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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="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, make sure <productname>PostgreSQL</> was built with
the <option>--enable-syslog</> configure option, and 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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