There are several WAL-related configuration parameters that affect database performance. This section explains their use. Consult Chapter 17 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,
LightDB 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 lt_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
,
the most recent wal_keep_size megabytes of
WAL files plus one additional WAL file are
kept at all times. Also, if WAL archiving is used, old segments cannot 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 lt_wal
until the situation is resolved. A slow or failed standby server that
uses a replication slot will have the same effect (see
Section 24.2.6).
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 lt_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 lt_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 lt_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
LightDB 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 lt_test_fsync program.
Note that this parameter is irrelevant if fsync
has been turned off.
Enabling the wal_debug configuration parameter
(provided that LightDB 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.