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Magnus Hagander authored
This hasn't been true since 9.1, when the default was changed to -1. Remove the reference completely, keeping the discussion of the parameter and it's shared memory effects on the config page.
Magnus Hagander authoredThis hasn't been true since 9.1, when the default was changed to -1. Remove the reference completely, keeping the discussion of the parameter and it's shared memory effects on the config page.
wal.sgml 32.67 KiB
<!-- doc/src/sgml/wal.sgml -->
<chapter id="wal">
<title>Reliability and the Write-Ahead Log</title>
<para>
This chapter explains how the Write-Ahead Log is used to obtain
efficient, reliable operation.
</para>
<sect1 id="wal-reliability">
<title>Reliability</title>
<para>
Reliability is an important property of any serious database
system, and <productname>PostgreSQL</> does everything possible to
guarantee reliable operation. One aspect of reliable operation is
that all data recorded by a committed transaction should be stored
in a nonvolatile area that is safe from power loss, operating
system failure, and hardware failure (except failure of the
nonvolatile area itself, of course). Successfully writing the data
to the computer's permanent storage (disk drive or equivalent)
ordinarily meets this requirement. In fact, even if a computer is
fatally damaged, if the disk drives survive they can be moved to
another computer with similar hardware and all committed
transactions will remain intact.
</para>
<para>
While forcing data to the disk platters periodically might seem like
a simple operation, it is not. Because disk drives are dramatically
slower than main memory and CPUs, several layers of caching exist
between the computer's main memory and the disk platters.
First, there is the operating system's buffer cache, which caches
frequently requested disk blocks and combines disk writes. Fortunately,
all operating systems give applications a way to force writes from
the buffer cache to disk, and <productname>PostgreSQL</> uses those
features. (See the <xref linkend="guc-wal-sync-method"> parameter
to adjust how this is done.)
</para>
<para>
Next, there might be a cache in the disk drive controller; this is
particularly common on <acronym>RAID</> controller cards. Some of
these caches are <firstterm>write-through</>, meaning writes are sent
to the drive as soon as they arrive. Others are
<firstterm>write-back</>, meaning data is sent to the drive at
some later time. Such caches can be a reliability hazard because the
memory in the disk controller cache is volatile, and will lose its
contents in a power failure. Better controller cards have
<firstterm>battery-backup units</> (<acronym>BBU</>s), meaning
the card has a battery that
maintains power to the cache in case of system power loss. After power
is restored the data will be written to the disk drives.
</para>
<para>
And finally, most disk drives have caches. Some are write-through
while some are write-back, and the same concerns about data loss
exist for write-back drive caches as for disk controller
caches. Consumer-grade IDE and SATA drives are particularly likely
to have write-back caches that will not survive a power failure. Many
solid-state drives (SSD) also have volatile write-back caches.
</para>
<para>
These caches can typically be disabled; however, the method for doing
this varies by operating system and drive type:
</para>
<itemizedlist>
<listitem>
<para>
On <productname>Linux</>, IDE drives can be queried using
<command>hdparm -I</command>; write caching is enabled if there is
a <literal>*</> next to <literal>Write cache</>. <command>hdparm -W 0</>
can be used to turn off write caching. SCSI drives can be queried
using <ulink url="http://sg.danny.cz/sg/sdparm.html"><application>sdparm</></ulink>.
Use <command>sdparm --get=WCE</command> to check
whether the write cache is enabled and <command>sdparm --clear=WCE</>
to disable it.
</para>
</listitem>
<listitem>
<para>
On <productname>FreeBSD</>, IDE drives can be queried using
<command>atacontrol</command> and write caching turned off using
<literal>hw.ata.wc=0</> in <filename>/boot/loader.conf</>;
SCSI drives can be queried using <command>camcontrol identify</command>,
and the write cache both queried and changed using
<command>sdparm</command> when available.
</para>
</listitem>
<listitem>
<para>
On <productname>Solaris</>, the disk write cache is controlled by
<ulink url="http://www.sun.com/bigadmin/content/submitted/format_utility.jsp"><literal>format -e</></ulink>.
(The Solaris <acronym>ZFS</> file system is safe with disk write-cache
enabled because it issues its own disk cache flush commands.)
</para>
</listitem>
<listitem>
<para>
On <productname>Windows</>, if <varname>wal_sync_method</> is
<literal>open_datasync</> (the default), write caching can be disabled
by unchecking <literal>My Computer\Open\<replaceable>disk drive</>\Properties\Hardware\Properties\Policies\Enable write caching on the disk</>.
Alternatively, set <varname>wal_sync_method</varname> to
<literal>fsync</> or <literal>fsync_writethrough</>, which prevent
write caching.
</para>
</listitem>
<listitem>
<para>
On <productname>Mac OS X</productname>, write caching can be prevented by
setting <varname>wal_sync_method</> to <literal>fsync_writethrough</>.
</para>
</listitem>
</itemizedlist>
<para>
Recent SATA drives (those following <acronym>ATAPI-6</> or later)
offer a drive cache flush command (<command>FLUSH CACHE EXT</>),
while SCSI drives have long supported a similar command
<command>SYNCHRONIZE CACHE</>. These commands are not directly
accessible to <productname>PostgreSQL</>, but some file systems
(e.g., <acronym>ZFS</>, <acronym>ext4</>) can use them to flush
data to the platters on write-back-enabled drives. Unfortunately, such
file systems behave suboptimally when combined with battery-backup unit
(<acronym>BBU</>) disk controllers. In such setups, the synchronize
command forces all data from the controller cache to the disks,
eliminating much of the benefit of the BBU. You can run the
<xref linkend="pgtestfsync"> module to see
if you are affected. If you are affected, the performance benefits
of the BBU can be regained by turning off write barriers in
the file system or reconfiguring the disk controller, if that is
an option. If write barriers are turned off, make sure the battery remains functional; a faulty battery can potentially lead to data loss.
Hopefully file system and disk controller designers will eventually
address this suboptimal behavior.
</para>
<para>
When the operating system sends a write request to the storage hardware,
there is little it can do to make sure the data has arrived at a truly
non-volatile storage area. Rather, it is the
administrator's responsibility to make certain that all storage components
ensure data integrity. Avoid disk controllers that have non-battery-backed
write caches. At the drive level, disable write-back caching if the
drive cannot guarantee the data will be written before shutdown.
If you use SSDs, be aware that many of these do not honor cache flush
commands by default.
You can test for reliable I/O subsystem behavior using <ulink
url="http://brad.livejournal.com/2116715.html"><filename>diskchecker.pl</filename></ulink>.
</para>
<para>
Another risk of data loss is posed by the disk platter write
operations themselves. Disk platters are divided into sectors,
commonly 512 bytes each. Every physical read or write operation
processes a whole sector.
When a write request arrives at the drive, it might be for some multiple
of 512 bytes (<productname>PostgreSQL</> typically writes 8192 bytes, or
16 sectors, at a time), and the process of writing could fail due
to power loss at any time, meaning some of the 512-byte sectors were
written while others were not. To guard against such failures,
<productname>PostgreSQL</> periodically writes full page images to
permanent WAL storage <emphasis>before</> modifying the actual page on
disk. By doing this, during crash recovery <productname>PostgreSQL</> can
restore partially-written pages from WAL. If you have file-system software
that prevents partial page writes (e.g., ZFS), you can turn off
this page imaging by turning off the <xref
linkend="guc-full-page-writes"> parameter. Battery-Backed Unit
(BBU) disk controllers do not prevent partial page writes unless
they guarantee that data is written to the BBU as full (8kB) pages.
</para>
</sect1>
<sect1 id="wal-intro">
<title>Write-Ahead Logging (<acronym>WAL</acronym>)</title>
<indexterm zone="wal">
<primary>WAL</primary>
</indexterm>
<indexterm>
<primary>transaction log</primary>
<see>WAL</see>
</indexterm>
<para>
<firstterm>Write-Ahead Logging</firstterm> (<acronym>WAL</acronym>)
is a standard method for ensuring data integrity. A detailed
description can be found in most (if not all) books about
transaction processing. Briefly, <acronym>WAL</acronym>'s central
concept is that changes to data files (where tables and indexes
reside) must be written only after those changes have been logged,
that is, after log records describing the changes have been flushed
to permanent storage. If we follow this procedure, we do not need
to flush data pages to disk on every transaction commit, because we
know that in the event of a crash we will be able to recover the
database using the log: any changes that have not been applied to
the data pages can be redone from the log records. (This is
roll-forward recovery, also known as REDO.)
</para>
<tip> <para>
Because <acronym>WAL</acronym> restores database file
contents after a crash, journaled file systems are not necessary for
reliable storage of the data files or WAL files. In fact, journaling
overhead can reduce performance, especially if journaling
causes file system <emphasis>data</emphasis> to be flushed
to disk. Fortunately, data flushing during journaling can
often be disabled with a file system mount option, e.g.
<literal>data=writeback</> on a Linux ext3 file system.
Journaled file systems do improve boot speed after a crash.
</para>
</tip>
<para>
Using <acronym>WAL</acronym> results in a
significantly reduced number of disk writes, because only the log
file needs to be flushed to disk to guarantee that a transaction is
committed, rather than every data file changed by the transaction.
The log file is written sequentially,
and so the cost of syncing the log is much less than the cost of
flushing the data pages. This is especially true for servers
handling many small transactions touching different parts of the data
store. Furthermore, when the server is processing many small concurrent
transactions, one <function>fsync</function> of the log file may
suffice to commit many transactions.
</para>
<para>
<acronym>WAL</acronym> also makes it possible to support on-line
backup and point-in-time recovery, as described in <xref
linkend="continuous-archiving">. By archiving the WAL data we can support
reverting to any time instant covered by the available WAL data:
we simply install a prior physical backup of the database, and
replay the WAL log just as far as the desired time. What's more,
the physical backup doesn't have to be an instantaneous snapshot
of the database state — if it is made over some period of time,
then replaying the WAL log for that period will fix any internal
inconsistencies.
</para>
</sect1>
<sect1 id="wal-async-commit">
<title>Asynchronous Commit</title>
<indexterm>
<primary>synchronous commit</primary>
</indexterm>
<indexterm>
<primary>asynchronous commit</primary>
</indexterm>
<para>
<firstterm>Asynchronous commit</> is an option that allows transactions
to complete more quickly, at the cost that the most recent transactions may
be lost if the database should crash. In many applications this is an
acceptable trade-off.
</para>
<para>
As described in the previous section, transaction commit is normally
<firstterm>synchronous</>: the server waits for the transaction's
<acronym>WAL</acronym> records to be flushed to permanent storage
before returning a success indication to the client. The client is
therefore guaranteed that a transaction reported to be committed will
be preserved, even in the event of a server crash immediately after.
However, for short transactions this delay is a major component of the
total transaction time. Selecting asynchronous commit mode means that
the server returns success as soon as the transaction is logically completed, before the <acronym>WAL</acronym> records it generated have
actually made their way to disk. This can provide a significant boost
in throughput for small transactions.
</para>
<para>
Asynchronous commit introduces the risk of data loss. There is a short
time window between the report of transaction completion to the client
and the time that the transaction is truly committed (that is, it is
guaranteed not to be lost if the server crashes). Thus asynchronous
commit should not be used if the client will take external actions
relying on the assumption that the transaction will be remembered.
As an example, a bank would certainly not use asynchronous commit for
a transaction recording an ATM's dispensing of cash. But in many
scenarios, such as event logging, there is no need for a strong
guarantee of this kind.
</para>
<para>
The risk that is taken by using asynchronous commit is of data loss,
not data corruption. If the database should crash, it will recover
by replaying <acronym>WAL</acronym> up to the last record that was
flushed. The database will therefore be restored to a self-consistent
state, but any transactions that were not yet flushed to disk will
not be reflected in that state. The net effect is therefore loss of
the last few transactions. Because the transactions are replayed in
commit order, no inconsistency can be introduced — for example,
if transaction B made changes relying on the effects of a previous
transaction A, it is not possible for A's effects to be lost while B's
effects are preserved.
</para>
<para>
The user can select the commit mode of each transaction, so that
it is possible to have both synchronous and asynchronous commit
transactions running concurrently. This allows flexible trade-offs
between performance and certainty of transaction durability.
The commit mode is controlled by the user-settable parameter
<xref linkend="guc-synchronous-commit">, which can be changed in any of
the ways that a configuration parameter can be set. The mode used for
any one transaction depends on the value of
<varname>synchronous_commit</varname> when transaction commit begins.
</para>
<para>
Certain utility commands, for instance <command>DROP TABLE</>, are
forced to commit synchronously regardless of the setting of
<varname>synchronous_commit</varname>. This is to ensure consistency
between the server's file system and the logical state of the database.
The commands supporting two-phase commit, such as <command>PREPARE
TRANSACTION</>, are also always synchronous.
</para>
<para>
If the database crashes during the risk window between an
asynchronous commit and the writing of the transaction's
<acronym>WAL</acronym> records,
then changes made during that transaction <emphasis>will</> be lost.
The duration of the
risk window is limited because a background process (the <quote>WAL
writer</>) flushes unwritten <acronym>WAL</acronym> records to disk
every <xref linkend="guc-wal-writer-delay"> milliseconds.
The actual maximum duration of the risk window is three times
<varname>wal_writer_delay</varname> because the WAL writer is
designed to favor writing whole pages at a time during busy periods.
</para>
<caution>
<para>
An immediate-mode shutdown is equivalent to a server crash, and will therefore cause loss of any unflushed asynchronous commits.
</para>
</caution>
<para>
Asynchronous commit provides behavior different from setting
<xref linkend="guc-fsync"> = off.
<varname>fsync</varname> is a server-wide
setting that will alter the behavior of all transactions. It disables
all logic within <productname>PostgreSQL</> that attempts to synchronize
writes to different portions of the database, and therefore a system
crash (that is, a hardware or operating system crash, not a failure of
<productname>PostgreSQL</> itself) could result in arbitrarily bad
corruption of the database state. In many scenarios, asynchronous
commit provides most of the performance improvement that could be
obtained by turning off <varname>fsync</varname>, but without the risk
of data corruption.
</para>
<para>
<xref linkend="guc-commit-delay"> also sounds very similar to
asynchronous commit, but it is actually a synchronous commit method
(in fact, <varname>commit_delay</varname> is ignored during an
asynchronous commit). <varname>commit_delay</varname> causes a delay
just before a synchronous commit attempts to flush
<acronym>WAL</acronym> to disk, in the hope that a single flush
executed by one such transaction can also serve other transactions
committing at about the same time. Setting <varname>commit_delay</varname>
can only help when there are many concurrently committing transactions,
and it is difficult to tune it to a value that actually helps rather
than hurts throughput.
</para>
</sect1>
<sect1 id="wal-configuration">
<title><acronym>WAL</acronym> Configuration</title>
<para>
There are several <acronym>WAL</>-related configuration parameters that
affect database performance. This section explains their use.
Consult <xref linkend="runtime-config"> for general information about
setting server configuration parameters.
</para>
<para>
<firstterm>Checkpoints</firstterm><indexterm><primary>checkpoint</></>
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
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 <acronym>WAL</acronym> 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
<acronym>WAL</acronym> archiving is being done, the log segments must be
archived before being recycled or removed.)
</para>
<para>
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.
</para>
<para>
The server's checkpointer process automatically performs
a checkpoint every so often. A checkpoint is created every <xref
linkend="guc-checkpoint-segments"> log segments, or every <xref
linkend="guc-checkpoint-timeout"> seconds, whichever comes first.
The default settings are 3 segments and 300 seconds (5 minutes), respectively.
In cases where little or no WAL has been written, checkpoints will be
skipped even if checkpoint_timeout has passed. At least one new WAL segment
must have been created before an automatic checkpoint occurs. The time
between checkpoints and when new WAL segments are created are not related
in any other way. If file-based WAL shipping is being used and you want to
bound how often files are sent to standby server to reduce potential data
loss, you should adjust archive_timeout parameter rather than the checkpoint
parameters. It is also possible to force a checkpoint by using the SQL
command <command>CHECKPOINT</command>.
</para>
<para>
Reducing <varname>checkpoint_segments</varname> and/or
<varname>checkpoint_timeout</varname> 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
<xref linkend="guc-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.
</para>
<para>
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 <xref linkend="guc-checkpoint-warning">
parameter. If checkpoints happen closer together than
<varname>checkpoint_warning</> seconds,
a message will be output to the server log recommending increasing
<varname>checkpoint_segments</varname>. 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 <command>COPY</> transfers might cause a number of such warnings
to appear if you have not set <varname>checkpoint_segments</> high
enough.
</para>
<para>
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
<xref linkend="guc-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 <varname>checkpoint_segments</varname> WAL segments
have been consumed since checkpoint start, or the given fraction of
<varname>checkpoint_timeout</varname> seconds have elapsed,
whichever is sooner. With the default value of 0.5,
<productname>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 <varname>checkpoint_completion_target</varname>
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
<varname>checkpoint_completion_target</varname> 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.
</para>
<para>
There will always be at least one WAL segment file, and will normally
not be more than (2 + <varname>checkpoint_completion_target</varname>) * <varname>checkpoint_segments</varname> + 1
or <varname>checkpoint_segments</> + <xref linkend="guc-wal-keep-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 <acronym>WAL</acronym>.
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 * <varname>checkpoint_segments</varname> + 1
segment files, the unneeded segment files will be deleted instead
of recycled until the system gets back under this limit.
</para>
<para>
In archive recovery or standby mode, the server periodically performs
<firstterm>restartpoints</><indexterm><primary>restartpoint</></>
which are similar to checkpoints in normal operation: the server forces
all its state to disk, updates the <filename>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 <filename>pg_xlog</>
directory. A restartpoint is triggered if at least one checkpoint record
has been replayed and <varname>checkpoint_timeout</> seconds have passed
since last restartpoint. In standby mode, a restartpoint is also triggered
if <varname>checkpoint_segments</> log segments have been replayed since
last restartpoint and at least one checkpoint record has been replayed.
Restartpoints can't be performed more frequently than checkpoints in the
master because restartpoints can only be performed at checkpoint records.
</para>
<para>
There are two commonly used internal <acronym>WAL</acronym> functions:
<function>LogInsert</function> and <function>LogFlush</function>.
<function>LogInsert</function> is used to place a new record into
the <acronym>WAL</acronym> buffers in shared memory. If there is no
space for the new record, <function>LogInsert</function> will have
to write (move to kernel cache) a few filled <acronym>WAL</acronym>
buffers. This is undesirable because <function>LogInsert</function>
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 <acronym>WAL</acronym> buffers might also force the
creation of a new log segment, which takes even more
time. Normally, <acronym>WAL</acronym> buffers should be written
and flushed by a <function>LogFlush</function> 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, <function>LogFlush</function> requests might
not occur often enough to prevent <function>LogInsert</function>
from having to do writes. On such systems
one should increase the number of <acronym>WAL</acronym> buffers by
modifying the configuration parameter <xref
linkend="guc-wal-buffers">. When
<xref linkend="guc-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.
</para>
<para>
The <xref linkend="guc-commit-delay"> parameter defines for how many
microseconds the server process will sleep after writing a commit
record to the log with <function>LogInsert</function> but before
performing a <function>LogFlush</function>. 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
<xref linkend="guc-fsync">
is not enabled, or if fewer than <xref linkend="guc-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 <varname>commit_delay</varname>
setting between 1 and 10000 microseconds would have the same effect.
Good values for these parameters are not yet clear; experimentation
is encouraged.
</para>
<para>
The <xref linkend="guc-wal-sync-method"> parameter determines how
<productname>PostgreSQL</productname> will ask the kernel to force
<acronym>WAL</acronym> updates out to disk.
All the options should be the same in terms of reliability, with
the exception of <literal>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 option speeds using the <xref
linkend="pgtestfsync"> module.
Note that this parameter is irrelevant if <varname>fsync</varname>
has been turned off.
</para>
<para>
Enabling the <xref linkend="guc-wal-debug"> configuration parameter
(provided that <productname>PostgreSQL</productname> has been
compiled with support for it) will result in each
<function>LogInsert</function> and <function>LogFlush</function>
<acronym>WAL</acronym> call being logged to the server log. This
option might be replaced by a more general mechanism in the future.
</para>
</sect1>
<sect1 id="wal-internals">
<title>WAL Internals</title>
<para>
<acronym>WAL</acronym> is automatically enabled; no action is
required from the administrator except ensuring that the
disk-space requirements for the <acronym>WAL</acronym> logs are met,
and that any necessary tuning is done (see <xref
linkend="wal-configuration">).
</para>
<para>
<acronym>WAL</acronym> logs are stored in the directory
<filename>pg_xlog</filename> under the data directory, as a set of
segment files, normally each 16 MB in size (but the size can be changed
by altering the <option>--with-wal-segsize</> configure option when
building the server). Each segment is divided into pages, normally
8 kB each (this size can be changed via the <option>--with-wal-blocksize</>
configure option). The log record headers are described in
<filename>access/xlog.h</filename>; the record content is dependent
on the type of event that is being logged. Segment files are given
ever-increasing numbers as names, starting at
<filename>000000010000000000000000</filename>. The numbers do not wrap,
but it will take a very, very long time to exhaust the
available stock of numbers.
</para>
<para>
It is advantageous if the log is located on a different disk from the
main database files. This can be achieved by moving the
<filename>pg_xlog</filename> directory to another location (while the server
is shut down, of course) and creating a symbolic link from the
original location in the main data directory to the new location. </para>
<para>
The aim of <acronym>WAL</acronym> is to ensure that the log is
written before database records are altered, but this can be subverted by
disk drives<indexterm><primary>disk drive</></> that falsely report a
successful write to the kernel,
when in fact they have only cached the data and not yet stored it
on the disk. A power failure in such a situation might lead to
irrecoverable data corruption. Administrators should try to ensure
that disks holding <productname>PostgreSQL</productname>'s
<acronym>WAL</acronym> log files do not make such false reports.
(See <xref linkend="wal-reliability">.)
</para>
<para>
After a checkpoint has been made and the log flushed, the
checkpoint's position is saved in the file
<filename>pg_control</filename>. Therefore, at the start of recovery,
the server first reads <filename>pg_control</filename> and
then the checkpoint record; then it performs the REDO operation by
scanning forward from the log position indicated in the checkpoint
record. Because the entire content of data pages is saved in the
log on the first page modification after a checkpoint (assuming
<xref linkend="guc-full-page-writes"> is not disabled), all pages
changed since the checkpoint will be restored to a consistent
state.
</para>
<para>
To deal with the case where <filename>pg_control</filename> is
corrupt, we should support the possibility of scanning existing log
segments in reverse order — newest to oldest — in order to find the
latest checkpoint. This has not been implemented yet.
<filename>pg_control</filename> is small enough (less than one disk page)
that it is not subject to partial-write problems, and as of this writing
there have been no reports of database failures due solely to the inability
to read <filename>pg_control</filename> itself. So while it is
theoretically a weak spot, <filename>pg_control</filename> does not
seem to be a problem in practice.
</para>
</sect1>
</chapter>