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<chapter id="maintenance">
 <title>Routine Database Maintenance Tasks</title>

 <sect1 id="maintenance-general">
  <title>General Discussion</Title>

  <para>
   There are a few routine maintenance chores that must be performed on
   a regular basis to keep a <productname>PostgreSQL</productname>
   installation running smoothly.  The tasks discussed here are repetitive
   in nature and can easily be automated using standard Unix tools such
   as <filename>cron</filename> scripts.  But it is the database
   administrator's responsibility to set up appropriate scripts, and to
   check that they execute successfully.
  </para>

  <para>
   One obvious maintenance task is creation of backup copies of the data on a
   regular schedule.  Without a recent backup, you have no chance of recovery
   after a catastrophe (disk failure, fire, mistakenly dropping a critical
   table, etc).  The backup and recovery mechanisms available in
   <productname>PostgreSQL</productname> are discussed at length in
   <xref linkend="backup">.
  </para>

  <para>
   The other main category of maintenance task is periodic <quote>vacuuming</>
   of the database.  This activity is discussed in
   <xref linkend="routine-vacuuming">.
  </para>

  <para>
   Something else that might need periodic attention is log file management.
   This is discussed in <xref linkend="logfile-maintenance">.
  </para>

  <para>
   <productname>PostgreSQL</productname> is low-maintenance compared to
   some other database products.  Nonetheless, appropriate attention to
   these tasks will go far towards ensuring a pleasant and productive
   experience with the system.
  </para>

 </sect1>

 <sect1 id="routine-vacuuming">
  <title>Routine Vacuuming</title>

  <indexterm zone="routine-vacuuming">
   <primary>vacuum</primary>
  </indexterm>

  <para>
   <productname>PostgreSQL</productname>'s <command>VACUUM</> command
   must be run on a regular basis for several reasons:

    <orderedlist>
     <listitem>
      <simpara>To recover disk space occupied by updated or deleted
      rows.</simpara>
     </listitem>

     <listitem>
      <simpara>To update data statistics used by the
      <productname>PostgreSQL</productname> query planner.</simpara>
     </listitem>

     <listitem>
      <simpara>To protect against loss of very old data due to
      <firstterm>transaction ID wraparound</>.</simpara>
     </listitem>
    </orderedlist>

   The frequency and scope of <command>VACUUM</>s performed for each of
   these reasons will vary depending on the needs of each installation.
   Therefore, database administrators must understand these issues and
   develop an appropriate maintenance strategy.  This section concentrates
   on explaining the high-level issues; for details about command syntax
   and so on, see the <command>VACUUM</> command reference page.
  </para>

  <para>
   Beginning in <productname>PostgreSQL</productname> 7.2, the standard form
   of <command>VACUUM</> can run in parallel with normal database operations
   (selects, inserts, updates, deletes, but not changes to table schemas).
   Routine vacuuming is therefore not nearly as intrusive as it was in prior
   releases, and it's not as critical to try to schedule it at low-usage
   times of day.
  </para>

  <sect2 id="vacuum-for-space-recovery">
   <title>Recovering disk space</title>

   <indexterm zone="vacuum-for-space-recovery">
    <primary>disk space</primary>
   </indexterm>

   <para>
    In normal <productname>PostgreSQL</productname> operation, an
    <command>UPDATE</> or <command>DELETE</> of a row does not
    immediately remove the old <firstterm>tuple</> (version of the row).
    This approach is necessary to gain the benefits of multiversion
    concurrency control (see the <citetitle>User's Guide</>): the tuple
    must not be deleted while it is still potentially visible to other
    transactions. But eventually, an outdated or deleted tuple is no
    longer of interest to any transaction. The space it occupies must be
    reclaimed for reuse by new tuples, to avoid infinite growth of disk
    space requirements. This is done by running <command>VACUUM</>.
   </para>

   <para>
    Clearly, a table that receives frequent updates or deletes will need
    to be vacuumed more often than tables that are seldom updated. It
    may be useful to set up periodic <application>cron</> tasks that
    vacuum only selected tables, skipping tables that are known not to
    change often. This is only likely to be helpful if you have both
    large heavily-updated tables and large seldom-updated tables --- the
    extra cost of vacuuming a small table isn't enough to be worth
    worrying about.
   </para>

   <para>
    The standard form of <command>VACUUM</> is best used with the goal of
    maintaining a fairly level steady-state usage of disk space.  The standard
    form finds old tuples and makes their space available for re-use within
    the table, but it does not try very hard to shorten the table file and
    return disk space to the operating system.  If you need to return disk
    space to the operating system you can use <command>VACUUM FULL</> ---
    but what's the point of releasing disk space that will only have to be
    allocated again soon?  Moderately frequent standard <command>VACUUM</>s
    are a better approach than infrequent <command>VACUUM FULL</>s for
    maintaining heavily-updated tables.
   </para>

   <para>
    Recommended practice for most sites is to schedule a database-wide
    <command>VACUUM</> once a day at a low-usage time of day, supplemented
    by more frequent vacuuming of heavily-updated tables if necessary.
    (If you have multiple databases in an installation, don't forget to
    vacuum each one; the <filename>vacuumdb</> script may be helpful.)
    Use plain <command>VACUUM</>, not <command>VACUUM FULL</>, for routine
    vacuuming for space recovery.
   </para>

   <para>
    <command>VACUUM FULL</> is recommended for cases where you know you have
    deleted the majority of tuples in a table, so that the steady-state size
    of the table can be shrunk substantially with <command>VACUUM FULL</>'s
    more aggressive approach.
   </para>

   <para>
    If you have a table whose contents are deleted completely every so often,
    consider doing it with <command>TRUNCATE</> rather than using
    <command>DELETE</> followed by <command>VACUUM</>.
   </para>
  </sect2>

  <sect2 id="vacuum-for-statistics">
   <title>Updating planner statistics</title>

   <para>
    The <productname>PostgreSQL</productname> query planner relies on
    statistical information about the contents of tables in order to
    generate good plans for queries.  These statistics are gathered by
    the <command>ANALYZE</> command, which can be invoked by itself or
    as an optional step in <command>VACUUM</>.  It is important to have
    reasonably accurate statistics, otherwise poor choices of plans may
    degrade database performance.
   </para>

   <para>
    As with vacuuming for space recovery, frequent updates of statistics
    are more useful for heavily-updated tables than for seldom-updated
    ones. But even for a heavily-updated table, there may be no need for
    statistics updates if the statistical distribution of the data is
    not changing much. A simple rule of thumb is to think about how much
    the minimum and maximum values of the columns in the table change.
    For example, a <type>timestamp</type> column that contains the time
    of row update will have a constantly-increasing maximum value as
    rows are added and updated; such a column will probably need more
    frequent statistics updates than, say, a column containing URLs for
    pages accessed on a website. The URL column may receive changes just
    as often, but the statistical distribution of its values probably
    changes relatively slowly.
   </para>

   <para>
    It is possible to run <command>ANALYZE</> on specific tables and even
    just specific columns of a table, so the flexibility exists to update some
    statistics more frequently than others if your application requires it.
    In practice, however, the usefulness of this feature is doubtful.
    Beginning in <productname>PostgreSQL</productname> 7.2,
    <command>ANALYZE</> is a fairly fast operation even on large tables,
    because it uses a statistical random sampling of the rows of a table
    rather than reading every single row.  So it's probably much simpler
    to just run it over the whole database every so often.
   </para>

   <tip>
    <para>
     Although per-column tweaking of <command>ANALYZE</> frequency may not be
     very productive, you may well find it worthwhile to do per-column
     adjustment of the level of detail of the statistics collected by
     <command>ANALYZE</>.  Columns that are heavily used in WHERE clauses
     and have highly irregular data distributions may require a finer-grain
     data histogram than other columns.  See <command>ALTER TABLE SET
     STATISTICS</>.
    </para>
   </tip>

   <para>
    Recommended practice for most sites is to schedule a database-wide
    <command>ANALYZE</> once a day at a low-usage time of day; this can
    usefully be combined with a nightly <command>VACUUM</>.  However,
    sites with relatively slowly changing table statistics may find that
    this is overkill, and that less-frequent <command>ANALYZE</> runs
    are sufficient.
   </para>
  </sect2>

  <sect2 id="vacuum-for-wraparound">
   <title>Preventing transaction ID wraparound failures</title>

   <indexterm zone="vacuum-for-wraparound">
    <primary>transaction ID</primary>
    <secondary>wraparound</secondary>
   </indexterm>

   <para>
    <productname>PostgreSQL</productname>'s MVCC transaction semantics
    depend on being able to compare transaction ID (<firstterm>XID</>)
    numbers: a tuple with an insertion XID newer than the current
    transaction's XID is <quote>in the future</> and should not be visible
    to the current transaction.  But since transaction IDs have limited size
    (32 bits at this writing) an installation that runs for a long time (more
    than 4 billion transactions) will suffer <firstterm>transaction ID
    wraparound</>: the XID counter wraps around to zero, and all of a sudden
    transactions that were in the past appear to be in the future --- which
    means their outputs become invisible.  In short, catastrophic data loss.
    (Actually the data is still there, but that's cold comfort if you can't
    get at it.)
   </para>

   <para>
    Prior to <productname>PostgreSQL</productname> 7.2, the only defense
    against XID wraparound was to re-<command>initdb</> at least every 4
    billion transactions. This of course was not very satisfactory for
    high-traffic sites, so a better solution has been devised. The new
    approach allows an installation to remain up indefinitely, without
    <command>initdb</> or any sort of restart. The price is this
    maintenance requirement: <emphasis>every table in the database must
    be vacuumed at least once every billion transactions</emphasis>.
   </para>

   <para>
    In practice this isn't an onerous requirement, but since the
    consequences of failing to meet it can be complete data loss (not
    just wasted disk space or slow performance), some special provisions
    have been made to help database administrators keep track of the
    time since the last <command>VACUUM</>. The remainder of this
    section gives the details.
   </para>

   <para>
    The new approach to XID comparison distinguishes two special XIDs,
    numbers 1 and 2 (<literal>BootstrapXID</> and
    <literal>FrozenXID</>). These two XIDs are always considered older
    than every normal XID. Normal XIDs (those greater than 2) are
    compared using modulo-2<superscript>31</> arithmetic. This means
    that for every normal XID, there are two billion XIDs that are
    <quote>older</> and two billion that are <quote>newer</>; another
    way to say it is that the normal XID space is circular with no
    endpoint. Therefore, once a tuple has been created with a particular
    normal XID, the tuple will appear to be <quote>in the past</> for
    the next two billion transactions, no matter which normal XID we are
    talking about. If the tuple still exists after more than two billion
    transactions, it will suddenly appear to be in the future. To
    prevent data loss, old tuples must be reassigned the XID
    <literal>FrozenXID</> sometime before they reach the
    two-billion-transactions-old mark. Once they are assigned this
    special XID, they will appear to be <quote>in the past</> to all
    normal transactions regardless of wraparound issues, and so such
    tuples will be good until deleted, no matter how long that is. This
    reassignment of XID is handled by <command>VACUUM</>.
   </para>

   <para>
    <command>VACUUM</>'s normal policy is to reassign <literal>FrozenXID</>
    to any tuple with a normal XID more than one billion transactions in the
    past.  This policy preserves the original insertion XID until it is not
    likely to be of interest anymore (in fact, most tuples will probably
    live and die without ever being <quote>frozen</>).  With this policy,
    the maximum safe interval between <command>VACUUM</>s of any table
    is exactly one billion transactions: if you wait longer, it's possible
    that a tuple that was not quite old enough to be reassigned last time
    is now more than two billion transactions old and has wrapped around
    into the future --- ie, is lost to you.  (Of course, it'll reappear
    after another two billion transactions, but that's no help.)
   </para>

   <para>
    Since periodic <command>VACUUM</>s are needed anyway for the reasons
    described earlier, it's unlikely that any table would not be vacuumed
    for as long as a billion transactions.  But to help administrators ensure
    this constraint is met, <command>VACUUM</> stores transaction ID
    statistics in the system table <filename>pg_database</>.  In particular,
    the <filename>datfrozenxid</> field of a database's
    <filename>pg_database</> row is updated at the completion of any
    database-wide vacuum operation (ie, <command>VACUUM</> that does not
    name a specific table).  The value stored in this field is the freeze
    cutoff XID that was used by that <command>VACUUM</> command.  All normal
    XIDs older than this cutoff XID are guaranteed to have been replaced by
    <literal>FrozenXID</> within that database.  A convenient way to
    examine this information is to execute the query
    <informalexample>
<programlisting>
SELECT datname, age(datfrozenxid) FROM pg_database;
</programlisting>
    </informalexample>
    The <literal>age</> column measures the number of transactions from the
    cutoff XID to the current transaction's XID.
   </para>

   <para>
    With the standard freezing policy, the <literal>age</> column will start
    at one billion for a freshly-vacuumed database.  When the <literal>age</>
    approaches two billion, the database must be vacuumed again to avoid
    risk of wraparound failures.  Recommended practice is to vacuum each
    database at least once every half-a-billion (500 million) transactions,
    so as to provide plenty of safety margin.  To help meet this rule,
    each database-wide <command>VACUUM</> automatically delivers a warning
    if there are any <filename>pg_database</> entries showing an
    <literal>age</> of more than 1.5 billion transactions, for example:
    <informalexample>
<programlisting>
play=# vacuum;
WARNING:  Some databases have not been vacuumed in 1613770184 transactions.
        Better vacuum them within 533713463 transactions,
        or you may have a wraparound failure.
VACUUM
</programlisting>
    </informalexample>
   </para>

   <para>
    <command>VACUUM</> with the <command>FREEZE</> option uses a more
    aggressive freezing policy: tuples are frozen if they are old enough
    to be considered good by all open transactions. In particular, if a
    <command>VACUUM FREEZE</> is performed in an otherwise-idle
    database, it is guaranteed that <emphasis>all</> tuples in that
    database will be frozen. Hence, as long as the database is not
    modified in any way, it will not need subsequent vacuuming to avoid
    transaction ID wraparound problems. This technique is used by
    <filename>initdb</> to prepare the <filename>template0</> database.
    It should also be used to prepare any user-created databases that
    are to be marked <literal>datallowconn</> = <literal>false</> in
    <filename>pg_database</>, since there isn't any convenient way to
    vacuum a database that you can't connect to. Note that
    <command>VACUUM</command>'s automatic warning message about
    unvacuumed databases will ignore <filename>pg_database</> entries
    with <literal>datallowconn</> = <literal>false</>, so as to avoid
    giving false warnings about these databases; therefore it's up to
    you to ensure that such databases are frozen correctly.
   </para>

  </sect2>
 </sect1>


 <sect1 id="routine-reindex">
  <title>Routine Reindexing</title>

  <indexterm zone="routine-reindex">
   <primary>reindex</primary>
  </indexterm>

  <para>
   <productname>PostgreSQL</productname> is unable to reuse btree index
   pages in certain cases. The problem is that if indexed rows are
   deleted, those index pages can only be reused by rows with similar
   values. For example, if indexed rows are deleted and newly
   inserted/updated rows have much higher values, the new rows can't use
   the index space made available by the deleted rows. Instead, such
   new rows must be placed on new index pages. In such cases, disk
   space used by the index will grow indefinately, even if
   <command>VACUUM</> is run frequently.
  </para>
  <para>
   As a solution, you can use the <command>REINDEX</> command
   periodically to discard pages used by deleted rows. There is also
   <filename>contrib/reindexdb</> which can reindex an entire database.
  </para>
 </sect1>


 <sect1 id="logfile-maintenance">
  <title>Log File Maintenance</title>

  <indexterm zone="logfile-maintenance">
   <primary>log files</primary>
  </indexterm>

  <para>
   It's a good idea to save the database server's log output somewhere,
   rather than just routing it to <filename>/dev/null</>.  The log output
   is invaluable when it comes time to diagnose problems.  However, the
   log output tends to be voluminous (especially at higher debug levels)
   and you won't want to save it indefinitely.  You need to <quote>rotate</>
   the log files so that new log files are started and old ones thrown
   away every so often.
  </para>

  <para>
   If you simply direct the postmaster's <systemitem>stderr</> into a
   file, the only way to truncate the log file is to stop and restart
   the postmaster. This may be OK for development setups but you won't
   want to run a production server that way.
  </para>

  <para>
   The simplest production-grade approach to managing log output is to
   send it all to <application>syslog</> and let
   <application>syslog</> deal with file rotation. To do this, set
   <literal>syslog</> to 2 (log to syslog only) in
   <filename>postgresql.conf</>. Then you can send a
   <literal>SIGHUP</literal> signal to the <application>syslog</>
   daemon whenever you want to force it to start writing a new log
   file.
  </para>

  <para>
   On many systems, however, syslog is not very reliable, particularly
   with large log messages; it may truncate or drop messages just when
   you need them the most. You may find it more useful to pipe the
   <application>postmaster</>'s <systemitem>stderr</> to some type of
   log rotation script. If you start the postmaster with
   <application>pg_ctl</>, then the postmaster's <systemitem>stderr</>
   is already redirected to <systemitem>stdout</>, so you just need a
   pipe command:
   
<screen>
<userinput>pg_ctl start | logrotate</userinput>
</screen>

   The <productname>PostgreSQL</> distribution doesn't include a suitable
   log rotation program, but there are many available on the net;
   one is included in the Apache distribution, for example.
  </para>
 </sect1>
</chapter>

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