There are several WAL-related configuration parameters that affect database performance. This section explains their use. Consult Chapter 19 for general information about setting server configuration parameters.
Checkpoints are points in the sequence of transactions at which it is guaranteed that the heap and index data files have been updated with all information written before that checkpoint. At checkpoint time, all dirty data pages are flushed to disk and a special checkpoint record is written to the log file. (The change records 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 that I/O begins at checkpoint start and completes before the next checkpoint is due to start; this minimizes performance degradation during checkpoints.
   The server's checkpointer process automatically performs
   a checkpoint every so often.  A checkpoint is begun every checkpoint_timeout seconds, or if
   max_wal_size is about to be exceeded,
   whichever comes first.
   The default settings are 5 minutes and 1 GB, respectively.
   If no WAL has been written since the previous checkpoint, new checkpoints
   will be skipped even if checkpoint_timeout has passed.
   (If WAL archiving is being used and you want to put a lower limit on how
   often files are archived in order to bound potential data loss, you should
   adjust the archive_timeout parameter rather than the
   checkpoint parameters.)
   It is also possible to force a checkpoint by using the SQL
   command CHECKPOINT.
  
   Reducing checkpoint_timeout and/or
   max_wal_size causes checkpoints to occur
   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 so 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
   max_wal_size.  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 max_wal_size 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_timeout seconds have elapsed, or before
   max_wal_size is exceeded, 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.
  
   On Linux and POSIX platforms checkpoint_flush_after
   allows to force the OS that pages written by the checkpoint should be
   flushed to disk after a configurable number of bytes.  Otherwise, these
   pages may be kept in the OS's page cache, inducing a stall when
   fsync is issued at the end of a checkpoint.  This setting will
   often help to reduce transaction latency, but it also can have an adverse
   effect on performance; particularly for workloads that are bigger than
   shared_buffers, but smaller than the OS's page cache.
  
   The number of WAL segment files in pg_wal directory depends on
   min_wal_size, max_wal_size and
   the amount of WAL generated in previous checkpoint cycles. When old log
   segment files are no longer needed, they are removed or recycled (that is,
   renamed to become future segments in the numbered sequence). If, due to a
   short-term peak of log output rate, max_wal_size is
   exceeded, the unneeded segment files will be removed until the system
   gets back under this limit. Below that limit, the system recycles enough
   WAL files to cover the estimated need until the next checkpoint, and
   removes the rest. The estimate is based on a moving average of the number
   of WAL files used in previous checkpoint cycles. The moving average
   is increased immediately if the actual usage exceeds the estimate, so it
   accommodates peak usage rather than average usage to some extent.
   min_wal_size puts a minimum on the amount of WAL files
   recycled for future usage; that much WAL is always recycled for future use,
   even if the system is idle and the WAL usage estimate suggests that little
   WAL is needed.
  
   Independently of max_wal_size,
   wal_keep_segments + 1 most recent WAL files are
   kept at all times. Also, if WAL archiving is used, old segments can not be
   removed or recycled until they are archived. If WAL archiving cannot keep up
   with the pace that WAL is generated, or if archive_command
   fails repeatedly, old WAL files will accumulate in pg_wal
   until the situation is resolved. A slow or failed standby server that
   uses a replication slot will have the same effect (see
   Section 26.2.6).
  
   In archive recovery or standby mode, the server periodically performs
   restartpoints,
   which are similar to checkpoints in normal operation: the server forces
   all its state to disk, updates the pg_control file to
   indicate that the already-processed WAL data need not be scanned again,
   and then recycles any old log segment files in the pg_wal
   directory.
   Restartpoints can't be performed more frequently than checkpoints in the
   master because restartpoints can only be performed at checkpoint records.
   A restartpoint is triggered when a checkpoint record is reached if at
   least checkpoint_timeout seconds have passed since the last
   restartpoint, or if WAL size is about to exceed
   max_wal_size. However, because of limitations on when a
   restartpoint can be performed, max_wal_size is often exceeded
   during recovery, by up to one checkpoint cycle's worth of WAL.
   (max_wal_size is never a hard limit anyway, so you should
   always leave plenty of headroom to avoid running out of disk space.)
  
   There are two commonly used internal WAL functions:
   XLogInsertRecord and XLogFlush.
   XLogInsertRecord is used to place a new record into
   the WAL buffers in shared memory. If there is no
   space for the new record, XLogInsertRecord will have
   to write (move to kernel cache) a few filled WAL
   buffers. This is undesirable because XLogInsertRecord
   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 an XLogFlush 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, XLogFlush requests might
   not occur often enough to prevent XLogInsertRecord
   from having to do writes.  On such systems
   one should increase the number of WAL buffers by
   modifying the wal_buffers parameter.  When
   full_page_writes is set and the system is very busy,
   setting wal_buffers higher will help smooth response times
   during the period immediately following each checkpoint.
  
   The commit_delay parameter defines for how many
   microseconds a group commit leader process will sleep after acquiring a
   lock within XLogFlush, while group commit
   followers queue up behind the leader.  This delay allows other server
   processes to add their commit records to the WAL buffers so that all of
   them will be flushed by the leader's eventual sync operation.  No sleep
   will occur if fsync is not enabled, or 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 some 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.  Note also that on some
   platforms, sleep operations may take slightly longer than requested by
   the parameter.
  
   Since the purpose of commit_delay is to allow the
   cost of each flush operation to be amortized across concurrently
   committing transactions (potentially at the expense of transaction
   latency), it is necessary to quantify that cost before the setting can
   be chosen intelligently.  The higher that cost is, the more effective
   commit_delay is expected to be in increasing
   transaction throughput, up to a point.  The pg_test_fsync program can be used to measure the average time
   in microseconds that a single WAL flush operation takes.  A value of
   half of the average time the program reports it takes to flush after a
   single 8kB write operation is often the most effective setting for
   commit_delay, so this value is recommended as the
   starting point to use when optimizing for a particular workload.  While
   tuning commit_delay is particularly useful when the
   WAL log is stored on high-latency rotating disks, benefits can be
   significant even on storage media with very fast sync times, such as
   solid-state drives or RAID arrays with a battery-backed write cache;
   but this should definitely be tested against a representative workload.
   Higher values of commit_siblings should be used in
   such cases, whereas smaller commit_siblings values
   are often helpful on higher latency media.  Note that it is quite
   possible that a setting of commit_delay that is too
   high can increase transaction latency by so much that total transaction
   throughput suffers.
  
   When commit_delay is set to zero (the default), it
   is still possible for a form of group commit to occur, but each group
   will consist only of sessions that reach the point where they need to
   flush their commit records during the window in which the previous
   flush operation (if any) is occurring.  At higher client counts a
   “gangway effect” tends to occur, so that the effects of group
   commit become significant even when commit_delay is
   zero, and thus explicitly setting commit_delay tends
   to help less.  Setting commit_delay can only help
   when (1) there are some concurrently committing transactions, and (2)
   throughput is limited to some degree by commit rate; but with high
   rotational latency this setting can be effective in increasing
   transaction throughput with as few as two clients (that is, a single
   committing client with one sibling transaction).
  
   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 in terms of reliability, with
   the exception of fsync_writethrough, which can sometimes
   force a flush of the disk cache even when other options do not do so.
   However, it's quite platform-specific which one will be the fastest.
   You can test the speeds of different options using the pg_test_fsync program.
   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
   XLogInsertRecord and XLogFlush
   WAL call being logged to the server log. This
   option might be replaced by a more general mechanism in the future.