WAL Configuration

PostgreSQL 8.4.2 Documentation
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# 28.4. WAL Configuration

There are several WAL-related configuration parameters that affect database performance. This section explains their use. Consult Chapter 18 for general information about setting server configuration parameters.

Checkpoints are points in the sequence of transactions at which it is guaranteed that the data files have been updated with all information written before the checkpoint. At checkpoint time, all dirty data pages are flushed to disk and a special checkpoint record is written to the log file. (The changes were previously flushed to the WAL files.) In the event of a crash, the crash recovery procedure looks at the latest checkpoint record to determine the point in the log (known as the redo record) from which it should start the REDO operation. Any changes made to data files before that point are guaranteed to be already on disk. Hence, after a checkpoint, log segments preceding the one containing the redo record are no longer needed and can be recycled or removed. (When WAL archiving is being done, the log segments must be archived before being recycled or removed.)

The checkpoint requirement of flushing all dirty data pages to disk can cause a significant I/O load. For this reason, checkpoint activity is throttled so I/O begins at checkpoint start and completes before the next checkpoint starts; this minimizes performance degradation during checkpoints.

The server's background writer process will automatically perform a checkpoint every so often. A checkpoint is created every checkpoint_segments log segments, or every checkpoint_timeout seconds, whichever comes first. The default settings are 3 segments and 300 seconds respectively. It is also possible to force a checkpoint by using the SQL command `CHECKPOINT`.

Reducing `checkpoint_segments` and/or `checkpoint_timeout` causes checkpoints to be done more often. This allows faster after-crash recovery (since less work will need to be redone). However, one must balance this against the increased cost of flushing dirty data pages more often. If full_page_writes is set (as is the default), there is another factor to consider. To ensure data page consistency, the first modification of a data page after each checkpoint results in logging the entire page content. In that case, a smaller checkpoint interval increases the volume of output to the WAL log, partially negating the goal of using a smaller interval, and in any case causing more disk I/O.

Checkpoints are fairly expensive, first because they require writing out all currently dirty buffers, and second because they result in extra subsequent WAL traffic as discussed above. It is therefore wise to set the checkpointing parameters high enough that checkpoints don't happen too often. As a simple sanity check on your checkpointing parameters, you can set the checkpoint_warning parameter. If checkpoints happen closer together than `checkpoint_warning` seconds, a message will be output to the server log recommending increasing `checkpoint_segments`. Occasional appearance of such a message is not cause for alarm, but if it appears often then the checkpoint control parameters should be increased. Bulk operations such as large `COPY` transfers might cause a number of such warnings to appear if you have not set `checkpoint_segments` high enough.

To avoid flooding the I/O system with a burst of page writes, writing dirty buffers during a checkpoint is spread over a period of time. That period is controlled by checkpoint_completion_target, which is given as a fraction of the checkpoint interval. The I/O rate is adjusted so that the checkpoint finishes when the given fraction of `checkpoint_segments` WAL segments have been consumed since checkpoint start, or the given fraction of `checkpoint_timeout` seconds have elapsed, whichever is sooner. With the default value of 0.5, PostgreSQL can be expected to complete each checkpoint in about half the time before the next checkpoint starts. On a system that's very close to maximum I/O throughput during normal operation, you might want to increase `checkpoint_completion_target` to reduce the I/O load from checkpoints. The disadvantage of this is that prolonging checkpoints affects recovery time, because more WAL segments will need to be kept around for possible use in recovery. Although `checkpoint_completion_target` can be set as high as 1.0, it is best to keep it less than that (perhaps 0.9 at most) since checkpoints include some other activities besides writing dirty buffers. A setting of 1.0 is quite likely to result in checkpoints not being completed on time, which would result in performance loss due to unexpected variation in the number of WAL segments needed.

There will always be at least one WAL segment file, and will normally not be more than (2 + `checkpoint_completion_target`) * `checkpoint_segments` + 1 files. Each segment file is normally 16 MB (though this size can be altered when building the server). You can use this to estimate space requirements for WAL. Ordinarily, when old log segment files are no longer needed, they are recycled (renamed to become the next segments in the numbered sequence). If, due to a short-term peak of log output rate, there are more than 3 * `checkpoint_segments` + 1 segment files, the unneeded segment files will be deleted instead of recycled until the system gets back under this limit.

There are two commonly used internal WAL functions: `LogInsert` and `LogFlush`. `LogInsert` is used to place a new record into the WAL buffers in shared memory. If there is no space for the new record, `LogInsert` will have to write (move to kernel cache) a few filled WAL buffers. This is undesirable because `LogInsert` is used on every database low level modification (for example, row insertion) at a time when an exclusive lock is held on affected data pages, so the operation needs to be as fast as possible. What is worse, writing WAL buffers might also force the creation of a new log segment, which takes even more time. Normally, WAL buffers should be written and flushed by a `LogFlush` request, which is made, for the most part, at transaction commit time to ensure that transaction records are flushed to permanent storage. On systems with high log output, `LogFlush` requests might not occur often enough to prevent `LogInsert` from having to do writes. On such systems one should increase the number of WAL buffers by modifying the configuration parameter wal_buffers. The default number of WAL buffers is 8. Increasing this value will correspondingly increase shared memory usage. When full_page_writes is set and the system is very busy, setting this value higher will help smooth response times during the period immediately following each checkpoint.

The commit_delay parameter defines for how many microseconds the server process will sleep after writing a commit record to the log with `LogInsert` but before performing a `LogFlush`. This delay allows other server processes to add their commit records to the log so as to have all of them flushed with a single log sync. No sleep will occur if fsync is not enabled, nor if fewer than commit_siblings other sessions are currently in active transactions; this avoids sleeping when it's unlikely that any other session will commit soon. Note that on most platforms, the resolution of a sleep request is ten milliseconds, so that any nonzero `commit_delay` setting between 1 and 10000 microseconds would have the same effect. Good values for these parameters are not yet clear; experimentation is encouraged.

The wal_sync_method parameter determines how PostgreSQL will ask the kernel to force WAL updates out to disk. All the options should be the same as far as reliability goes, but it's quite platform-specific which one will be the fastest. Note that this parameter is irrelevant if `fsync` has been turned off.

Enabling the wal_debug configuration parameter (provided that PostgreSQL has been compiled with support for it) will result in each `LogInsert` and `LogFlush` WAL call being logged to the server log. This option might be replaced by a more general mechanism in the future.

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