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
can impose performance limitations on a busy database
server. Where practical, wrap several related DML operations
into a single transaction, by issuing
AUTOCOMMIT=0 or a
TRANSACTION statement, followed by a
COMMIT statement after making all the
InnoDB must 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.
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.
so that update and delete operations are buffered in
addition to inserts.
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
explained in Section 14.18.1, “The InnoDB Recovery Process”.
This issue is expected to be less prominent in MySQL 5.5 and
up, or in MySQL 5.1 with the InnoDB Plugin, because the
allows 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
parameter to 0.
InnoDB tries to flush the
log once per second anyway, although the flush is not
guaranteed. Also, set the value of
innodb_support_xa to 0,
which will reduce the number of disk flushes due to
synchronizing on disk data and the binary log.
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
purging data that was changed by a different transaction.
When rows are modified or deleted within a long-running
transaction, other transactions using the
READ COMMITTED and
REPEATABLE READ isolation
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_ID that is too new, or if
records in the secondary index are delete-marked,
InnoDB may need to look up records using
a clustered index.