InnoDB transaction processing,
find the ideal balance between the performance overhead of
transactional features and the workload of your server. For
example, an application might encounter performance issues if it
commits thousands of times per second, and different performance
issues if it commits only every 2-3 hours.
The default MySQL setting
AUTOCOMMIT=1can impose performance limitations on a busy database server. Where practical, wrap several related DML operations into a single transaction, by issuing
SET AUTOCOMMIT=0or a
START TRANSACTIONstatement, followed by a
COMMITstatement after making all the changes.
InnoDBmust flush the log to disk at each transaction commit if that transaction made modifications to the database. When each change is followed by a commit (as with the default autocommit setting), the I/O throughput of the storage device puts a cap on the number of potential operations per second.
Alternatively, for transactions that consist only of a single
SELECTstatement, turning on
InnoDBto recognize read-only transactions and optimize them. See Section 9.5.3, “Optimizing InnoDB Read-Only Transactions” for requirements.
Avoid performing rollbacks after inserting, updating, or deleting huge numbers of rows. If a big transaction is slowing down server performance, rolling it back can make the problem worse, potentially taking several times as long to perform as the original DML operations. Killing the database process does not help, because the rollback starts again on server startup.
To minimize the chance of this issue occurring:
Increase the size of the buffer pool so that all the DML changes can be cached rather than immediately written to disk.
innodb_change_buffering=allso that update and delete operations are buffered in addition to inserts.
COMMITstatements periodically during the big DML operation, possibly breaking a single delete or update into multiple statements that operate on smaller numbers of rows.
To get rid of a runaway rollback once it occurs, increase the buffer pool so that the rollback becomes CPU-bound and runs fast, or kill the server and restart with
innodb_force_recovery=3, as explained in Section 15.16.1, “The InnoDB Recovery Process”.
This issue is expected to be less prominent in MySQL 5.5 and higher because the default setting
innodb_change_buffering=allallows update and delete operations to be cached in memory, making them faster to perform in the first place, and also faster to roll back if needed. Make sure to use this parameter setting on servers that process long-running transactions with many inserts, updates, or deletes.
If you can afford the loss of some of the latest committed transactions if a crash occurs, you can set the
innodb_flush_log_at_trx_commitparameter to 0.
InnoDBtries to flush the log once per second anyway, although the flush is not guaranteed. Also, set the value of
innodb_support_xato 0, which will reduce the number of disk flushes due to synchronizing on disk data and the binary log.
When rows are modified or deleted, the rows and associated undo logs are not physically removed immediately, or even immediately after the transaction commits. The old data is preserved until transactions that started earlier or concurrently are finished, so that those transactions can access the previous state of modified or deleted rows. Thus, a long-running transaction can prevent
InnoDBfrom purging data that was changed by a different transaction.
When rows are modified or deleted within a long-running transaction, other transactions using the
REPEATABLE READisolation levels have to do more work to reconstruct the older data if they read those same rows.
When a long-running transaction modifies a table, queries against that table from other transactions do not make use of the covering index technique. Queries that normally could retrieve all the result columns from a secondary index, instead look up the appropriate values from the table data.
If secondary index pages are found to have a
PAGE_MAX_TRX_IDthat is too new, or if records in the secondary index are delete-marked,
InnoDBmay need to look up records using a clustered index.