and
INNODB_SYS_FOREIGN_COLS
tables,
also in the INFORMATION_SCHEMA
database.
In addition to SHOW ERRORS
, in
the event of a foreign key error involving
InnoDB
tables (usually Error 150 in the
MySQL Server), you can obtain a detailed explanation of the
most recent InnoDB
foreign key error by
checking the output of
SHOW ENGINE
INNODB STATUS
.
Limits on InnoDB
tables are described under
the following topics in this section:
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 regenerate them by reinitializing the data directory
(see Section 2.10.1, “Initializing the Data Directory”).
Before using NFS with InnoDB
, review
potential issues outlined in
Using NFS with MySQL.
A table can contain a maximum of 1017 columns (raised in MySQL 5.6.9 from the earlier limit of 1000). Virtual generated columns are included in this limit.
A table can contain a maximum of 64 secondary indexes.
If innodb_large_prefix
is
enabled (the default), the index key prefix limit is 3072
bytes for InnoDB
tables that use
DYNAMIC
or
COMPRESSED
row format. If
innodb_large_prefix
is
disabled, the index key prefix limit is 767 bytes for
tables of any row format.
innodb_large_prefix
is
deprecated and will be removed in a future release.
innodb_large_prefix
was
introduced in MySQL 5.5 to disable large index key
prefixes for compatibility with earlier versions of
InnoDB
that do not support large index
key prefixes.
The index key prefix length limit is 767 bytes for
InnoDB
tables that use the
REDUNDANT
or
COMPACT
row format. For example, you might hit this limit with a
column prefix
index of more than 255 characters on a
TEXT
or VARCHAR
column, assuming a utf8mb3
character
set and the maximum of 3 bytes for each character.
Attempting to use an index key prefix length that exceeds
the limit returns an error. To avoid such errors in
replication configurations, avoid enabling
innodb_large_prefix
on
the master if it cannot also be enabled on slaves.
The limits that apply to index key prefixes also apply to full-column index keys.
If you reduce the InnoDB
page size to 8KB or
4KB by specifying the
innodb_page_size
option
when creating the MySQL instance, the maximum length of
the index key is lowered proportionally, based on the
limit of 3072 bytes for a 16KB page size. That is, the
maximum index key length is 1536 bytes when the page size
is 8KB, and 768 bytes when the page size is 4KB.
A maximum of 16 columns is permitted for multicolumn indexes. Exceeding the limit returns an error.
ERROR 1070 (42000): Too many key parts specified; max 16 parts allowed
The maximum row length, except for variable-length columns
(VARBINARY
,
VARCHAR
,
BLOB
and
TEXT
), is slightly less
than half of a page for 4KB, 8KB, 16KB, and 32KB page
sizes. For example, the maximum row length for the default
innodb_page_size
of 16KB
is about 8000 bytes. For an InnoDB
page
size of 64KB, the maximum row length is about 16000 bytes.
LONGBLOB
and
LONGTEXT
columns must be less than 4GB, and the total row length,
including BLOB
and
TEXT
columns, must be less
than 4GB.
If a row is less than half a page long, all of it is stored locally within the page. If it exceeds half a page, variable-length columns are chosen for external off-page storage until the row fits within half a page, as described in Section 14.12.2, “File Space Management”.
Although InnoDB
supports row sizes
larger than 65,535 bytes internally, MySQL itself imposes
a row-size limit of 65,535 for the combined size of all
columns:
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
See Section C.10.4, “Limits on Table Column Count and Row Size”.
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, configure
it using several smaller data files rather than one large
data file.
The combined size of the InnoDB
log
files can be up to 512GB.
The minimum tablespace size is slightly larger than 10MB.
The maximum tablespace size depends on the
InnoDB
page size.
Table 14.6 InnoDB Maximum Tablespace Size
InnoDB Page Size | Maximum Tablespace Size |
---|---|
4KB | 16TB |
8KB | 32TB |
16KB | 64TB |
32KB | 128TB |
64KB | 256TB |
The maximum tablespace size is also the maximum size for a table.
The default page size in InnoDB
is
16KB. You can increase or decrease the page size by
configuring the
innodb_page_size
option
when creating the MySQL instance.
ROW_FORMAT=COMPRESSED
in the
Barracuda file
format assumes that the page size is at most 16KB and uses
14-bit pointers.
32KB and 64KB page sizes are supported, but
ROW_FORMAT=COMPRESSED
is unsupported
for page sizes greater than 16KB. For both 32KB and 64KB
page sizes, the maximum record size is 16KB. For
innodb_page_size=32k
,
extent size is 2MB. For
innodb_page_size=64k
,
extent size is 4MB.
A MySQL instance using a particular
InnoDB
page size cannot use data files
or log files from an instance that uses a different page
size.
ANALYZE TABLE
determines
index cardinality (as displayed in the
Cardinality
column of
SHOW INDEX
output) by
performing random
dives on each of the index trees and updating index
cardinality estimates accordingly. Because these are only
estimates, repeated runs of ANALYZE
TABLE
could produce different numbers. This
makes ANALYZE TABLE
fast on
InnoDB
tables but not 100% accurate
because it does not take all rows into account.
You can make the
statistics
collected by ANALYZE TABLE
more precise and more stable by turning on the
innodb_stats_persistent
configuration option, as explained in
Section 14.6.12.1, “Configuring Persistent Optimizer Statistics Parameters”. When that
setting is enabled, it is important to run
ANALYZE TABLE
after major
changes to indexed column data, because the statistics are
not recalculated periodically (such as after a server
restart).
If the persistent statistics setting is enabled, you can
change the number of random dives by modifying the
innodb_stats_persistent_sample_pages
system variable. If the persistent statistics setting is
disabled, modify the
innodb_stats_transient_sample_pages
system variable instead.
MySQL uses index cardinality estimates in join
optimization. If a join is not optimized in the right way,
try using ANALYZE TABLE
. In
the few cases that ANALYZE
TABLE
does not 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 B.5.5, “Optimizer-Related Issues”.
If statements or transactions are running on a table, and
ANALYZE TABLE
is run on the
same table followed by a second
ANALYZE TABLE
operation,
the second ANALYZE TABLE
operation is blocked until the statements or transactions
are completed. This behavior occurs because
ANALYZE TABLE
marks the
currently loaded table definition as obsolete when
ANALYZE TABLE
is finished
running. New statements or transactions (including a
second ANALYZE TABLE
statement) must load the new table definition into the
table cache, which cannot occur until currently running
statements or transactions are completed and the old table
definition is purged. Loading multiple concurrent table
definitions is not supported.
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 because concurrent transactions might
“see” different numbers of rows at the same
time. Consequently, SELECT COUNT(*)
statements only count rows visible to the current
transaction.
Prior to MySQL 5.7.18, InnoDB
processes
SELECT COUNT(*)
statements by scanning
the clustered index. As of MySQL 5.7.18,
InnoDB
processes SELECT
COUNT(*)
statements by traversing a smaller
secondary index, if present.
Processing SELECT COUNT(*)
statements
takes some time if index records are not entirely in the
buffer pool. For a faster count, you can create a counter
table and let your application update it according to the
inserts and deletes it does. However, this method may not
scale well in situations where thousands of concurrent
transactions are initiating updates to the same counter
table. If an approximate row count is sufficient,
SHOW TABLE STATUS
can be
used.
InnoDB
handles SELECT
COUNT(*)
and SELECT COUNT(1)
operations in the same way. There is no performance
difference.
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, create all databases and tables using
lowercase names.
An AUTO_INCREMENT
column
ai_col
must be defined as part
of an index such that it is possible to perform the
equivalent of an indexed SELECT
MAX(
lookup on
the table to obtain the maximum column value. Typically,
this is achieved by making the column the first column of
some table index.
ai_col
)
InnoDB
sets an exclusive lock on the
end of the index associated with the
AUTO_INCREMENT
column while
initializing a previously specified
AUTO_INCREMENT
column on a table.
With
innodb_autoinc_lock_mode=0
,
InnoDB
uses a special
AUTO-INC
table lock mode where the lock
is obtained and held to the end of the current SQL
statement while accessing the auto-increment counter.
Other clients cannot insert into the table while the
AUTO-INC
table lock is held. The same
behavior occurs for “bulk inserts” with
innodb_autoinc_lock_mode=1
.
Table-level AUTO-INC
locks are not used
with
innodb_autoinc_lock_mode=2
.
For more information, See
Section 14.8.1.5, “AUTO_INCREMENT Handling in InnoDB”.
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
integer column
runs out of values, a subsequent INSERT
operation returns a duplicate-key error. This is general
MySQL behavior.
DELETE FROM
does not
regenerate the table but instead deletes all rows, one by
one.
tbl_name
Cascaded foreign key actions do not activate triggers.
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
). This restriction applies to
use of the names in any letter case.
mysql> CREATE TABLE t1 (c1 INT, db_row_id INT) ENGINE=INNODB;
ERROR 1166 (42000): Incorrect column name 'db_row_id'
LOCK TABLES
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. Versions
of MySQL before 4.1.2 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.
In MySQL 5.7,
innodb_table_locks=0
has
no effect for tables locked explicitly with
LOCK TABLES
... WRITE
. It does have an effect for tables
locked for read or write by
LOCK TABLES
... WRITE
implicitly (for example, through
triggers) or by
LOCK TABLES
... READ
.
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.
You cannot lock additional tables in the middle of a
transaction because LOCK
TABLES
performs an implicit
COMMIT
and
UNLOCK
TABLES
.
The limit on data-modifying transactions is 96 * 1023 concurrent transactions that generate undo records. 32 of 128 rollback segments are assigned to non-redo logs for transactions that modify temporary tables and related objects. This reduces the maximum number of concurrent data-modifying transactions from 128K to 96K. The 96K limit assumes that transactions do not modify temporary tables. If all data-modifying transactions also modify temporary tables, the limit is 32K concurrent transactions.
This section covers topics related to InnoDB
indexes.
Every InnoDB
table has a special index called
the clustered index
where the data for the rows is stored. Typically, the clustered
index is synonymous with the
primary key. To get the
best performance from queries, inserts, and other database
operations, you must understand how InnoDB
uses the clustered index to optimize the most common lookup and
DML operations for each table.
When you define a PRIMARY KEY
on your
table, InnoDB
uses it as the clustered
index. Define a primary key for each table that you create.
If there is no logical unique and non-null column or set of
columns, add a new
auto-increment
column, whose values are filled in automatically.
If you do not define a PRIMARY KEY
for
your table, MySQL locates the first
UNIQUE
index where all the key columns
are NOT NULL
and
InnoDB
uses it as the clustered index.
If the table has no PRIMARY KEY
or
suitable UNIQUE
index,
InnoDB
internally generates a hidden
clustered index named GEN_CLUST_INDEX
on
a synthetic column containing row ID values. The rows are
ordered by the 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 index search leads directly to the page with all the row data. If a table is large, the clustered index architecture often saves a disk I/O operation when compared to storage organizations that store row data using a different page from the index record.
All indexes other than the clustered index are known as
secondary indexes.
In InnoDB
, each record in a secondary index
contains the primary key columns for the row, as well as the
columns specified for the secondary index.
InnoDB
uses this primary key value to
search for the row in the clustered index.
If the primary key is long, the secondary indexes use more space, so it is advantageous to have a short primary key.
For guidelines to take advantage of InnoDB
clustered and secondary indexes, see
Section 8.3, “Optimization and Indexes”.
With the exception of spatial indexes, InnoDB
indexes are B-tree data
structures. Spatial indexes use
R-trees, which are
specialized data structures for indexing multi-dimensional data.
Index records are stored in the leaf pages of their B-tree or
R-tree data structure. The default size of an index page is
16KB.
When new records are inserted into an InnoDB
clustered index,
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.
InnoDB
performs a bulk load when creating or
rebuilding B-tree indexes. This method of index creation is
known as a sorted index build. The
innodb_fill_factor
configuration option defines the percentage of space on each
B-tree page that is filled during a sorted index build, with the
remaining space reserved for future index growth. Sorted index
builds are not supported for spatial indexes. For more
information, see Section 14.8.2.3, “Sorted Index Builds”. An
innodb_fill_factor
setting of
100 leaves 1/16 of the space in clustered index pages free for
future index growth.
If the fill factor of an InnoDB
index page
drops below the MERGE_THRESHOLD
, which is 50%
by default if not specified, InnoDB
tries to
contract the index tree to free the page. The
MERGE_THRESHOLD
setting applies to both
B-tree and R-tree indexes. For more information, see
Section 14.6.13, “Configuring the Merge Threshold for Index Pages”.
You can define the page
size for all InnoDB
tablespaces in a
MySQL instance by setting the
innodb_page_size
configuration
option prior to initializing the MySQL instance. Once the page
size for an instance is defined, you cannot change it without
reinitializing the instance. Supported sizes are 64KB, 32KB,
16KB (default), 8KB, and 4KB, corresponding to the option values
64k
, 32k
,
16k
, 8k
, and
4k
.
Support for 32KB and 64KB pages sizes was added in MySQL
5.7. For more information, refer to the
innodb_page_size
documentation.
A MySQL instance using a particular InnoDB
page size cannot use data files or log files from an instance
that uses a different page size.
InnoDB
performs a bulk load instead of
inserting one index record at a time when creating or rebuilding
indexes. This method of index creation is also known as a sorted
index build. Sorted index builds are not supported for spatial
indexes.
There are three phases to an index build. In the first phase, the clustered index is scanned, and index entries are generated and added to the sort buffer. When the sort buffer becomes full, entries are sorted and written out to a temporary intermediate file. This process is also known as a “run”. In the second phase, with one or more runs written to the temporary intermediate file, a merge sort is performed on all entries in the file. In the third and final phase, the sorted entries are inserted into the B-tree.
Prior to the introduction of sorted index builds, index entries were inserted into the B-tree one record at a time using insert APIs. This method involved opening a B-tree cursor to find the insert position and then inserting entries into a B-tree page using an optimistic insert. If an insert failed due to a page being full, a pessimistic insert would be performed, which involves opening a B-tree cursor and splitting and merging B-tree nodes as necessary to find space for the entry. The drawbacks of this “top-down” method of building an index are the cost of searching for an insert position and the constant splitting and merging of B-tree nodes.
Sorted index builds use a “bottom-up” approach to building an index. With this approach, a reference to the right-most leaf page is held at all levels of the B-tree. The right-most leaf page at the necessary B-tree depth is allocated and entries are inserted according to their sorted order. Once a leaf page is full, a node pointer is appended to the parent page and a sibling leaf page is allocated for the next insert. This process continues until all entries are inserted, which may result in inserts up to the root level. When a sibling page is allocated, the reference to the previously pinned leaf page is released, and the newly allocated leaf page becomes the right-most leaf page and new default insert location.
To set aside space for future index growth, you can use the
innodb_fill_factor
configuration option to reserve a percentage of B-tree page
space. For example, setting
innodb_fill_factor
to 80
reserves 20 percent of the space in B-tree pages during a sorted
index build. This setting applies to both B-tree leaf and
non-leaf pages. It does not apply to external pages used for
TEXT
or
BLOB
entries. The amount of space
that is reserved may not be exactly as configured, as the
innodb_fill_factor
value is
interpreted as a hint rather than a hard limit.
Sorted index builds are supported for fulltext indexes. Previously, SQL was used to insert entries into a fulltext index.
For compressed tables, the previous index creation method appended entries to both compressed and uncompressed pages. When the modification log (representing free space on the compressed page) became full, the compressed page would be recompressed. If compression failed due to a lack of space, the page would be split. With sorted index builds, entries are only appended to uncompressed pages. When an uncompressed page becomes full, it is compressed. Adaptive padding is used to ensure that compression succeeds in most cases, but if compression fails, the page is split and compression is attempted again. This process continues until compression is successful. For more information about compression of B-Tree pages, see Section 14.9.1.5, “How Compression Works for InnoDB Tables”.
Redo logging is disabled during a sorted index build. Instead, there is a checkpoint to ensure that the index build can withstand a crash or failure. The checkpoint forces a write of all dirty pages to disk. During a sorted index build, the page cleaner thread is signaled periodically to flush dirty pages to ensure that the checkpoint operation can be processed quickly. Normally, the page cleaner thread flushes dirty pages when the number of clean pages falls below a set threshold. For sorted index builds, dirty pages are flushed promptly to reduce checkpoint overhead and to parallelize I/O and CPU activity.
Sorted index builds may result in optimizer statistics that differ from those generated by the previous method of index creation. The difference in statistics, which is not expected to affect workload performance, is due to the different algorithm used to populate the index.
FULLTEXT
indexes are created on text-based
columns (CHAR
,
VARCHAR
, or
TEXT
columns) to help speed up
queries and DML operations on data contained within those
columns, omitting any words that are defined as stopwords.
A FULLTEXT
index is defined as part of a
CREATE TABLE
statement or added
to an existing table using ALTER
TABLE
or CREATE INDEX
.
Full-text search is performed using MATCH()
... AGAINST
syntax. For usage information, see
Section 12.9, “Full-Text Search Functions”.
InnoDB
FULLTEXT
indexes
are described under the following topics in this section:
InnoDB
FULLTEXT
indexes
have an inverted index design. Inverted indexes store a list
of words, and for each word, a list of documents that the word
appears in. To support proximity search, position information
for each word is also stored, as a byte offset.
When creating an InnoDB
FULLTEXT
index, a set of index tables is
created, as shown in the following example:
mysql>CREATE TABLE opening_lines (
id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
opening_line TEXT(500),
author VARCHAR(200),
title VARCHAR(200),
FULLTEXT idx (opening_line)
) ENGINE=InnoDB;
mysql>SELECT table_id, name, space from INFORMATION_SCHEMA.INNODB_SYS_TABLES
WHERE name LIKE 'test/%';
+----------+----------------------------------------------------+-------+ | table_id | name | space | +----------+----------------------------------------------------+-------+ | 333 | test/FTS_0000000000000147_00000000000001c9_INDEX_1 | 289 | | 334 | test/FTS_0000000000000147_00000000000001c9_INDEX_2 | 290 | | 335 | test/FTS_0000000000000147_00000000000001c9_INDEX_3 | 291 | | 336 | test/FTS_0000000000000147_00000000000001c9_INDEX_4 | 292 | | 337 | test/FTS_0000000000000147_00000000000001c9_INDEX_5 | 293 | | 338 | test/FTS_0000000000000147_00000000000001c9_INDEX_6 | 294 | | 330 | test/FTS_0000000000000147_BEING_DELETED | 286 | | 331 | test/FTS_0000000000000147_BEING_DELETED_CACHE | 287 | | 332 | test/FTS_0000000000000147_CONFIG | 288 | | 328 | test/FTS_0000000000000147_DELETED | 284 | | 329 | test/FTS_0000000000000147_DELETED_CACHE | 285 | | 327 | test/opening_lines | 283 | +----------+----------------------------------------------------+-------+
The first six tables represent the inverted index and are
referred to as auxiliary index tables. When incoming documents
are tokenized, the individual words (also referred to as
“tokens”) are inserted into the index tables
along with position information and the associated Document ID
(DOC_ID
). The words are fully sorted and
partitioned among the six index tables based on the character
set sort weight of the word's first character.
The inverted index is partitioned into six auxiliary index
tables to support parallel index creation. By default, two
threads tokenize, sort, and insert words and associated data
into the index tables. The number of threads is configurable
using the
innodb_ft_sort_pll_degree
option. Consider increasing the number of threads when
creating FULLTEXT
indexes on large tables.
Auxiliary index table names are prefixed with
FTS_
and postfixed with
INDEX_*
. Each index table is associated
with the indexed table by a hex value in the index table name
that matches the table_id
of the indexed
table. For example, the table_id
of the
test/opening_lines
table is
327
, for which the hex value is 0x147. As
shown in the preceding example, the “147” hex
value appears in the names of index tables that are associated
with the test/opening_lines
table.
A hex value representing the index_id
of
the FULLTEXT
index also appears in
auxiliary index table names. For example, in the auxiliary
table name
test/FTS_0000000000000147_00000000000001c9_INDEX_1
,
the hex value 1c9
has a decimal value of
457. The index defined on the opening_lines
table (idx
) can be identified by querying
the
INFORMATION_SCHEMA.INNODB_SYS_INDEXES
table for this value (457).
mysql>SELECT index_id, name, table_id, space from INFORMATION_SCHEMA.INNODB_SYS_INDEXES
WHERE index_id=457;
+----------+------+----------+-------+ | index_id | name | table_id | space | +----------+------+----------+-------+ | 457 | idx | 327 | 283 | +----------+------+----------+-------+
Index tables are stored in their own tablespace if the primary table is created in a file-per-table tablespace.
The other index tables shown in the preceding example are
referred to as common index tables and are used for deletion
handling and storing the internal state of
FULLTEXT
indexes. Unlike the inverted index
tables, which are created for each full-text index, this set
of tables is common to all full-text indexes created on a
particular table.
Common auxiliary tables are retained even if full-text indexes
are dropped. When a full-text index is dropped, the
FTS_DOC_ID
column that was created for the
index is retained, as removing the
FTS_DOC_ID
column would require rebuilding
the table. Common axillary tables are required to manage the
FTS_DOC_ID
column.
FTS_*_DELETED
and
FTS_*_DELETED_CACHE
Contain the document IDs (DOC_ID) for documents that are
deleted but whose data is not yet removed from the
full-text index. The
FTS_*_DELETED_CACHE
is the in-memory
version of the FTS_*_DELETED
table.
FTS_*_BEING_DELETED
and
FTS_*_BEING_DELETED_CACHE
Contain the document IDs (DOC_ID) for documents that are
deleted and whose data is currently in the process of
being removed from the full-text index. The
FTS_*_BEING_DELETED_CACHE
table is the
in-memory version of the
FTS_*_BEING_DELETED
table.
FTS_*_CONFIG
Stores information about the internal state of the
FULLTEXT
index. Most importantly, it
stores the FTS_SYNCED_DOC_ID
, which
identifies documents that have been parsed and flushed to
disk. In case of crash recovery,
FTS_SYNCED_DOC_ID
values are used to
identify documents that have not been flushed to disk so
that the documents can be re-parsed and added back to the
FULLTEXT
index cache. To view the data
in this table, query the
INFORMATION_SCHEMA.INNODB_FT_CONFIG
table.
When a document is inserted, it is tokenized, and the
individual words and associated data are inserted into the
FULLTEXT
index. This process, even for
small documents, could result in numerous small insertions
into the auxiliary index tables, making concurrent access to
these tables a point of contention. To avoid this problem,
InnoDB
uses a FULLTEXT
index cache to temporarily cache index table insertions for
recently inserted rows. This in-memory cache structure holds
insertions until the cache is full and then batch flushes them
to disk (to the auxiliary index tables). You can query the
INFORMATION_SCHEMA.INNODB_FT_INDEX_CACHE
table to view tokenized data for recently inserted rows.
The caching and batch flushing behavior avoids frequent updates to auxiliary index tables, which could result in concurrent access issues during busy insert and update times. The batching technique also avoids multiple insertions for the same word, and minimizes duplicate entries. Instead of flushing each word individually, insertions for the same word are merged and flushed to disk as a single entry, improving insertion efficiency while keeping auxiliary index tables as small as possible.
The innodb_ft_cache_size
variable is used to configure the full-text index cache size
(on a per-table basis), which affects how often the full-text
index cache is flushed. You can also define a global full-text
index cache size limit for all tables in a given instance
using the
innodb_ft_total_cache_size
option.
The full-text index cache stores the same information as auxiliary index tables. However, the full-text index cache only caches tokenized data for recently inserted rows. The data that is already flushed to disk (to the full-text auxiliary tables) is not brought back into the full-text index cache when queried. The data in auxiliary index tables is queried directly, and results from the auxiliary index tables are merged with results from the full-text index cache before being returned.
InnoDB
uses a unique document identifier
referred to as a Document ID (DOC_ID
) to
map words in the full-text index to document records where the
word appears. The mapping requires an
FTS_DOC_ID
column on the indexed table. If
an FTS_DOC_ID
column is not defined,
InnoDB
automatically adds a hidden
FTS_DOC_ID
column when the full-text index
is created. The following example demonstrates this behavior.
The following table definition does not include an
FTS_DOC_ID
column:
mysql>CREATE TABLE opening_lines (
id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
opening_line TEXT(500),
author VARCHAR(200),
title VARCHAR(200)
) ENGINE=InnoDB;
When you create a full-text index on the table using
CREATE FULLTEXT INDEX
syntax, a warning is
returned which reports that InnoDB
is
rebuilding the table to add the FTS_DOC_ID
column.
mysql>CREATE FULLTEXT INDEX idx ON opening_lines(opening_line);
Query OK, 0 rows affected, 1 warning (0.19 sec) Records: 0 Duplicates: 0 Warnings: 1 mysql>SHOW WARNINGS;
+---------+------+--------------------------------------------------+ | Level | Code | Message | +---------+------+--------------------------------------------------+ | Warning | 124 | InnoDB rebuilding table to add column FTS_DOC_ID | +---------+------+--------------------------------------------------+
The same warning is returned when using
ALTER TABLE
to add a full-text
index to a table that does not have an
FTS_DOC_ID
column. If you create a
full-text index at CREATE TABLE
time and do not specify an FTS_DOC_ID
column, InnoDB
adds a hidden
FTS_DOC_ID
column, without warning.
Defining an FTS_DOC_ID
column at
CREATE TABLE
time is less
expensive than creating a full-text index on a table that is
already loaded with data. If an FTS_DOC_ID
column is defined on a table prior to loading data, the table
and its indexes do not have to be rebuilt to add the new
column. If you are not concerned with CREATE FULLTEXT
INDEX
performance, leave out the
FTS_DOC_ID
column to have
InnoDB
create it for you.
InnoDB
creates a hidden
FTS_DOC_ID
column along with a unique index
(FTS_DOC_ID_INDEX
) on the
FTS_DOC_ID
column. If you want to create
your own FTS_DOC_ID
column, the column must
be defined as BIGINT UNSIGNED NOT NULL
and
named FTS_DOC_ID
(all upper case), as in
the following example:
The FTS_DOC_ID
column does not need to be
defined as an AUTO_INCREMENT
column, but
AUTO_INCREMENT
could make loading data
easier.
mysql>CREATE TABLE opening_lines (
FTS_DOC_ID BIGINT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
opening_line TEXT(500),
author VARCHAR(200),
title VARCHAR(200)
) ENGINE=InnoDB;
If you choose to define the FTS_DOC_ID
column yourself, you are responsible for managing the column
to avoid empty or duplicate values.
FTS_DOC_ID
values cannot be reused, which
means FTS_DOC_ID
values must be ever
increasing.
Optionally, you can create the required unique
FTS_DOC_ID_INDEX
(all upper case) on the
FTS_DOC_ID
column.
mysql> CREATE UNIQUE INDEX FTS_DOC_ID_INDEX on opening_lines(FTS_DOC_ID);
If you do not create the FTS_DOC_ID_INDEX
,
InnoDB
creates it automatically.
Before MySQL 5.7.13, the permitted gap between the largest
used FTS_DOC_ID
value and new
FTS_DOC_ID
value is 10000. In MySQL 5.7.13
and later, the permitted gap is 65535.
To avoid rebuilding the table, the
FTS_DOC_ID
column is retained when dropping
a full-text index.
Deleting a record that has a full-text index column could
result in numerous small deletions in the auxiliary index
tables, making concurrent access to these tables a point of
contention. To avoid this problem, the Document ID
(DOC_ID
) of a deleted document is logged in
a special FTS_*_DELETED
table whenever a
record is deleted from an indexed table, and the indexed
record remains in the full-text index. Before returning query
results, information in the FTS_*_DELETED
table is used to filter out deleted Document IDs. The benefit
of this design is that deletions are fast and inexpensive. The
drawback is that the size of the index is not immediately
reduced after deleting records. To remove full-text index
entries for deleted records, run OPTIMIZE
TABLE
on the indexed table with
innodb_optimize_fulltext_only=ON
to rebuild the full-text index. For more information, see
Optimizing InnoDB Full-Text Indexes.
InnoDB
FULLTEXT
indexes
have special transaction handling characteristics due its
caching and batch processing behavior. Specifically, updates
and insertions on a FULLTEXT
index are
processed at transaction commit time, which means that a
FULLTEXT
search can only see committed
data. The following example demonstrates this behavior. The
FULLTEXT
search only returns a result after
the inserted lines are committed.
mysql>CREATE TABLE opening_lines (
id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,
opening_line TEXT(500),
author VARCHAR(200),
title VARCHAR(200),
FULLTEXT idx (opening_line)
) ENGINE=InnoDB;
mysql>BEGIN;
mysql>INSERT INTO opening_lines(opening_line,author,title) VALUES
('Call me Ishmael.','Herman Melville','Moby-Dick'),
('A screaming comes across the sky.','Thomas Pynchon','Gravity\'s Rainbow'),
('I am an invisible man.','Ralph Ellison','Invisible Man'),
('Where now? Who now? When now?','Samuel Beckett','The Unnamable'),
('It was love at first sight.','Joseph Heller','Catch-22'),
('All this happened, more or less.','Kurt Vonnegut','Slaughterhouse-Five'),
('Mrs. Dalloway said she would buy the flowers herself.','Virginia Woolf','Mrs. Dalloway'),
('It was a pleasure to burn.','Ray Bradbury','Fahrenheit 451');
mysql>SELECT COUNT(*) FROM opening_lines WHERE MATCH(opening_line) AGAINST('Ishmael');
+----------+ | COUNT(*) | +----------+ | 0 | +----------+ mysql>COMMIT;
mysql>SELECT COUNT(*) FROM opening_lines WHERE MATCH(opening_line) AGAINST('Ishmael');
+----------+ | COUNT(*) | +----------+ | 1 | +----------+
You can monitor and examine the special text-processing
aspects of InnoDB
FULLTEXT
indexes by querying the following
INFORMATION_SCHEMA
tables:
You can also view basic information for
FULLTEXT
indexes and tables by querying
INNODB_SYS_INDEXES
and
INNODB_SYS_TABLES
.
For more information, see Section 14.15.4, “InnoDB INFORMATION_SCHEMA FULLTEXT Index Tables”.
This section provides information about the
InnoDB
table compression and
InnoDB
page compression features. The page
compression feature is referred to as
transparent page
compression.
Using the compression features of InnoDB
, you can
create tables where the data is stored in compressed form.
Compression can help to improve both raw performance and
scalability. The compression means less data is transferred between
disk and memory, and takes up less space on disk and in memory. The
benefits are amplified for tables with
secondary indexes,
because index data is compressed also. Compression can be especially
important for SSD storage devices,
because they tend to have lower capacity than
HDD devices.
This section describes InnoDB
table
compression, which is supported with InnoDB
tables that reside in
file_per_table
tablespaces or general
tablespaces. Table compression is enabled using the
ROW_FORMAT=COMPRESSED
attribute with
CREATE TABLE
or
ALTER TABLE
.
Because processors and cache memories have increased in speed more than disk storage devices, many workloads are disk-bound. Data compression enables smaller database size, reduced I/O, and improved throughput, at the small cost of increased CPU utilization. Compression is especially valuable for read-intensive applications, on systems with enough RAM to keep frequently used data in memory.
An InnoDB
table created with
ROW_FORMAT=COMPRESSED
can use a smaller
page size on disk than the
configured innodb_page_size
value. Smaller pages require less I/O to read from and write to
disk, which is especially valuable for
SSD devices.
The compressed page size is specified through the
CREATE TABLE
or
ALTER TABLE
KEY_BLOCK_SIZE
parameter. The different page
size requires that the table be placed in a
file-per-table
tablespace or general
tablespace rather than in the
system tablespace,
as the system tablespace cannot store compressed tables. For
more information, see
Section 14.7.4, “InnoDB File-Per-Table Tablespaces”, and
Section 14.7.9, “InnoDB General Tablespaces”.
The level of compression is the same regardless of the
KEY_BLOCK_SIZE
value. As you specify smaller
values for KEY_BLOCK_SIZE
, you get the I/O
benefits of increasingly smaller pages. But if you specify a
value that is too small, there is additional overhead to
reorganize the pages when data values cannot be compressed
enough to fit multiple rows in each page. There is a hard limit
on how small KEY_BLOCK_SIZE
can be for a
table, based on the lengths of the key columns for each of its
indexes. Specify a value that is too small, and the
CREATE TABLE
or
ALTER TABLE
statement fails.
In the buffer pool, the compressed data is held in small pages,
with a page size based on the KEY_BLOCK_SIZE
value. For extracting or updating the column values, MySQL also
creates an uncompressed page in the buffer pool with the
uncompressed data. Within the buffer pool, any updates to the
uncompressed page are also re-written back to the equivalent
compressed page. You might need to size your buffer pool to
accommodate the additional data of both compressed and
uncompressed pages, although the uncompressed pages are
evicted from the buffer
pool when space is needed, and then uncompressed again on the
next access.
Compressed tables can be created in file-per-table tablespaces or in general tablespaces. Table compression is not available for the InnoDB system tablespace. The system tablespace (space 0, the .ibdata files) can contain user-created tables, but it also contains internal system data, which is never compressed. Thus, compression applies only to tables (and indexes) stored in file-per-table or general tablespaces.
To create a compressed table in a file-per-table tablespace,
innodb_file_per_table
must be
enabled (the default in MySQL 5.6.6) and
innodb_file_format
must be set
to Barracuda
. You can set these parameters in
the MySQL configuration file (my.cnf
or
my.ini
) or dynamically, using a
SET
statement.
After the innodb_file_per_table
and innodb_file_format
options
are configured, specify the
ROW_FORMAT=COMPRESSED
clause or
KEY_BLOCK_SIZE
clause, or both, in a
CREATE TABLE
or
ALTER TABLE
statement to create a
compressed table in a file-per-table tablespace.
For example, you might use the following statements:
SET GLOBAL innodb_file_per_table=1; SET GLOBAL innodb_file_format=Barracuda; CREATE TABLE t1 (c1 INT PRIMARY KEY) ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;
To create a compressed table in a general tablespace,
FILE_BLOCK_SIZE
must be defined for the
general tablespace, which is specified when the tablespace is
created. The FILE_BLOCK_SIZE
value must be a
valid compressed page size in relation to the
innodb_page_size
value, and the
page size of the compressed table, defined by the
CREATE TABLE
or
ALTER TABLE
KEY_BLOCK_SIZE
clause, must be equal to
FILE_BLOCK_SIZE/1024
. For example, if
innodb_page_size=16384
and
FILE_BLOCK_SIZE=8192
, the
KEY_BLOCK_SIZE
of the table must be 8. For
more information, see Section 14.7.9, “InnoDB General Tablespaces”.
The following example demonstrates creating a general tablespace
and adding a compressed table. The example assumes a default
innodb_page_size
of 16K. The
FILE_BLOCK_SIZE
of 8192 requires that the
compressed table have a KEY_BLOCK_SIZE
of 8.
mysql>CREATE TABLESPACE `ts2` ADD DATAFILE 'ts2.ibd' FILE_BLOCK_SIZE = 8192 Engine=InnoDB;
mysql>CREATE TABLE t4 (c1 INT PRIMARY KEY) TABLESPACE ts2 ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;
If you specify ROW_FORMAT=COMPRESSED
, you
can omit KEY_BLOCK_SIZE
; the
KEY_BLOCK_SIZE
setting defaults to half
the innodb_page_size
value.
If you specify a valid KEY_BLOCK_SIZE
value, you can omit
ROW_FORMAT=COMPRESSED
; compression is
enabled automatically.
To determine the best value for
KEY_BLOCK_SIZE,
typically you create
several copies of the same table with different values for
this clause, then measure the size of the resulting
.ibd
files and see how well each
performs with a realistic
workload. For general
tablespaces, keep in mind that dropping a table does not
reduce the size of the general tablespace
.ibd
file, nor does it return disk
space to the operating system. For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
The KEY_BLOCK_SIZE
value is treated as a
hint; a different size could be used by
InnoDB
if necessary. For file-per-table
tablespaces, the KEY_BLOCK_SIZE
can only
be less than or equal to the
innodb_page_size
value. If
you specify a value greater than the
innodb_page_size
value, the
specified value is ignored, a warning is issued, and
KEY_BLOCK_SIZE
is set to half of the
innodb_page_size
value. If
innodb_strict_mode=ON
, specifying an
invalid KEY_BLOCK_SIZE
value returns an
error. For general tablespaces, valid
KEY_BLOCK_SIZE
values depend on the
FILE_BLOCK_SIZE
setting of the
tablespace. For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
32k and 64k page sizes do not support compression. For more
information, refer to the
innodb_page_size
documentation.
The default uncompressed size of InnoDB
data pages is 16KB.
Depending on the combination of option values, MySQL uses a
page size of 1KB, 2KB, 4KB, 8KB, or 16KB for the tablespace
data file (.ibd
file). The actual
compression algorithm is not affected by the
KEY_BLOCK_SIZE
value; the value
determines how large each compressed chunk is, which in turn
affects how many rows can be packed into each compressed
page.
When creating a compressed table in a file-per-table
tablespace, setting KEY_BLOCK_SIZE
equal
to the InnoDB
page size does not
typically result in much compression. For example, setting
KEY_BLOCK_SIZE=16
typically would not
result in much compression, since the normal
InnoDB
page size is 16KB. This setting
may still be useful for tables with many long
BLOB
,
VARCHAR
or
TEXT
columns, because such
values often do compress well, and might therefore require
fewer overflow
pages as described in
Section 14.9.1.5, “How Compression Works for InnoDB Tables”. For general
tablespaces, a KEY_BLOCK_SIZE
value equal
to the InnoDB
page size is not permitted.
For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
All indexes of a table (including the
clustered index)
are compressed using the same page size, as specified in the
CREATE TABLE
or ALTER
TABLE
statement. Table attributes such as
ROW_FORMAT
and
KEY_BLOCK_SIZE
are not part of the
CREATE INDEX
syntax for
InnoDB
tables, and are ignored if they
are specified (although, if specified, they will appear in
the output of the SHOW CREATE
TABLE
statement).
For performance-related configuration options, see Section 14.9.1.3, “Tuning Compression for InnoDB Tables”.
MySQL versions prior to 5.1 cannot process compressed tables.
Compressed tables cannot be stored in the
InnoDB
system tablespace.
General tablespaces can contain multiple tables, but compressed and uncompressed tables cannot coexist within the same general tablespace.
Compression applies to an entire table and all its
associated indexes, not to individual rows, despite the
clause name ROW_FORMAT
.
Most often, the internal optimizations described in InnoDB Data Storage and Compression ensure that the system runs well with compressed data. However, because the efficiency of compression depends on the nature of your data, you can make decisions that affect the performance of compressed tables:
Which tables to compress.
What compressed page size to use.
Whether to adjust the size of the buffer pool based on run-time performance characteristics, such as the amount of time the system spends compressing and uncompressing data. Whether the workload is more like a data warehouse (primarily queries) or an OLTP system (mix of queries and DML).
If the system performs DML operations on compressed tables, and the way the data is distributed leads to expensive compression failures at runtime, you might adjust additional advanced configuration options.
Use the guidelines in this section to help make those architectural and configuration choices. When you are ready to conduct long-term testing and put compressed tables into production, see Section 14.9.1.4, “Monitoring InnoDB Table Compression at Runtime” for ways to verify the effectiveness of those choices under real-world conditions.
In general, compression works best on tables that include a reasonable number of character string columns and where the data is read far more often than it is written. Because there are no guaranteed ways to predict whether or not compression benefits a particular situation, always test with a specific workload and data set running on a representative configuration. Consider the following factors when deciding which tables to compress.
A key determinant of the efficiency of compression in reducing
the size of data files is the nature of the data itself. Recall
that compression works by identifying repeated strings of bytes
in a block of data. Completely randomized data is the worst
case. Typical data often has repeated values, and so compresses
effectively. Character strings often compress well, whether
defined in CHAR
, VARCHAR
,
TEXT
or BLOB
columns. On
the other hand, tables containing mostly binary data (integers
or floating point numbers) or data that is previously compressed
(for example JPEG or PNG
images) may not generally compress well, significantly or at
all.
You choose whether to turn on compression for each InnoDB table. A table and all of its indexes use the same (compressed) page size. It might be that the primary key (clustered) index, which contains the data for all columns of a table, compresses more effectively than the secondary indexes. For those cases where there are long rows, the use of compression might result in long column values being stored “off-page”, as discussed in Section 14.11.3, “DYNAMIC and COMPRESSED Row Formats”. Those overflow pages may compress well. Given these considerations, for many applications, some tables compress more effectively than others, and you might find that your workload performs best only with a subset of tables compressed.
To determine whether or not to compress a particular table,
conduct experiments. You can get a rough estimate of how
efficiently your data can be compressed by using a utility that
implements LZ77 compression (such as gzip
or
WinZip) on a copy of the .ibd
file for an uncompressed table. You can expect less
compression from a MySQL compressed table than from file-based
compression tools, because MySQL compresses data in chunks based
on the page size, 16KB by
default. In addition to user data, the page format includes some
internal system data that is not compressed. File-based
compression utilities can examine much larger chunks of data,
and so might find more repeated strings in a huge file than
MySQL can find in an individual page.
Another way to test compression on a specific table is to copy
some data from your uncompressed table to a similar, compressed
table (having all the same indexes) in a
file-per-table
tablespace and look at the size of the resulting
.ibd
file. For example:
USE test; SET GLOBAL innodb_file_per_table=1; SET GLOBAL innodb_file_format=Barracuda; SET GLOBAL autocommit=0; -- Create an uncompressed table with a million or two rows. CREATE TABLE big_table AS SELECT * FROM information_schema.columns; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; INSERT INTO big_table SELECT * FROM big_table; COMMIT; ALTER TABLE big_table ADD id int unsigned NOT NULL PRIMARY KEY auto_increment; SHOW CREATE TABLE big_table\G select count(id) from big_table; -- Check how much space is needed for the uncompressed table. \! ls -l data/test/big_table.ibd CREATE TABLE key_block_size_4 LIKE big_table; ALTER TABLE key_block_size_4 key_block_size=4 row_format=compressed; INSERT INTO key_block_size_4 SELECT * FROM big_table; commit; -- Check how much space is needed for a compressed table -- with particular compression settings. \! ls -l data/test/key_block_size_4.ibd
This experiment produced the following numbers, which of course could vary considerably depending on your table structure and data:
-rw-rw---- 1 cirrus staff 310378496 Jan 9 13:44 data/test/big_table.ibd -rw-rw---- 1 cirrus staff 83886080 Jan 9 15:10 data/test/key_block_size_4.ibd
To see whether compression is efficient for your particular workload:
For simple tests, use a MySQL instance with no other
compressed tables and run queries against the
INFORMATION_SCHEMA.INNODB_CMP
table.
For more elaborate tests involving workloads with multiple
compressed tables, run queries against the
INFORMATION_SCHEMA.INNODB_CMP_PER_INDEX
table. Because the statistics in the
INNODB_CMP_PER_INDEX
table are expensive
to collect, you must enable the configuration option
innodb_cmp_per_index_enabled
before querying that table, and you might restrict such
testing to a development server or a non-critical
slave server.
Run some typical SQL statements against the compressed table you are testing.
Examine the ratio of successful compression operations to
overall compression operations by querying the
INFORMATION_SCHEMA.INNODB_CMP
or
INFORMATION_SCHEMA.INNODB_CMP_PER_INDEX
table, and comparing COMPRESS_OPS
to
COMPRESS_OPS_OK
.
If a high percentage of compression operations complete successfully, the table might be a good candidate for compression.
If you get a high proportion of
compression
failures, you can adjust
innodb_compression_level
,
innodb_compression_failure_threshold_pct
,
and
innodb_compression_pad_pct_max
options as described in
Section 14.9.1.6, “Compression for OLTP Workloads”, and
try further tests.
Decide whether to compress data in your application or in the table; do not use both types of compression for the same data. When you compress the data in the application and store the results in a compressed table, extra space savings are extremely unlikely, and the double compression just wastes CPU cycles.
When enabled, MySQL table compression is automatic and applies
to all columns and index values. The columns can still be tested
with operators such as LIKE
, and sort
operations can still use indexes even when the index values are
compressed. Because indexes are often a significant fraction of
the total size of a database, compression could result in
significant savings in storage, I/O or processor time. The
compression and decompression operations happen on the database
server, which likely is a powerful system that is sized to
handle the expected load.
If you compress data such as text in your application, before it is inserted into the database, You might save overhead for data that does not compress well by compressing some columns and not others. This approach uses CPU cycles for compression and uncompression on the client machine rather than the database server, which might be appropriate for a distributed application with many clients, or where the client machine has spare CPU cycles.
Of course, it is possible to combine these approaches. For some applications, it may be appropriate to use some compressed tables and some uncompressed tables. It may be best to externally compress some data (and store it in uncompressed tables) and allow MySQL to compress (some of) the other tables in the application. As always, up-front design and real-life testing are valuable in reaching the right decision.
In addition to choosing which tables to compress (and the page
size), the workload is another key determinant of performance.
If the application is dominated by reads, rather than updates,
fewer pages need to be reorganized and recompressed after the
index page runs out of room for the per-page “modification
log” that MySQL maintains for compressed data. If the
updates predominantly change non-indexed columns or those
containing BLOB
s or large strings that happen
to be stored “off-page”, the overhead of
compression may be acceptable. If the only changes to a table
are INSERT
s that use a monotonically
increasing primary key, and there are few secondary indexes,
there is little need to reorganize and recompress index pages.
Since MySQL can “delete-mark” and delete rows on
compressed pages “in place” by modifying
uncompressed data, DELETE
operations on a
table are relatively efficient.
For some environments, the time it takes to load data can be as important as run-time retrieval. Especially in data warehouse environments, many tables may be read-only or read-mostly. In those cases, it might or might not be acceptable to pay the price of compression in terms of increased load time, unless the resulting savings in fewer disk reads or in storage cost is significant.
Fundamentally, compression works best when the CPU time is available for compressing and uncompressing data. Thus, if your workload is I/O bound, rather than CPU-bound, you might find that compression can improve overall performance. When you test your application performance with different compression configurations, test on a platform similar to the planned configuration of the production system.
Reading and writing database pages from and to disk is the slowest aspect of system performance. Compression attempts to reduce I/O by using CPU time to compress and uncompress data, and is most effective when I/O is a relatively scarce resource compared to processor cycles.
This is often especially the case when running in a multi-user environment with fast, multi-core CPUs. When a page of a compressed table is in memory, MySQL often uses additional memory, typically 16KB, in the buffer pool for an uncompressed copy of the page. The adaptive LRU algorithm attempts to balance the use of memory between compressed and uncompressed pages to take into account whether the workload is running in an I/O-bound or CPU-bound manner. Still, a configuration with more memory dedicated to the buffer pool tends to run better when using compressed tables than a configuration where memory is highly constrained.
The optimal setting of the compressed page size depends on the type and distribution of data that the table and its indexes contain. The compressed page size should always be bigger than the maximum record size, or operations may fail as noted in Compression of B-Tree Pages.
Setting the compressed page size too large wastes some space, but the pages do not have to be compressed as often. If the compressed page size is set too small, inserts or updates may require time-consuming recompression, and the B-tree nodes may have to be split more frequently, leading to bigger data files and less efficient indexing.
Typically, you set the compressed page size to 8K or 4K bytes.
Given that the maximum row size for an InnoDB table is around
8K, KEY_BLOCK_SIZE=8
is usually a safe
choice.
Overall application performance, CPU and I/O utilization and the size of disk files are good indicators of how effective compression is for your application. This section builds on the performance tuning advice from Section 14.9.1.3, “Tuning Compression for InnoDB Tables”, and shows how to find problems that might not turn up during initial testing.
To dig deeper into performance considerations for compressed tables, you can monitor compression performance at runtime using the Information Schema tables described in Example 14.1, “Using the Compression Information Schema Tables”. These tables reflect the internal use of memory and the rates of compression used overall.
The INNODB_CMP
table reports
information about compression activity for each compressed page
size (KEY_BLOCK_SIZE
) in use. The information
in these tables is system-wide: it summarizes the compression
statistics across all compressed tables in your database. You
can use this data to help decide whether or not to compress a
table by examining these tables when no other compressed tables
are being accessed. It involves relatively low overhead on the
server, so you might query it periodically on a production
server to check the overall efficiency of the compression
feature.
The INNODB_CMP_PER_INDEX
table
reports information about compression activity for individual
tables and indexes. This information is more targeted and more
useful for evaluating compression efficiency and diagnosing
performance issues one table or index at a time. (Because that
each InnoDB
table is represented as a
clustered index, MySQL does not make a big distinction between
tables and indexes in this context.) The
INNODB_CMP_PER_INDEX
table does
involve substantial overhead, so it is more suitable for
development servers, where you can compare the effects of
different workloads, data,
and compression settings in isolation. To guard against imposing
this monitoring overhead by accident, you must enable the
innodb_cmp_per_index_enabled
configuration option before you can query the
INNODB_CMP_PER_INDEX
table.
The key statistics to consider are the number of, and amount of
time spent performing, compression and uncompression operations.
Since MySQL splits B-tree
nodes when they are too full to contain the compressed data
following a modification, compare the number of
“successful” compression operations with the number
of such operations overall. Based on the information in the
INNODB_CMP
and
INNODB_CMP_PER_INDEX
tables and
overall application performance and hardware resource
utilization, you might make changes in your hardware
configuration, adjust the size of the buffer pool, choose a
different page size, or select a different set of tables to
compress.
If the amount of CPU time required for compressing and uncompressing is high, changing to faster or multi-core CPUs can help improve performance with the same data, application workload and set of compressed tables. Increasing the size of the buffer pool might also help performance, so that more uncompressed pages can stay in memory, reducing the need to uncompress pages that exist in memory only in compressed form.
A large number of compression operations overall (compared to
the number of INSERT
,
UPDATE
and DELETE
operations in your application and the size of the database)
could indicate that some of your compressed tables are being
updated too heavily for effective compression. If so, choose a
larger page size, or be more selective about which tables you
compress.
If the number of “successful” compression
operations (COMPRESS_OPS_OK
) is a high
percentage of the total number of compression operations
(COMPRESS_OPS
), then the system is likely
performing well. If the ratio is low, then MySQL is
reorganizing, recompressing, and splitting B-tree nodes more
often than is desirable. In this case, avoid compressing some
tables, or increase KEY_BLOCK_SIZE
for some
of the compressed tables. You might turn off compression for
tables that cause the number of “compression
failures” in your application to be more than 1% or 2% of
the total. (Such a failure ratio might be acceptable during a
temporary operation such as a data load).
This section describes some internal implementation details about compression for InnoDB tables. The information presented here may be helpful in tuning for performance, but is not necessary to know for basic use of compression.
Some operating systems implement compression at the file system level. Files are typically divided into fixed-size blocks that are compressed into variable-size blocks, which easily leads into fragmentation. Every time something inside a block is modified, the whole block is recompressed before it is written to disk. These properties make this compression technique unsuitable for use in an update-intensive database system.
MySQL implements compression with the help of the well-known zlib library, which implements the LZ77 compression algorithm. This compression algorithm is mature, robust, and efficient in both CPU utilization and in reduction of data size. The algorithm is “lossless”, so that the original uncompressed data can always be reconstructed from the compressed form. LZ77 compression works by finding sequences of data that are repeated within the data to be compressed. The patterns of values in your data determine how well it compresses, but typical user data often compresses by 50% or more.
InnoDB supports the zlib
library only up to
version 1.2.3.
Unlike compression performed by an application, or compression
features of some other database management systems, InnoDB
compression applies both to user data and to indexes. In many
cases, indexes can constitute 40-50% or more of the total
database size, so this difference is significant. When
compression is working well for a data set, the size of the
InnoDB data files (the
file-per-table
tablespace or general
tablespace .idb
files) is 25% to 50%
of the uncompressed size or possibly smaller. Depending on the
workload, this smaller
database can in turn lead to a reduction in I/O, and an increase
in throughput, at a modest cost in terms of increased CPU
utilization. You can adjust the balance between compression
level and CPU overhead by modifying the
innodb_compression_level
configuration option.
All user data in InnoDB tables is stored in pages comprising a B-tree index (the clustered index). In some other database systems, this type of index is called an “index-organized table”. Each row in the index node contains the values of the (user-specified or system-generated) primary key and all the other columns of the table.
Secondary indexes in InnoDB tables are also B-trees, containing pairs of values: the index key and a pointer to a row in the clustered index. The pointer is in fact the value of the primary key of the table, which is used to access the clustered index if columns other than the index key and primary key are required. Secondary index records must always fit on a single B-tree page.
The compression of B-tree nodes (of both clustered and secondary
indexes) is handled differently from compression of
overflow pages used to
store long VARCHAR
, BLOB
,
or TEXT
columns, as explained in the
following sections.
Because they are frequently updated, B-tree pages require special treatment. It is important to minimize the number of times B-tree nodes are split, as well as to minimize the need to uncompress and recompress their content.
One technique MySQL uses is to maintain some system information in the B-tree node in uncompressed form, thus facilitating certain in-place updates. For example, this allows rows to be delete-marked and deleted without any compression operation.
In addition, MySQL attempts to avoid unnecessary uncompression and recompression of index pages when they are changed. Within each B-tree page, the system keeps an uncompressed “modification log” to record changes made to the page. Updates and inserts of small records may be written to this modification log without requiring the entire page to be completely reconstructed.
When the space for the modification log runs out, InnoDB uncompresses the page, applies the changes and recompresses the page. If recompression fails (a situation known as a compression failure), the B-tree nodes are split and the process is repeated until the update or insert succeeds.
To avoid frequent compression failures in write-intensive
workloads, such as for OLTP
applications, MySQL sometimes reserves some empty space
(padding) in the page, so that the modification log fills up
sooner and the page is recompressed while there is still enough
room to avoid splitting it. The amount of padding space left in
each page varies as the system keeps track of the frequency of
page splits. On a busy server doing frequent writes to
compressed tables, you can adjust the
innodb_compression_failure_threshold_pct
,
and
innodb_compression_pad_pct_max
configuration options to fine-tune this mechanism.
Generally, MySQL requires that each B-tree page in an InnoDB
table can accommodate at least two records. For compressed
tables, this requirement has been relaxed. Leaf pages of B-tree
nodes (whether of the primary key or secondary indexes) only
need to accommodate one record, but that record must fit, in
uncompressed form, in the per-page modification log. If
innodb_strict_mode
is
ON
, MySQL checks the maximum row size during
CREATE TABLE
or
CREATE INDEX
. If the row does not
fit, the following error message is issued: ERROR
HY000: Too big row
.
If you create a table when
innodb_strict_mode
is OFF, and
a subsequent INSERT
or
UPDATE
statement attempts to create an index
entry that does not fit in the size of the compressed page, the
operation fails with ERROR 42000: Row size too
large
. (This error message does not name the index for
which the record is too large, or mention the length of the
index record or the maximum record size on that particular index
page.) To solve this problem, rebuild the table with
ALTER TABLE
and select a larger
compressed page size (KEY_BLOCK_SIZE
),
shorten any column prefix indexes, or disable compression
entirely with ROW_FORMAT=DYNAMIC
or
ROW_FORMAT=COMPACT
.
innodb_strict_mode
is not
applicable to general tablespaces, which also support compressed
tables. Tablespace management rules for general tablespaces are
strictly enforced independently of
innodb_strict_mode
. For more
information, see Section 13.1.19, “CREATE TABLESPACE Syntax”.
In an InnoDB table, BLOB
,
VARCHAR
, and
TEXT
columns that are not part of
the primary key may be stored on separately allocated
overflow pages. We
refer to these columns as
off-page columns.
Their values are stored on singly-linked lists of overflow
pages.
For tables created in ROW_FORMAT=DYNAMIC
or
ROW_FORMAT=COMPRESSED
, the values of
BLOB
,
TEXT
, or
VARCHAR
columns may be stored
fully off-page, depending on their length and the length of the
entire row. For columns that are stored off-page, the clustered
index record only contains 20-byte pointers to the overflow
pages, one per column. Whether any columns are stored off-page
depends on the page size and the total size of the row. When the
row is too long to fit entirely within the page of the clustered
index, MySQL chooses the longest columns for off-page storage
until the row fits on the clustered index page. As noted above,
if a row does not fit by itself on a compressed page, an error
occurs.
For tables created in ROW_FORMAT=DYNAMIC
or
ROW_FORMAT=COMPRESSED
,
TEXT
and
BLOB
columns that are less than
or equal to 40 bytes are always stored in-line.
Tables created in older versions of MySQL use the
Antelope file format, which
supports only ROW_FORMAT=REDUNDANT
and
ROW_FORMAT=COMPACT
. In these formats, MySQL
stores the first 768 bytes of
BLOB
,
VARCHAR
, and
TEXT
columns in the clustered
index record along with the primary key. The 768-byte prefix is
followed by a 20-byte pointer to the overflow pages that contain
the rest of the column value.
When a table is in COMPRESSED
format, all
data written to overflow pages is compressed “as
is”; that is, MySQL applies the zlib compression
algorithm to the entire data item. Other than the data,
compressed overflow pages contain an uncompressed header and
trailer comprising a page checksum and a link to the next
overflow page, among other things. Therefore, very significant
storage savings can be obtained for longer
BLOB
, TEXT
, or
VARCHAR
columns if the data is highly
compressible, as is often the case with text data. Image data,
such as JPEG
, is typically already compressed
and so does not benefit much from being stored in a compressed
table; the double compression can waste CPU cycles for little or
no space savings.
The overflow pages are of the same size as other pages. A row containing ten columns stored off-page occupies ten overflow pages, even if the total length of the columns is only 8K bytes. In an uncompressed table, ten uncompressed overflow pages occupy 160K bytes. In a compressed table with an 8K page size, they occupy only 80K bytes. Thus, it is often more efficient to use compressed table format for tables with long column values.
For file-per-table
tablespaces, using a 16K compressed page size can reduce storage
and I/O costs for BLOB
,
VARCHAR
, or
TEXT
columns, because such data
often compress well, and might therefore require fewer overflow
pages, even though the B-tree nodes themselves take as many
pages as in the uncompressed form. General tablespaces do not
support a 16K compressed page size
(KEY_BLOCK_SIZE
). For more information, see
Section 14.7.9, “InnoDB General Tablespaces”.
In a compressed InnoDB
table, every
compressed page (whether 1K, 2K, 4K or 8K) corresponds to an
uncompressed page of 16K bytes (or a smaller size if
innodb_page_size
is set). To
access the data in a page, MySQL reads the compressed page from
disk if it is not already in the
buffer pool, then
uncompresses the page to its original form. This section
describes how InnoDB
manages the buffer pool
with respect to pages of compressed tables.
To minimize I/O and to reduce the need to uncompress a page, at times the buffer pool contains both the compressed and uncompressed form of a database page. To make room for other required database pages, MySQL can evict from the buffer pool an uncompressed page, while leaving the compressed page in memory. Or, if a page has not been accessed in a while, the compressed form of the page might be written to disk, to free space for other data. Thus, at any given time, the buffer pool might contain both the compressed and uncompressed forms of the page, or only the compressed form of the page, or neither.
MySQL keeps track of which pages to keep in memory and which to evict using a least-recently-used (LRU) list, so that hot (frequently accessed) data tends to stay in memory. When compressed tables are accessed, MySQL uses an adaptive LRU algorithm to achieve an appropriate balance of compressed and uncompressed pages in memory. This adaptive algorithm is sensitive to whether the system is running in an I/O-bound or CPU-bound manner. The goal is to avoid spending too much processing time uncompressing pages when the CPU is busy, and to avoid doing excess I/O when the CPU has spare cycles that can be used for uncompressing compressed pages (that may already be in memory). When the system is I/O-bound, the algorithm prefers to evict the uncompressed copy of a page rather than both copies, to make more room for other disk pages to become memory resident. When the system is CPU-bound, MySQL prefers to evict both the compressed and uncompressed page, so that more memory can be used for “hot” pages and reducing the need to uncompress data in memory only in compressed form.
Before a compressed page is written to a
data file, MySQL writes a
copy of the page to the redo log (if it has been recompressed
since the last time it was written to the database). This is
done to ensure that redo logs are usable for
crash recovery, even
in the unlikely case that the zlib
library is
upgraded and that change introduces a compatibility problem with
the compressed data. Therefore, some increase in the size of
log files, or a need for
more frequent
checkpoints, can be
expected when using compression. The amount of increase in the
log file size or checkpoint frequency depends on the number of
times compressed pages are modified in a way that requires
reorganization and recompression.
Compressed tables require the
Barracuda file format. To
create a compressed table in a file-per-table tablespace,
innodb_file_per_table
must be
enabled and innodb_file_format
must be set to Barracuda.
There is no dependence on the
innodb_file_format
setting when
creating a compressed table in a general tablespace. For more
information, see Section 14.7.9, “InnoDB General Tablespaces”. The
MySQL Enterprise
Backup product supports the
Barracuda file format.
Traditionally, the InnoDB
compression feature was
recommended primarily for read-only or read-mostly
workloads, such as in a
data warehouse
configuration. The rise of SSD
storage devices, which are fast but relatively small and
expensive, makes compression attractive also for
OLTP
workloads: high-traffic, interactive
websites can reduce their storage requirements and their I/O
operations per second (IOPS) by
using compressed tables with applications that do frequent
INSERT
,
UPDATE
, and
DELETE
operations.
Configuration options introduced in MySQL 5.6 let you adjust the way compression works for a particular MySQL instance, with an emphasis on performance and scalability for write-intensive operations:
innodb_compression_level
lets you turn the degree of compression up or down. A higher
value lets you fit more data onto a storage device, at the
expense of more CPU overhead during compression. A lower
value lets you reduce CPU overhead when storage space is not
critical, or you expect the data is not especially
compressible.
innodb_compression_failure_threshold_pct
specifies a cutoff point for
compression
failures during updates to a compressed table. When
this threshold is passed, MySQL begins to leave additional
free space within each new compressed page, dynamically
adjusting the amount of free space up to the percentage of
page size specified by
innodb_compression_pad_pct_max
innodb_compression_pad_pct_max
lets you adjust the maximum amount of space reserved within
each page to record changes
to compressed rows, without needing to compress the entire
page again. The higher the value, the more changes can be
recorded without recompressing the page. MySQL uses a
variable amount of free space for the pages within each
compressed table, only when a designated percentage of
compression operations
“fail”
at runtime, requiring an expensive operation to split the
compressed page.
innodb_log_compressed_pages
lets you disable writing of images of
re-compressed
pages to the
redo log.
Re-compression may occur when changes are made to compressed
data. This option is enabled by default to prevent
corruption that could occur if a different version of the
zlib
compression algorithm is used during
recovery. If you are certain that the
zlib
version will not change, disable
innodb_log_compressed_pages
to reduce redo log generation for workloads that modify
compressed data.
Because working with compressed data sometimes involves keeping
both compressed and uncompressed versions of a page in memory at
the same time, when using compression with an OLTP-style
workload, be prepared to increase the value of the
innodb_buffer_pool_size
configuration option.
This section describes syntax warnings and errors that you may encounter when using the table compression feature with file-per-table tablespaces and general tablespaces.
When innodb_strict_mode
is
enabled (the default), specifying
ROW_FORMAT=COMPRESSED
or
KEY_BLOCK_SIZE
in CREATE
TABLE
or ALTER TABLE
statements produces the following error if
innodb_file_per_table
is
disabled or if
innodb_file_format
is set to
Antelope
rather than
Barracuda
.
ERROR 1031 (HY000): Table storage engine for 't1' doesn't have this option
The table is not created if the current configuration does not permit using compressed tables.
When innodb_strict_mode
is
disabled, specifying ROW_FORMAT=COMPRESSED
or
KEY_BLOCK_SIZE
in CREATE
TABLE
or ALTER TABLE
statements produces the following warnings if
innodb_file_per_table
is
disabled.
mysql> SHOW WARNINGS;
+---------+------+---------------------------------------------------------------+
| Level | Code | Message |
+---------+------+---------------------------------------------------------------+
| Warning | 1478 | InnoDB: KEY_BLOCK_SIZE requires innodb_file_per_table. |
| Warning | 1478 | InnoDB: ignoring KEY_BLOCK_SIZE=4. |
| Warning | 1478 | InnoDB: ROW_FORMAT=COMPRESSED requires innodb_file_per_table. |
| Warning | 1478 | InnoDB: assuming ROW_FORMAT=DYNAMIC. |
+---------+------+---------------------------------------------------------------+
Similar warnings are issued if
innodb_file_format
is set to
Antelope
rather than
Barracuda
.
These messages are only warnings, not errors, and the table is created without compression, as if the options were not specified.
The “non-strict” behavior lets you import a
mysqldump
file into a database that does not
support compressed tables, even if the source database contained
compressed tables. In that case, MySQL creates the table in
ROW_FORMAT=COMPACT
instead of preventing the
operation.
To import the dump file into a new database, and have the tables
re-created as they exist in the original database, ensure the
server has the proper settings for the configuration parameters
innodb_file_format
and
innodb_file_per_table
.
The attribute KEY_BLOCK_SIZE
is permitted
only when ROW_FORMAT
is specified as
COMPRESSED
or is omitted. Specifying a
KEY_BLOCK_SIZE
with any other
ROW_FORMAT
generates a warning that you can
view with SHOW WARNINGS
. However, the table
is non-compressed; the specified
KEY_BLOCK_SIZE
is ignored).
Level | Code | Message |
---|---|---|
Warning | 1478 | InnoDB: ignoring KEY_BLOCK_SIZE= |
If you are running with
innodb_strict_mode
enabled, the
combination of a KEY_BLOCK_SIZE
with any
ROW_FORMAT
other than
COMPRESSED
generates an error, not a warning,
and the table is not created.
Table 14.7, “ROW_FORMAT and KEY_BLOCK_SIZE Options”
provides an overview the ROW_FORMAT
and
KEY_BLOCK_SIZE
options that are used with
CREATE TABLE
or
ALTER TABLE
.
Table 14.7 ROW_FORMAT and KEY_BLOCK_SIZE Options
Option | Usage Notes | Description |
---|---|---|
ROW_FORMAT=REDUNDANT |
Storage format used prior to MySQL 5.0.3 | Less efficient than ROW_FORMAT=COMPACT ; for backward
compatibility |
ROW_FORMAT=COMPACT |
Default storage format since MySQL 5.0.3 | Stores a prefix of 768 bytes of long column values in the clustered index page, with the remaining bytes stored in an overflow page |
ROW_FORMAT=DYNAMIC |
File-per-table tablespaces require
innodb_file_format=Barracuda |
Store values within the clustered index page if they fit; if not, stores only a 20-byte pointer to an overflow page (no prefix) |
ROW_FORMAT=COMPRESSED |
File-per-table tablespaces require
innodb_file_format=Barracuda |
Compresses the table and indexes using zlib |
KEY_BLOCK_SIZE= |
File-per-table tablespaces require
innodb_file_format=Barracuda |
Specifies compressed page size of 1, 2, 4, 8 or 16 kilobytes; implies
ROW_FORMAT=COMPRESSED . For general
tablespaces, a KEY_BLOCK_SIZE value
equal to the InnoDB page size is not
permitted. |
Table 14.8, “CREATE/ALTER TABLE Warnings and Errors when InnoDB Strict Mode is OFF”
summarizes error conditions that occur with certain combinations
of configuration parameters and options on the
CREATE TABLE
or
ALTER TABLE
statements, and how
the options appear in the output of SHOW TABLE
STATUS
.
When innodb_strict_mode
is
OFF
, MySQL creates or alters the table, but
ignores certain settings as shown below. You can see the warning
messages in the MySQL error log. When
innodb_strict_mode
is
ON
, these specified combinations of options
generate errors, and the table is not created or altered. To see
the full description of the error condition, issue the
SHOW ERRORS
statement: example:
mysql>CREATE TABLE x (id INT PRIMARY KEY, c INT)
->ENGINE=INNODB KEY_BLOCK_SIZE=33333;
ERROR 1005 (HY000): Can't create table 'test.x' (errno: 1478) mysql>SHOW ERRORS;
+-------+------+-------------------------------------------+ | Level | Code | Message | +-------+------+-------------------------------------------+ | Error | 1478 | InnoDB: invalid KEY_BLOCK_SIZE=33333. | | Error | 1005 | Can't create table 'test.x' (errno: 1478) | +-------+------+-------------------------------------------+
Table 14.8 CREATE/ALTER TABLE Warnings and Errors when InnoDB Strict Mode is OFF
Syntax | Warning or Error Condition | Resulting ROW_FORMAT , as shown in SHOW TABLE
STATUS |
---|---|---|
ROW_FORMAT=REDUNDANT |
None | REDUNDANT |
ROW_FORMAT=COMPACT |
None | COMPACT |
ROW_FORMAT=COMPRESSED or
ROW_FORMAT=DYNAMIC or
KEY_BLOCK_SIZE is specified |
Ignored for file-per-table tablespaces unless both
innodb_file_format =Barracuda
and innodb_file_per_table
are enabled. General tablespaces support all row formats
(with some restrictions) regardless of
innodb_file_format and
innodb_file_per_table
settings. See Section 14.7.9, “InnoDB General Tablespaces”. |
the default row format for file-per-table tablespaces; the
specified row format for general tablespaces |
Invalid KEY_BLOCK_SIZE is specified (not 1, 2, 4, 8
or 16) |
KEY_BLOCK_SIZE is ignored |
the specified row format, or the default row format |
ROW_FORMAT=COMPRESSED and valid
KEY_BLOCK_SIZE are specified |
None; KEY_BLOCK_SIZE specified is used |
COMPRESSED |
KEY_BLOCK_SIZE is specified with
REDUNDANT , COMPACT
or DYNAMIC row format |
KEY_BLOCK_SIZE is ignored |
REDUNDANT , COMPACT or
DYNAMIC |
ROW_FORMAT is not one of
REDUNDANT , COMPACT ,
DYNAMIC or
COMPRESSED |
Ignored if recognized by the MySQL parser. Otherwise, an error is issued. | the default row format or N/A |
When innodb_strict_mode
is
ON
, MySQL rejects invalid
ROW_FORMAT
or
KEY_BLOCK_SIZE
parameters and issues errors.
When innodb_strict_mode
is
OFF
, MySQL issues warnings instead of errors
for ignored invalid parameters.
innodb_strict_mode
is ON
by default.
When innodb_strict_mode
is
ON
, MySQL rejects invalid
ROW_FORMAT
or
KEY_BLOCK_SIZE
parameters. For compatibility
with earlier versions of MySQL, strict mode is not enabled by
default; instead, MySQL issues warnings (not errors) for ignored
invalid parameters.
It is not possible to see the chosen
KEY_BLOCK_SIZE
using SHOW TABLE
STATUS
. The statement SHOW CREATE
TABLE
displays the KEY_BLOCK_SIZE
(even if it was ignored when creating the table). The real
compressed page size of the table cannot be displayed by MySQL.
If FILE_BLOCK_SIZE
was not defined for
the general tablespace when the tablespace was created, the
tablespace cannot contain compressed tables. If you attempt
to add a compressed table, an error is returned, as shown in
the following example:
mysql>CREATE TABLESPACE `ts1` ADD DATAFILE 'ts1.ibd' Engine=InnoDB;
mysql>CREATE TABLE t1 (c1 INT PRIMARY KEY) TABLESPACE ts1 ROW_FORMAT=COMPRESSED
KEY_BLOCK_SIZE=8;
ERROR 1478 (HY000): InnoDB: Tablespace `ts1` cannot contain a COMPRESSED table
Attempting to add a table with an invalid
KEY_BLOCK_SIZE
to a general tablespace
returns an error, as shown in the following example:
mysql>CREATE TABLESPACE `ts2` ADD DATAFILE 'ts2.ibd' FILE_BLOCK_SIZE = 8192 Engine=InnoDB;
mysql>CREATE TABLE t2 (c1 INT PRIMARY KEY) TABLESPACE ts2 ROW_FORMAT=COMPRESSED
KEY_BLOCK_SIZE=4;
ERROR 1478 (HY000): InnoDB: Tablespace `ts2` uses block size 8192 and cannot contain a table with physical page size 4096
For general tablespaces, the
KEY_BLOCK_SIZE
of the table must be equal
to the FILE_BLOCK_SIZE
of the tablespace
divided by 1024. For example, if the
FILE_BLOCK_SIZE
of the tablespace is
8192, the KEY_BLOCK_SIZE
of the table
must be 8.
Attempting to add a table with an uncompressed row format to a general tablespace configured to store compressed tables returns an error, as shown in the following example:
mysql>CREATE TABLESPACE `ts3` ADD DATAFILE 'ts3.ibd' FILE_BLOCK_SIZE = 8192 Engine=InnoDB;
mysql>CREATE TABLE t3 (c1 INT PRIMARY KEY) TABLESPACE ts3 ROW_FORMAT=COMPACT;
ERROR 1478 (HY000): InnoDB: Tablespace `ts3` uses block size 8192 and cannot contain a table with physical page size 16384
innodb_strict_mode
is not
applicable to general tablespaces. Tablespace management rules
for general tablespaces are strictly enforced independently of
innodb_strict_mode
. For more
information, see Section 13.1.19, “CREATE TABLESPACE Syntax”.
For more information about using compressed tables with general tablespaces, see Section 14.7.9, “InnoDB General Tablespaces”.
InnoDB
supports page-level compression for
tables that reside in
file-per-table
tablespaces. This feature is referred to as Transparent
Page Compression. Page compression is enabled by
specifying the COMPRESSION
attribute with
CREATE TABLE
or
ALTER TABLE
. Supported compression
algorithms include Zlib
and
LZ4
.
Page compression requires sparse file and hole punching support. Page compression is supported on Windows with NTFS, and on the following subset of MySQL-supported Linux platforms where the kernel level provides hole punching support:
RHEL 7 and derived distributions that use kernel version 3.10.0-123 or higher
OEL 5.10 (UEK2) kernel version 2.6.39 or higher
OEL 6.5 (UEK3) kernel version 3.8.13 or higher
OEL 7.0 kernel version 3.8.13 or higher
SLE11 kernel version 3.0-x
SLE12 kernel version 3.12-x
OES11 kernel version 3.0-x