Repair memory leaks in plpython.

[pgsql.git] / doc / src / sgml / maintenance.sgml

<!-- doc/src/sgml/maintenance.sgml -->

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

 <indexterm zone="maintenance">
  <primary>maintenance</primary>
 </indexterm>

 <indexterm zone="maintenance">
  <primary>routine maintenance</primary>
 </indexterm>

  <para>
   <productname>PostgreSQL</productname>, like any database software, requires that certain tasks
   be performed regularly to achieve optimum performance. The tasks
   discussed here are <emphasis>required</emphasis>, but they
   are repetitive in nature and can easily be automated using standard
   tools such as <application>cron</application> scripts or
   Windows' <application>Task Scheduler</application>.  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 the 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</quote>
   of the database.  This activity is discussed in
   <xref linkend="routine-vacuuming"/>.  Closely related to this is updating
   the statistics that will be used by the query planner, as discussed in
   <xref linkend="vacuum-for-statistics"/>.
  </para>

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

  <para>
   <ulink
   url="https://bucardo.org/check_postgres/"><application>check_postgres</application></ulink>
   is available for monitoring database health and reporting unusual
   conditions.  <application>check_postgres</application> integrates with
   Nagios and MRTG, but can be run standalone too.
  </para>

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

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

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

  <para>
   <productname>PostgreSQL</productname> databases require periodic
   maintenance known as <firstterm>vacuuming</firstterm>.  For many installations, it
   is sufficient to let vacuuming be performed by the <firstterm>autovacuum
   daemon</firstterm>, which is described in <xref linkend="autovacuum"/>.  You might
   need to adjust the autovacuuming parameters described there to obtain best
   results for your situation.  Some database administrators will want to
   supplement or replace the daemon's activities with manually-managed
   <command>VACUUM</command> commands, which typically are executed according to a
   schedule by <application>cron</application> or <application>Task
   Scheduler</application> scripts.  To set up manually-managed vacuuming properly,
   it is essential to understand the issues discussed in the next few
   subsections.  Administrators who rely on autovacuuming may still wish
   to skim this material to help them understand and adjust autovacuuming.
  </para>

  <sect2 id="vacuum-basics">
   <title>Vacuuming Basics</title>

   <para>
    <productname>PostgreSQL</productname>'s
    <link linkend="sql-vacuum"><command>VACUUM</command></link> command has to
    process each table on a regular basis for several reasons:

    <orderedlist>
     <listitem>
      <simpara>To recover or reuse 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 update the visibility map, which speeds
      up <link linkend="indexes-index-only-scans">index-only
      scans</link>.</simpara>
     </listitem>

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

    Each of these reasons dictates performing <command>VACUUM</command> operations
    of varying frequency and scope, as explained in the following subsections.
   </para>

   <para>
    There are two variants of <command>VACUUM</command>: standard <command>VACUUM</command>
    and <command>VACUUM FULL</command>.  <command>VACUUM FULL</command> can reclaim more
    disk space but runs much more slowly.  Also,
    the standard form of <command>VACUUM</command> can run in parallel with production
    database operations.  (Commands such as <command>SELECT</command>,
    <command>INSERT</command>, <command>UPDATE</command>, and
    <command>DELETE</command> will continue to function normally, though you
    will not be able to modify the definition of a table with commands such as
    <command>ALTER TABLE</command> while it is being vacuumed.)
    <command>VACUUM FULL</command> requires an
    <literal>ACCESS EXCLUSIVE</literal> lock on the table it is
    working on, and therefore cannot be done in parallel with other use
    of the table.  Generally, therefore,
    administrators should strive to use standard <command>VACUUM</command> and
    avoid <command>VACUUM FULL</command>.
   </para>

   <para>
    <command>VACUUM</command> creates a substantial amount of I/O
    traffic, which can cause poor performance for other active sessions.
    There are configuration parameters that can be adjusted to reduce the
    performance impact of background vacuuming &mdash; see
    <xref linkend="runtime-config-resource-vacuum-cost"/>.
   </para>
  </sect2>

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

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

   <para>
    In <productname>PostgreSQL</productname>, an
    <command>UPDATE</command> or <command>DELETE</command> of a row does not
    immediately remove the old version of the row.
    This approach is necessary to gain the benefits of multiversion
    concurrency control (<acronym>MVCC</acronym>, see <xref linkend="mvcc"/>): the row version
    must not be deleted while it is still potentially visible to other
    transactions. But eventually, an outdated or deleted row version is no
    longer of interest to any transaction. The space it occupies must then be
    reclaimed for reuse by new rows, to avoid unbounded growth of disk
    space requirements. This is done by running <command>VACUUM</command>.
   </para>

   <para>
    The standard form of <command>VACUUM</command> removes dead row
    versions in tables and indexes and marks the space available for
    future reuse.  However, it will not return the space to the operating
    system, except in the special case where one or more pages at the
    end of a table become entirely free and an exclusive table lock can be
    easily obtained.  In contrast, <command>VACUUM FULL</command> actively compacts
    tables by writing a complete new version of the table file with no dead
    space.  This minimizes the size of the table, but can take a long time.
    It also requires extra disk space for the new copy of the table, until
    the operation completes.
   </para>

   <para>
    The usual goal of routine vacuuming is to do standard <command>VACUUM</command>s
    often enough to avoid needing <command>VACUUM FULL</command>.  The
    autovacuum daemon attempts to work this way, and in fact will
    never issue <command>VACUUM FULL</command>.  In this approach, the idea
    is not to keep tables at their minimum size, but to maintain steady-state
    usage of disk space: each table occupies space equivalent to its
    minimum size plus however much space gets used up between vacuum runs.
    Although <command>VACUUM FULL</command> can be used to shrink a table back
    to its minimum size and return the disk space to the operating system,
    there is not much point in this if the table will just grow again in the
    future.  Thus, moderately-frequent standard <command>VACUUM</command> runs are a
    better approach than infrequent <command>VACUUM FULL</command> runs for
    maintaining heavily-updated tables.
   </para>

   <para>
    Some administrators prefer to schedule vacuuming themselves, for example
    doing all the work at night when load is low.
    The difficulty with doing vacuuming according to a fixed schedule
    is that if a table has an unexpected spike in update activity, it may
    get bloated to the point that <command>VACUUM FULL</command> is really necessary
    to reclaim space.  Using the autovacuum daemon alleviates this problem,
    since the daemon schedules vacuuming dynamically in response to update
    activity.  It is unwise to disable the daemon completely unless you
    have an extremely predictable workload.  One possible compromise is
    to set the daemon's parameters so that it will only react to unusually
    heavy update activity, thus keeping things from getting out of hand,
    while scheduled <command>VACUUM</command>s are expected to do the bulk of the
    work when the load is typical.
   </para>

   <para>
    For those not using autovacuum, a typical approach is to schedule a
    database-wide <command>VACUUM</command> once a day during a low-usage period,
    supplemented by more frequent vacuuming of heavily-updated tables as
    necessary. (Some installations with extremely high update rates vacuum
    their busiest tables as often as once every few minutes.) If you have
    multiple databases in a cluster, don't forget to
    <command>VACUUM</command> each one; the program <xref
    linkend="app-vacuumdb"/> might be helpful.
   </para>

   <tip>
   <para>
    Plain <command>VACUUM</command> may not be satisfactory when
    a table contains large numbers of dead row versions as a result of
    massive update or delete activity.  If you have such a table and
    you need to reclaim the excess disk space it occupies, you will need
    to use <command>VACUUM FULL</command>, or alternatively
    <link linkend="sql-cluster"><command>CLUSTER</command></link>
    or one of the table-rewriting variants of
    <link linkend="sql-altertable"><command>ALTER TABLE</command></link>.
    These commands rewrite an entire new copy of the table and build
    new indexes for it.  All these options require an
    <literal>ACCESS EXCLUSIVE</literal> lock.  Note that
    they also temporarily use extra disk space approximately equal to the size
    of the table, since the old copies of the table and indexes can't be
    released until the new ones are complete.
   </para>
   </tip>

   <tip>
   <para>
    If you have a table whose entire contents are deleted on a periodic
    basis, consider doing it with
    <link linkend="sql-truncate"><command>TRUNCATE</command></link> rather
    than using <command>DELETE</command> followed by
    <command>VACUUM</command>. <command>TRUNCATE</command> removes the
    entire content of the table immediately, without requiring a
    subsequent <command>VACUUM</command> or <command>VACUUM
    FULL</command> to reclaim the now-unused disk space.
    The disadvantage is that strict MVCC semantics are violated.
   </para>
   </tip>
  </sect2>

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

   <indexterm zone="vacuum-for-statistics">
    <primary>statistics</primary>
    <secondary>of the planner</secondary>
   </indexterm>

   <indexterm zone="vacuum-for-statistics">
    <primary>ANALYZE</primary>
   </indexterm>

   <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 <link linkend="sql-analyze"><command>ANALYZE</command></link> command,
    which can be invoked by itself or
    as an optional step in <command>VACUUM</command>.  It is important to have
    reasonably accurate statistics, otherwise poor choices of plans might
    degrade database performance.
   </para>

   <para>
    The autovacuum daemon, if enabled, will automatically issue
    <command>ANALYZE</command> commands whenever the content of a table has
    changed sufficiently.  However, administrators might prefer to rely
    on manually-scheduled <command>ANALYZE</command> operations, particularly
    if it is known that update activity on a table will not affect the
    statistics of <quote>interesting</quote> columns.  The daemon schedules
    <command>ANALYZE</command> strictly as a function of the number of rows
    inserted or updated; it has no knowledge of whether that will lead
    to meaningful statistical changes.
   </para>

   <para>
    Tuples changed in partitions and inheritance children do not trigger
    analyze on the parent table.  If the parent table is empty or rarely
    changed, it may never be processed by autovacuum, and the statistics for
    the inheritance tree as a whole won't be collected. It is necessary to
    run <command>ANALYZE</command> on the parent table manually in order to
    keep the statistics up to date.
   </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 might 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 might 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</command> 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, it is usually best to just analyze the entire
    database, because it is a fast operation.  <command>ANALYZE</command> uses a
    statistically random sampling of the rows of a table rather than reading
    every single row.
   </para>

   <tip>
    <para>
     Although per-column tweaking of <command>ANALYZE</command> frequency might not be
     very productive, you might find it worthwhile to do per-column
     adjustment of the level of detail of the statistics collected by
     <command>ANALYZE</command>.  Columns that are heavily used in <literal>WHERE</literal>
     clauses and have highly irregular data distributions might require a
     finer-grain data histogram than other columns.  See <command>ALTER TABLE
     SET STATISTICS</command>, or change the database-wide default using the <xref
     linkend="guc-default-statistics-target"/> configuration parameter.
    </para>

    <para>
     Also, by default there is limited information available about
     the selectivity of functions.  However, if you create a statistics
     object or an expression
     index that uses a function call, useful statistics will be
     gathered about the function, which can greatly improve query
     plans that use the expression index.
    </para>
   </tip>

   <tip>
    <para>
     The autovacuum daemon does not issue <command>ANALYZE</command> commands for
     foreign tables, since it has no means of determining how often that
     might be useful.  If your queries require statistics on foreign tables
     for proper planning, it's a good idea to run manually-managed
     <command>ANALYZE</command> commands on those tables on a suitable schedule.
    </para>
   </tip>

   <tip>
    <para>
     The autovacuum daemon does not issue <command>ANALYZE</command> commands
     for partitioned tables.  Inheritance parents will only be analyzed if the
     parent itself is changed - changes to child tables do not trigger
     autoanalyze on the parent table.  If your queries require statistics on
     parent tables for proper planning, it is necessary to periodically run
     a manual <command>ANALYZE</command> on those tables to keep the statistics
     up to date.
    </para>
   </tip>

  </sect2>

  <sect2 id="vacuum-for-visibility-map">
   <title>Updating the Visibility Map</title>

   <para>
    Vacuum maintains a <link linkend="storage-vm">visibility map</link> for each
    table to keep track of which pages contain only tuples that are known to be
    visible to all active transactions (and all future transactions, until the
    page is again modified).  This has two purposes.  First, vacuum
    itself can skip such pages on the next run, since there is nothing to
    clean up.
   </para>

   <para>
    Second, it allows <productname>PostgreSQL</productname> to answer some
    queries using only the index, without reference to the underlying table.
    Since <productname>PostgreSQL</productname> indexes don't contain tuple
    visibility information, a normal index scan fetches the heap tuple for each
    matching index entry, to check whether it should be seen by the current
    transaction.
    An <link linkend="indexes-index-only-scans"><firstterm>index-only
    scan</firstterm></link>, on the other hand, checks the visibility map first.
    If it's known that all tuples on the page are
    visible, the heap fetch can be skipped.  This is most useful on
    large data sets where the visibility map can prevent disk accesses.
    The visibility map is vastly smaller than the heap, so it can easily be
    cached even when the heap is very large.
   </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>

    <indexterm>
     <primary>wraparound</primary>
     <secondary>of transaction IDs</secondary>
    </indexterm>

   <para>
    <productname>PostgreSQL</productname>'s
    <link linkend="mvcc-intro">MVCC</link> transaction semantics
    depend on being able to compare transaction ID (<acronym>XID</acronym>)
    numbers: a row version with an insertion XID greater than the current
    transaction's XID is <quote>in the future</quote> and should not be visible
    to the current transaction.  But since transaction IDs have limited size
    (32 bits) a cluster that runs for a long time (more
    than 4 billion transactions) would suffer <firstterm>transaction ID
    wraparound</firstterm>: the XID counter wraps around to zero, and all of a sudden
    transactions that were in the past appear to be in the future &mdash; which
    means their output become invisible.  In short, catastrophic data loss.
    (Actually the data is still there, but that's cold comfort if you cannot
    get at it.)  To avoid this, it is necessary to vacuum every table
    in every database at least once every two billion transactions.
   </para>

   <para>
    The reason that periodic vacuuming solves the problem is that
    <command>VACUUM</command> will mark rows as <emphasis>frozen</emphasis>, indicating that
    they were inserted by a transaction that committed sufficiently far in
    the past that the effects of the inserting transaction are certain to be
    visible to all current and future transactions.
    Normal XIDs are
    compared using modulo-2<superscript>32</superscript> arithmetic. This means
    that for every normal XID, there are two billion XIDs that are
    <quote>older</quote> and two billion that are <quote>newer</quote>; another
    way to say it is that the normal XID space is circular with no
    endpoint. Therefore, once a row version has been created with a particular
    normal XID, the row version will appear to be <quote>in the past</quote> for
    the next two billion transactions, no matter which normal XID we are
    talking about. If the row version still exists after more than two billion
    transactions, it will suddenly appear to be in the future. To
    prevent this, <productname>PostgreSQL</productname> reserves a special XID,
    <literal>FrozenTransactionId</literal>, which does not follow the normal XID
    comparison rules and is always considered older
    than every normal XID.
    Frozen row versions are treated as if the inserting XID were
    <literal>FrozenTransactionId</literal>, so that they will appear to be
    <quote>in the past</quote> to all normal transactions regardless of wraparound
    issues, and so such row versions will be valid until deleted, no matter
    how long that is.
   </para>

   <note>
    <para>
     In <productname>PostgreSQL</productname> versions before 9.4, freezing was
     implemented by actually replacing a row's insertion XID
     with <literal>FrozenTransactionId</literal>, which was visible in the
     row's <structname>xmin</structname> system column.  Newer versions just set a flag
     bit, preserving the row's original <structname>xmin</structname> for possible
     forensic use.  However, rows with <structname>xmin</structname> equal
     to <literal>FrozenTransactionId</literal> (2) may still be found
     in databases <application>pg_upgrade</application>'d from pre-9.4 versions.
    </para>
    <para>
     Also, system catalogs may contain rows with <structname>xmin</structname> equal
     to <literal>BootstrapTransactionId</literal> (1), indicating that they were
     inserted during the first phase of <application>initdb</application>.
     Like <literal>FrozenTransactionId</literal>, this special XID is treated as
     older than every normal XID.
    </para>
   </note>

   <para>
    <xref linkend="guc-vacuum-freeze-min-age"/>
    controls how old an XID value has to be before rows bearing that XID will be
    frozen.  Increasing this setting may avoid unnecessary work if the
    rows that would otherwise be frozen will soon be modified again,
    but decreasing this setting increases
    the number of transactions that can elapse before the table must be
    vacuumed again.
   </para>

   <para>
    <command>VACUUM</command> uses the <link linkend="storage-vm">visibility map</link>
    to determine which pages of a table must be scanned.  Normally, it
    will skip pages that don't have any dead row versions even if those pages
    might still have row versions with old XID values.  Therefore, normal
    <command>VACUUM</command>s won't always freeze every old row version in the table.
    When that happens, <command>VACUUM</command> will eventually need to perform an
    <firstterm>aggressive vacuum</firstterm>, which will freeze all eligible unfrozen
    XID and MXID values, including those from all-visible but not all-frozen pages.
    In practice most tables require periodic aggressive vacuuming.
    <xref linkend="guc-vacuum-freeze-table-age"/>
    controls when <command>VACUUM</command> does that: all-visible but not all-frozen
    pages are scanned if the number of transactions that have passed since the
    last such scan is greater than <varname>vacuum_freeze_table_age</varname> minus
    <varname>vacuum_freeze_min_age</varname>. Setting
    <varname>vacuum_freeze_table_age</varname> to 0 forces <command>VACUUM</command> to
    always use its aggressive strategy.
   </para>

   <para>
    The maximum time that a table can go unvacuumed is two billion
    transactions minus the <varname>vacuum_freeze_min_age</varname> value at
    the time of the last aggressive vacuum. If it were to go
    unvacuumed for longer than
    that, data loss could result.  To ensure that this does not happen,
    autovacuum is invoked on any table that might contain unfrozen rows with
    XIDs older than the age specified by the configuration parameter <xref
    linkend="guc-autovacuum-freeze-max-age"/>.  (This will happen even if
    autovacuum is disabled.)
   </para>

   <para>
    This implies that if a table is not otherwise vacuumed,
    autovacuum will be invoked on it approximately once every
    <varname>autovacuum_freeze_max_age</varname> minus
    <varname>vacuum_freeze_min_age</varname> transactions.
    For tables that are regularly vacuumed for space reclamation purposes,
    this is of little importance.  However, for static tables
    (including tables that receive inserts, but no updates or deletes),
    there is no need to vacuum for space reclamation, so it can
    be useful to try to maximize the interval between forced autovacuums
    on very large static tables.  Obviously one can do this either by
    increasing <varname>autovacuum_freeze_max_age</varname> or decreasing
    <varname>vacuum_freeze_min_age</varname>.
   </para>

   <para>
    The effective maximum for <varname>vacuum_freeze_table_age</varname> is 0.95 *
    <varname>autovacuum_freeze_max_age</varname>; a setting higher than that will be
    capped to the maximum. A value higher than
    <varname>autovacuum_freeze_max_age</varname> wouldn't make sense because an
    anti-wraparound autovacuum would be triggered at that point anyway, and
    the 0.95 multiplier leaves some breathing room to run a manual
    <command>VACUUM</command> before that happens.  As a rule of thumb,
    <command>vacuum_freeze_table_age</command> should be set to a value somewhat
    below <varname>autovacuum_freeze_max_age</varname>, leaving enough gap so that
    a regularly scheduled <command>VACUUM</command> or an autovacuum triggered by
    normal delete and update activity is run in that window.  Setting it too
    close could lead to anti-wraparound autovacuums, even though the table
    was recently vacuumed to reclaim space, whereas lower values lead to more
    frequent aggressive vacuuming.
   </para>

   <para>
    The sole disadvantage of increasing <varname>autovacuum_freeze_max_age</varname>
    (and <varname>vacuum_freeze_table_age</varname> along with it) is that
    the <filename>pg_xact</filename> and <filename>pg_commit_ts</filename>
    subdirectories of the database cluster will take more space, because it
    must store the commit status and (if <varname>track_commit_timestamp</varname> is
    enabled) timestamp of all transactions back to
    the <varname>autovacuum_freeze_max_age</varname> horizon.  The commit status uses
    two bits per transaction, so if
    <varname>autovacuum_freeze_max_age</varname> is set to its maximum allowed value
    of two billion, <filename>pg_xact</filename> can be expected to grow to about half
    a gigabyte and <filename>pg_commit_ts</filename> to about 20GB.  If this
    is trivial compared to your total database size,
    setting <varname>autovacuum_freeze_max_age</varname> to its maximum allowed value
    is recommended.  Otherwise, set it depending on what you are willing to
    allow for <filename>pg_xact</filename> and <filename>pg_commit_ts</filename> storage.
    (The default, 200 million transactions, translates to about 50MB
    of <filename>pg_xact</filename> storage and about 2GB of <filename>pg_commit_ts</filename>
    storage.)
   </para>

   <para>
    One disadvantage of decreasing <varname>vacuum_freeze_min_age</varname> is that
    it might cause <command>VACUUM</command> to do useless work: freezing a row
    version is a waste of time if the row is modified
    soon thereafter (causing it to acquire a new XID).  So the setting should
    be large enough that rows are not frozen until they are unlikely to change
    any more.
   </para>

   <para>
    To track the age of the oldest unfrozen XIDs in a database,
    <command>VACUUM</command> stores XID
    statistics in the system tables <structname>pg_class</structname> and
    <structname>pg_database</structname>.  In particular,
    the <structfield>relfrozenxid</structfield> column of a table's
    <structname>pg_class</structname> row contains the oldest remaining unfrozen
    XID at the end of the most recent <command>VACUUM</command> that successfully
    advanced <structfield>relfrozenxid</structfield> (typically the most recent
    aggressive VACUUM).  Similarly, the
    <structfield>datfrozenxid</structfield> column of a database's
    <structname>pg_database</structname> row is a lower bound on the unfrozen XIDs
    appearing in that database &mdash; it is just the minimum of the
    per-table <structfield>relfrozenxid</structfield> values within the database.
    A convenient way to
    examine this information is to execute queries such as:

<programlisting>
SELECT c.oid::regclass as table_name,
       greatest(age(c.relfrozenxid),age(t.relfrozenxid)) as age
FROM pg_class c
LEFT JOIN pg_class t ON c.reltoastrelid = t.oid
WHERE c.relkind IN ('r', 'm');

SELECT datname, age(datfrozenxid) FROM pg_database;
</programlisting>

    The <literal>age</literal> column measures the number of transactions from the
    cutoff XID to the current transaction's XID.
   </para>

   <tip>
    <para>
     When the <command>VACUUM</command> command's <literal>VERBOSE</literal>
     parameter is specified, <command>VACUUM</command> prints various
     statistics about the table.  This includes information about how
     <structfield>relfrozenxid</structfield> and
     <structfield>relminmxid</structfield> advanced, and the number of
     newly frozen pages.  The same details appear in the server log when
     autovacuum logging (controlled by <xref
      linkend="guc-log-autovacuum-min-duration"/>) reports on a
     <command>VACUUM</command> operation executed by autovacuum.
    </para>
   </tip>

   <para>
    <command>VACUUM</command> normally only scans pages that have been modified
    since the last vacuum, but <structfield>relfrozenxid</structfield> can only be
    advanced when every page of the table
    that might contain unfrozen XIDs is scanned.  This happens when
    <structfield>relfrozenxid</structfield> is more than
    <varname>vacuum_freeze_table_age</varname> transactions old, when
    <command>VACUUM</command>'s <literal>FREEZE</literal> option is used, or when all
    pages that are not already all-frozen happen to
    require vacuuming to remove dead row versions. When <command>VACUUM</command>
    scans every page in the table that is not already all-frozen, it should
    set <literal>age(relfrozenxid)</literal> to a value just a little more than the
    <varname>vacuum_freeze_min_age</varname> setting
    that was used (more by the number of transactions started since the
    <command>VACUUM</command> started).  <command>VACUUM</command>
    will set <structfield>relfrozenxid</structfield> to the oldest XID
    that remains in the table, so it's possible that the final value
    will be much more recent than strictly required.
    If no <structfield>relfrozenxid</structfield>-advancing
    <command>VACUUM</command> is issued on the table until
    <varname>autovacuum_freeze_max_age</varname> is reached, an autovacuum will soon
    be forced for the table.
   </para>

   <para>
    If for some reason autovacuum fails to clear old XIDs from a table, the
    system will begin to emit warning messages like this when the database's
    oldest XIDs reach forty million transactions from the wraparound point:

<programlisting>
WARNING:  database "mydb" must be vacuumed within 39985967 transactions
HINT:  To avoid XID assignment failures, execute a database-wide VACUUM in that database.
</programlisting>

    (A manual <command>VACUUM</command> should fix the problem, as suggested by the
    hint; but note that the <command>VACUUM</command> should be performed by a
    superuser, else it will fail to process system catalogs, which prevent it from
    being able to advance the database's <structfield>datfrozenxid</structfield>.)
    If these warnings are ignored, the system will refuse to assign new XIDs once
    there are fewer than three million transactions left until wraparound:

<programlisting>
ERROR:  database is not accepting commands that assign new XIDs to avoid wraparound data loss in database "mydb"
HINT:  Execute a database-wide VACUUM in that database.
</programlisting>

    In this condition any transactions already in progress can continue,
    but only read-only transactions can be started. Operations that
    modify database records or truncate relations will fail.
    The <command>VACUUM</command> command can still be run normally.
    Note that, contrary to what was sometimes recommended in earlier releases,
    it is not necessary or desirable to stop the postmaster or enter single
    user-mode in order to restore normal operation.
    Instead, follow these steps:

    <orderedlist>
     <listitem>
      <simpara>Resolve old prepared transactions. You can find these by checking
       <link linkend="view-pg-prepared-xacts">pg_prepared_xacts</link> for rows where
       <literal>age(transactionid)</literal> is large. Such transactions should be
       committed or rolled back.</simpara>
     </listitem>
     <listitem>
      <simpara>End long-running open transactions. You can find these by checking
       <link linkend="monitoring-pg-stat-activity-view">pg_stat_activity</link> for rows where
       <literal>age(backend_xid)</literal> or <literal>age(backend_xmin)</literal> is
       large. Such transactions should be committed or rolled back, or the session
       can be terminated using <literal>pg_terminate_backend</literal>.</simpara>
     </listitem>
     <listitem>
      <simpara>Drop any old replication slots. Use
       <link linkend="monitoring-pg-stat-replication-view">pg_stat_replication</link> to
       find slots where <literal>age(xmin)</literal> or <literal>age(catalog_xmin)</literal>
       is large. In many cases, such slots were created for replication to servers that no
       longer exist, or that have been down for a long time. If you drop a slot for a server
       that still exists and might still try to connect to that slot, that replica may
       need to be rebuilt.</simpara>
     </listitem>
     <listitem>
      <simpara>Execute <command>VACUUM</command> in the target database. A database-wide
       <literal>VACUUM</literal> is simplest; to reduce the time required, it as also possible
       to issue manual <command>VACUUM</command> commands on the tables where
       <structfield>relminxid</structfield> is oldest. Do not use <literal>VACUUM FULL</literal>
       in this scenario, because it requires an XID and will therefore fail, except in super-user
       mode, where it will instead consume an XID and thus increase the risk of transaction ID
       wraparound. Do not use <literal>VACUUM FREEZE</literal> either, because it will do
       more than the minimum amount of work required to restore normal operation.</simpara>
     </listitem>
     <listitem>
      <simpara>Once normal operation is restored, ensure that autovacuum is properly configured
       in the target database in order to avoid future problems.</simpara>
     </listitem>
    </orderedlist>
   </para>

   <note>
    <para>
     In earlier versions, it was sometimes necessary to stop the postmaster and
     <command>VACUUM</command> the database in a single-user mode. In typical scenarios, this
     is no longer necessary, and should be avoided whenever possible, since it involves taking
     the system down. It is also riskier, since it disables transaction ID wraparound safeguards
     that are designed to prevent data loss.  The only reason to use single-user mode in this
     scenario is if you wish to <command>TRUNCATE</command> or <command>DROP</command> unneeded
     tables to avoid needing to <command>VACUUM</command> them.  The three-million-transaction
     safety margin exists to let the administrator do this. See the
     <xref linkend="app-postgres"/> reference page for details about using single-user mode.
    </para>
   </note>

   <sect3 id="vacuum-for-multixact-wraparound">
    <title>Multixacts and Wraparound</title>

    <indexterm>
     <primary>MultiXactId</primary>
    </indexterm>

    <indexterm>
     <primary>wraparound</primary>
     <secondary>of multixact IDs</secondary>
    </indexterm>

    <para>
     <firstterm>Multixact IDs</firstterm> are used to support row locking by
     multiple transactions.  Since there is only limited space in a tuple
     header to store lock information, that information is encoded as
     a <quote>multiple transaction ID</quote>, or multixact ID for short,
     whenever there is more than one transaction concurrently locking a
     row.  Information about which transaction IDs are included in any
     particular multixact ID is stored separately in
     the <filename>pg_multixact</filename> subdirectory, and only the multixact ID
     appears in the <structfield>xmax</structfield> field in the tuple header.
     Like transaction IDs, multixact IDs are implemented as a
     32-bit counter and corresponding storage, all of which requires
     careful aging management, storage cleanup, and wraparound handling.
     There is a separate storage area which holds the list of members in
     each multixact, which also uses a 32-bit counter and which must also
     be managed.
    </para>

    <para>
     Whenever <command>VACUUM</command> scans any part of a table, it will replace
     any multixact ID it encounters which is older than
     <xref linkend="guc-vacuum-multixact-freeze-min-age"/>
     by a different value, which can be the zero value, a single
     transaction ID, or a newer multixact ID.  For each table,
     <structname>pg_class</structname>.<structfield>relminmxid</structfield> stores the oldest
     possible multixact ID still appearing in any tuple of that table.
     If this value is older than
     <xref linkend="guc-vacuum-multixact-freeze-table-age"/>, an aggressive
     vacuum is forced.  As discussed in the previous section, an aggressive
     vacuum means that only those pages which are known to be all-frozen will
     be skipped.  <function>mxid_age()</function> can be used on
     <structname>pg_class</structname>.<structfield>relminmxid</structfield> to find its age.
    </para>

    <para>
     Aggressive <command>VACUUM</command>s, regardless of what causes
     them, are <emphasis>guaranteed</emphasis> to be able to advance
     the table's <structfield>relminmxid</structfield>.
     Eventually, as all tables in all databases are scanned and their
     oldest multixact values are advanced, on-disk storage for older
     multixacts can be removed.
    </para>

    <para>
     As a safety device, an aggressive vacuum scan will
     occur for any table whose multixact-age is greater than <xref
     linkend="guc-autovacuum-multixact-freeze-max-age"/>.  Also, if the
     storage occupied by multixacts members exceeds 2GB, aggressive vacuum
     scans will occur more often for all tables, starting with those that
     have the oldest multixact-age.  Both of these kinds of aggressive
     scans will occur even if autovacuum is nominally disabled.
    </para>

    <para>
     Similar to the XID case, if autovacuum fails to clear old MXIDs from a table, the
     system will begin to emit warning messages when the database's oldest MXIDs reach forty
     million transactions from the wraparound point.  And, just as in the XID case, if these
     warnings are ignored, the system will refuse to generate new MXIDs once there are fewer
     than three million left until wraparound.
    </para>

    <para>
     Normal operation when MXIDs are exhausted can be restored in much the same way as
     when XIDs are exhausted. Follow the same steps in the previous section, but with the
     following differences:

    <orderedlist>
     <listitem>
      <simpara>Running transactions and prepared transactions can be ignored if there
       is no chance that they might appear in a multixact.</simpara>
     </listitem>
     <listitem>
      <simpara>MXID information is not directly visible in system views such as
       <literal>pg_stat_activity</literal>; however, looking for old XIDs is still a good
       way of determining which transactions are causing MXID wraparound problems.</simpara>
     </listitem>
     <listitem>
      <simpara>XID exhaustion will block all write transactions, but MXID exhaustion will
       only block a subset of write transactions, specifically those that involve
       row locks that require an MXID.</simpara>
     </listitem>
    </orderedlist>
   </para>

   </sect3>
  </sect2>

  <sect2 id="autovacuum">
   <title>The Autovacuum Daemon</title>

   <indexterm>
    <primary>autovacuum</primary>
    <secondary>general information</secondary>
   </indexterm>
   <para>
    <productname>PostgreSQL</productname> has an optional but highly
    recommended feature called <firstterm>autovacuum</firstterm>,
    whose purpose is to automate the execution of
    <command>VACUUM</command> and <command>ANALYZE</command> commands.
    When enabled, autovacuum checks for
    tables that have had a large number of inserted, updated or deleted
    tuples.  These checks use the statistics collection facility;
    therefore, autovacuum cannot be used unless <xref
    linkend="guc-track-counts"/> is set to <literal>true</literal>.
    In the default configuration, autovacuuming is enabled and the related
    configuration parameters are appropriately set.
   </para>

   <para>
    The <quote>autovacuum daemon</quote> actually consists of multiple processes.
    There is a persistent daemon process, called the
    <firstterm>autovacuum launcher</firstterm>, which is in charge of starting
    <firstterm>autovacuum worker</firstterm> processes for all databases. The
    launcher will distribute the work across time, attempting to start one
    worker within each database every <xref linkend="guc-autovacuum-naptime"/>
    seconds.  (Therefore, if the installation has <replaceable>N</replaceable> databases,
    a new worker will be launched every
    <varname>autovacuum_naptime</varname>/<replaceable>N</replaceable> seconds.)
    A maximum of <xref linkend="guc-autovacuum-max-workers"/> worker processes
    are allowed to run at the same time. If there are more than
    <varname>autovacuum_max_workers</varname> databases to be processed,
    the next database will be processed as soon as the first worker finishes.
    Each worker process will check each table within its database and
    execute <command>VACUUM</command> and/or <command>ANALYZE</command> as needed.
    <xref linkend="guc-log-autovacuum-min-duration"/> can be set to monitor
    autovacuum workers' activity.
   </para>

   <para>
    If several large tables all become eligible for vacuuming in a short
    amount of time, all autovacuum workers might become occupied with
    vacuuming those tables for a long period.  This would result
    in other tables and databases not being vacuumed until a worker becomes
    available. There is no limit on how many workers might be in a
    single database, but workers do try to avoid repeating work that has
    already been done by other workers. Note that the number of running
    workers does not count towards <xref linkend="guc-max-connections"/> or
    <xref linkend="guc-superuser-reserved-connections"/> limits.
   </para>

   <para>
    Tables whose <structfield>relfrozenxid</structfield> value is more than
    <xref linkend="guc-autovacuum-freeze-max-age"/> transactions old are always
    vacuumed (this also applies to those tables whose freeze max age has
    been modified via storage parameters; see below).  Otherwise, if the
    number of tuples obsoleted since the last
    <command>VACUUM</command> exceeds the <quote>vacuum threshold</quote>, the
    table is vacuumed.  The vacuum threshold is defined as:
<programlisting>
vacuum threshold = vacuum base threshold + vacuum scale factor * number of tuples
</programlisting>
    where the vacuum base threshold is
    <xref linkend="guc-autovacuum-vacuum-threshold"/>,
    the vacuum scale factor is
    <xref linkend="guc-autovacuum-vacuum-scale-factor"/>,
    and the number of tuples is
    <structname>pg_class</structname>.<structfield>reltuples</structfield>.
   </para>

   <para>
    The table is also vacuumed if the number of tuples inserted since the last
    vacuum has exceeded the defined insert threshold, which is defined as:
<programlisting>
vacuum insert threshold = vacuum base insert threshold + vacuum insert scale factor * number of tuples
</programlisting>
    where the vacuum insert base threshold is
    <xref linkend="guc-autovacuum-vacuum-insert-threshold"/>,
    and vacuum insert scale factor is
    <xref linkend="guc-autovacuum-vacuum-insert-scale-factor"/>.
    Such vacuums may allow portions of the table to be marked as
    <firstterm>all visible</firstterm> and also allow tuples to be frozen, which
    can reduce the work required in subsequent vacuums.
    For tables which receive <command>INSERT</command> operations but no or
    almost no <command>UPDATE</command>/<command>DELETE</command> operations,
    it may be beneficial to lower the table's
    <xref linkend="reloption-autovacuum-freeze-min-age"/> as this may allow
    tuples to be frozen by earlier vacuums.  The number of obsolete tuples and
    the number of inserted tuples are obtained from the cumulative statistics system;
    it is an eventually-consistent count updated by each <command>UPDATE</command>,
    <command>DELETE</command> and <command>INSERT</command> operation.
    If the <structfield>relfrozenxid</structfield> value of the table
    is more than <varname>vacuum_freeze_table_age</varname> transactions old,
    an aggressive vacuum is performed to freeze old tuples and advance
    <structfield>relfrozenxid</structfield>; otherwise, only pages that have been modified
    since the last vacuum are scanned.
   </para>

   <para>
    For analyze, a similar condition is used: the threshold, defined as:
<programlisting>
analyze threshold = analyze base threshold + analyze scale factor * number of tuples
</programlisting>
    is compared to the total number of tuples inserted, updated, or deleted
    since the last <command>ANALYZE</command>.
   </para>

   <para>
    Partitioned tables do not directly store tuples and consequently
    are not processed by autovacuum.  (Autovacuum does process table
    partitions just like other tables.)  Unfortunately, this means that
    autovacuum does  not run <command>ANALYZE</command> on partitioned
    tables, and this can cause suboptimal plans for queries that reference
    partitioned table statistics.  You can work around this problem by
    manually running <command>ANALYZE</command> on partitioned tables
    when they are first populated, and again whenever the distribution
    of data in their partitions changes significantly.
   </para>

   <para>
    Temporary tables cannot be accessed by autovacuum.  Therefore,
    appropriate vacuum and analyze operations should be performed via
    session SQL commands.
   </para>

   <para>
    The default thresholds and scale factors are taken from
    <filename>postgresql.conf</filename>, but it is possible to override them
    (and many other autovacuum control parameters) on a per-table basis; see
    <xref linkend="sql-createtable-storage-parameters"/> for more information.
    If a setting has been changed via a table's storage parameters, that value
    is used when processing that table; otherwise the global settings are
    used. See <xref linkend="runtime-config-autovacuum"/> for more details on
    the global settings.
   </para>

   <para>
    When multiple workers are running, the autovacuum cost delay parameters
    (see <xref linkend="runtime-config-resource-vacuum-cost"/>) are
    <quote>balanced</quote> among all the running workers, so that the
    total I/O impact on the system is the same regardless of the number
    of workers actually running.  However, any workers processing tables whose
    per-table <literal>autovacuum_vacuum_cost_delay</literal> or
    <literal>autovacuum_vacuum_cost_limit</literal> storage parameters have been set
    are not considered in the balancing algorithm.
   </para>

   <para>
    Autovacuum workers generally don't block other commands.  If a process
    attempts to acquire a lock that conflicts with the
    <literal>SHARE UPDATE EXCLUSIVE</literal> lock held by autovacuum, lock
    acquisition will interrupt the autovacuum.  For conflicting lock modes,
    see <xref linkend="table-lock-compatibility"/>.  However, if the autovacuum
    is running to prevent transaction ID wraparound (i.e., the autovacuum query
    name in the <structname>pg_stat_activity</structname> view ends with
    <literal>(to prevent wraparound)</literal>), the autovacuum is not
    automatically interrupted.
   </para>

   <warning>
    <para>
     Regularly running commands that acquire locks conflicting with a
     <literal>SHARE UPDATE EXCLUSIVE</literal> lock (e.g., ANALYZE) can
     effectively prevent autovacuums from ever completing.
    </para>
   </warning>
  </sect2>
 </sect1>


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

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

  <para>
   In some situations it is worthwhile to rebuild indexes periodically
   with the <xref linkend="sql-reindex"/> command or a series of individual
   rebuilding steps.

  </para>

  <para>
   B-tree index pages that have become completely empty are reclaimed for
   re-use.  However, there is still a possibility
   of inefficient use of space: if all but a few index keys on a page have
   been deleted, the page remains allocated.  Therefore, a usage
   pattern in which most, but not all, keys in each range are eventually
   deleted will see poor use of space.  For such usage patterns,
   periodic reindexing is recommended.
  </para>

  <para>
   The potential for bloat in non-B-tree indexes has not been well
   researched.  It is a good idea to periodically monitor the index's physical
   size when using any non-B-tree index type.
  </para>

  <para>
   Also, for B-tree indexes, a freshly-constructed index is slightly faster to
   access than one that has been updated many times because logically
   adjacent pages are usually also physically adjacent in a newly built index.
   (This consideration does not apply to non-B-tree indexes.)  It
   might be worthwhile to reindex periodically just to improve access speed.
  </para>

  <para>
   <xref linkend="sql-reindex"/> can be used safely and easily in all cases.
   This command requires an <literal>ACCESS EXCLUSIVE</literal> lock by
   default, hence it is often preferable to execute it with its
   <literal>CONCURRENTLY</literal> option, which requires only a
   <literal>SHARE UPDATE EXCLUSIVE</literal> lock.
  </para>
 </sect1>


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

  <indexterm zone="logfile-maintenance">
   <primary>server log</primary>
   <secondary>log file maintenance</secondary>
  </indexterm>

  <para>
   It is a good idea to save the database server's log output
   somewhere, rather than just discarding it via <filename>/dev/null</filename>.
   The log output is invaluable when diagnosing
   problems.
  </para>

  <note>
   <para>
    The server log can contain sensitive information and needs to be protected,
    no matter how or where it is stored, or the destination to which it is routed.
    For example, some DDL statements might contain plaintext passwords or other
    authentication details. Logged statements at the <literal>ERROR</literal>
    level might show the SQL source code for applications
    and might also contain some parts of data rows. Recording data, events and
    related information is the intended function of this facility, so this is
    not a leakage or a bug. Please ensure the server logs are visible only to
    appropriately authorized people.
   </para>
  </note>

  <para>
   Log output tends to be voluminous
   (especially at higher debug levels) so you won't want to save it
   indefinitely.  You need to <emphasis>rotate</emphasis> the log files so that
   new log files are started and old ones removed after a reasonable
   period of time.
  </para>

  <para>
   If you simply direct the <systemitem>stderr</systemitem> of
   <command>postgres</command> into a
   file, you will have log output, but
   the only way to truncate the log file is to stop and restart
   the server. This might be acceptable if you are using
   <productname>PostgreSQL</productname> in a development environment,
   but few production servers would find this behavior acceptable.
  </para>

  <para>
   A better approach is to send the server's
   <systemitem>stderr</systemitem> output to some type of log rotation program.
   There is a built-in log rotation facility, which you can use by
   setting the configuration parameter <varname>logging_collector</varname> to
   <literal>true</literal> in <filename>postgresql.conf</filename>.  The control
   parameters for this program are described in <xref
   linkend="runtime-config-logging-where"/>. You can also use this approach
   to capture the log data in machine readable <acronym>CSV</acronym>
   (comma-separated values) format.
  </para>

  <para>
   Alternatively, you might prefer to use an external log rotation
   program if you have one that you are already using with other
   server software. For example, the <application>rotatelogs</application>
   tool included in the <productname>Apache</productname> distribution
   can be used with <productname>PostgreSQL</productname>.  One way to
   do this is to pipe the server's
   <systemitem>stderr</systemitem> output to the desired program.
   If you start the server with
   <command>pg_ctl</command>, then <systemitem>stderr</systemitem>
   is already redirected to <systemitem>stdout</systemitem>, so you just need a
   pipe command, for example:

<programlisting>
pg_ctl start | rotatelogs /var/log/pgsql_log 86400
</programlisting>
  </para>

  <para>
   You can combine these approaches by setting up <application>logrotate</application>
   to collect log files produced by <productname>PostgreSQL</productname> built-in
   logging collector.  In this case, the logging collector defines the names and
   location of the log files, while <application>logrotate</application>
   periodically archives these files.  When initiating log rotation,
   <application>logrotate</application> must ensure that the application
   sends further output to the new file.  This is commonly done with a
   <literal>postrotate</literal> script that sends a <literal>SIGHUP</literal>
   signal to the application, which then reopens the log file.
   In <productname>PostgreSQL</productname>, you can run <command>pg_ctl</command>
   with the <literal>logrotate</literal> option instead.  When the server receives
   this command, the server either switches to a new log file or reopens the
   existing file, depending on the logging configuration
   (see <xref linkend="runtime-config-logging-where"/>).
  </para>

  <note>
   <para>
    When using static log file names, the server might fail to reopen the log
    file if the max open file limit is reached or a file table overflow occurs.
    In this case, log messages are sent to the old log file until a
    successful log rotation. If <application>logrotate</application> is
    configured to compress the log file and delete it, the server may lose
    the messages logged in this time frame. To avoid this issue, you can
    configure the logging collector to dynamically assign log file names
    and use a <literal>prerotate</literal> script to ignore open log files.
    </para>
  </note>

  <para>
   Another production-grade approach to managing log output is to
   send it to <application>syslog</application> and let
   <application>syslog</application> deal with file rotation. To do this, set the
   configuration parameter <varname>log_destination</varname> to <literal>syslog</literal>
   (to log to <application>syslog</application> only) in
   <filename>postgresql.conf</filename>. Then you can send a <literal>SIGHUP</literal>
   signal to the <application>syslog</application> daemon whenever you want to force it
   to start writing a new log file.  If you want to automate log
   rotation, the <application>logrotate</application> program can be
   configured to work with log files from
   <application>syslog</application>.
  </para>

  <para>
   On many systems, however, <application>syslog</application> is not very reliable,
   particularly with large log messages; it might truncate or drop messages
   just when you need them the most.  Also, on <productname>Linux</productname>,
   <application>syslog</application> will flush each message to disk, yielding poor
   performance.  (You can use a <quote><literal>-</literal></quote> at the start of the file name
   in the <application>syslog</application> configuration file to disable syncing.)
  </para>

  <para>
   Note that all the solutions described above take care of starting new
   log files at configurable intervals, but they do not handle deletion
   of old, no-longer-useful log files.  You will probably want to set
   up a batch job to periodically delete old log files.  Another possibility
   is to configure the rotation program so that old log files are overwritten
   cyclically.
  </para>

  <para>
   <ulink url="https://pgbadger.darold.net/"><productname>pgBadger</productname></ulink>
   is an external project that does sophisticated log file analysis.
   <ulink
   url="https://bucardo.org/check_postgres/"><productname>check_postgres</productname></ulink>
   provides Nagios alerts when important messages appear in the log
   files, as well as detection of many other extraordinary conditions.
  </para>
 </sect1>
</chapter>