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<chapter id="wal">
 <title>Reliability and the Write-Ahead Log</title>

 <para>
  This chapter explain 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 periodically to the disk platters 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 may 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 passed
   along to the drive as soon as they arrive. Others are
   <firstterm>write-back</>, meaning data is passed on 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-backed</> caches, 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
   exist for disk controller caches.  Consumer-grade IDE drives are
   particularly likely to contain write-back caches that will not
   survive a power failure.
  </para>

  <para>
   When the operating system sends a write request to the disk 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 be sure 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.
  </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 512 bytes,
   1024 bytes, or 8192 bytes, and the process of writing could fail due
   to power loss at any time, meaning some of the 512-byte sectors were
   written, and others were not.  To guard against such failures,
   <productname>PostgreSQL</> periodically writes full page images to
   permanent storage <emphasis>before</> modifying the actual page on
   disk. By doing this, during crash recovery <productname>PostgreSQL</> can
   restore partially-written pages.  If you have a battery-backed disk
   controller or file-system software (e.g., Reiser4) that prevents partial
   page writes,  you can turn off this page imaging by using the 
   <xref linkend="guc-full-page-writes"> parameter.
  </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 approach to transaction logging.  Its detailed
    description may 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, when 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>

   <para>
    A major benefit of using <acronym>WAL</acronym> is a
    significantly reduced number of disk writes, because only the log
    file needs to be flushed to disk at the time of transaction
    commit, rather than every data file changed by the transaction.
    In multiuser environments, commits of many transactions
    may be accomplished with a single <function>fsync</function> of
    the log file. Furthermore, 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.
   </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 &mdash; 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-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 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.
   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 known to be already on disk.  Hence, after
   a checkpoint has been made, any 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 server's background writer process will automatically perform
   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 respectively.
   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 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 
   <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 may cause a number of such warnings
   to appear if you have not set <varname>checkpoint_segments</> high
   enough.
  </para>

  <para>
   There will be at least one WAL segment file, and will normally
   not be more than 2 * <varname>checkpoint_segments</varname> + 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 2 * <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>
   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 may 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 may
   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">.  The default number of <acronym>WAL</acronym>
   buffers is 8.  Increasing this value will
   correspondingly increase shared memory usage.  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, nor 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 as far as reliability goes,
   but it's quite platform-specific which one will be the fastest.
   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 may 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.  Each segment is divided into
   pages, normally 8 KB each.  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, at
   present, but it should take a very very long time to exhaust the
   available stock of numbers.
  </para>

  <para>
   It is of advantage if the log is located on another disk than the
   main database files.  This may be achieved by moving the directory
   <filename>pg_xlog</filename> 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>, to ensure that the log is
   written before database records are altered, may 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 may still 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.
  </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, when recovery is to be
   done, 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, 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
   corrupted, we should support the possibility of scanning existing log
   segments in reverse order &mdash; newest to oldest &mdash; 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 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>

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