Routine Database Maintenance Tasks {#maintenance}
==================================

maintenance

routine maintenance

PostgreSQL, like any database software, requires that certain tasks be
performed regularly to achieve optimum performance. The tasks discussed
here are *required*, but they are repetitive in nature and can easily be
automated using standard tools such as cron scripts or Windows\' Task
Scheduler. It is the database administrator\'s responsibility to set up
appropriate scripts, and to check that they execute successfully.

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
PostgreSQL are discussed at length in [???](#backup).

The other main category of maintenance task is periodic "vacuuming" of
the database. This activity is discussed in [Routine
Vacuuming](#routine-vacuuming). Closely related to this is updating the
statistics that will be used by the query planner, as discussed in
[Updating Planner Statistics](#vacuum-for-statistics).

Another task that might need periodic attention is log file management.
This is discussed in [Log File Maintenance](#logfile-maintenance).

[check\_postgres](https://bucardo.org/check_postgres/) is available for
monitoring database health and reporting unusual conditions.
check\_postgres integrates with Nagios and MRTG, but can be run
standalone too.

PostgreSQL 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.

Routine Vacuuming
=================

vacuum

PostgreSQL databases require periodic maintenance known as vacuuming.
For many installations, it is sufficient to let vacuuming be performed
by the autovacuum daemon, which is described in [The Autovacuum
Daemon](#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 `VACUUM` commands, which
typically are executed according to a schedule by cron or Task Scheduler
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.

Vacuuming Basics {#vacuum-basics}
----------------

PostgreSQL\'s [`VACUUM`](#sql-vacuum) command has to process each table
on a regular basis for several reasons:

1.  To recover or reuse disk space occupied by updated or deleted rows.

2.  To update data statistics used by the PostgreSQL query planner.

3.  To update the visibility map, which speeds up [index-only
    scans](#indexes-index-only-scans).

4.  To protect against loss of very old data due to transaction ID
    wraparound or multixact ID wraparound.

Each of these reasons dictates performing `VACUUM` operations of varying
frequency and scope, as explained in the following subsections.

There are two variants of `VACUUM`: standard `VACUUM` and `VACUUM FULL`.
`VACUUM FULL` can reclaim more disk space but runs much more slowly.
Also, the standard form of `VACUUM` can run in parallel with production
database operations. (Commands such as `SELECT`, `INSERT`, `UPDATE`, and
`DELETE` will continue to function normally, though you will not be able
to modify the definition of a table with commands such as `ALTER TABLE`
while it is being vacuumed.) `VACUUM FULL` requires an
`ACCESS EXCLUSIVE` 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 `VACUUM` and
avoid `VACUUM FULL`.

`VACUUM` 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
[???](#runtime-config-resource-vacuum-cost).

Recovering Disk Space {#vacuum-for-space-recovery}
---------------------

disk space

In PostgreSQL, an `UPDATE` or `DELETE` 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 (MVCC, see
[???](#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
`VACUUM`.

The standard form of `VACUUM` 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,
`VACUUM FULL` 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.

The usual goal of routine vacuuming is to do standard `VACUUM`s often
enough to avoid needing `VACUUM FULL`. The autovacuum daemon attempts to
work this way, and in fact will never issue `VACUUM FULL`. 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 `VACUUM FULL` 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 `VACUUM`
runs are a better approach than infrequent `VACUUM FULL` runs for
maintaining heavily-updated tables.

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 `VACUUM FULL` 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 `VACUUM`s are expected
to do the bulk of the work when the load is typical.

For those not using autovacuum, a typical approach is to schedule a
database-wide `VACUUM` 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 `VACUUM` each one; the
program [???](#app-vacuumdb) might be helpful.

> **Tip**
>
> Plain `VACUUM` 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 `VACUUM FULL`, or
> alternatively [`CLUSTER`](#sql-cluster) or one of the table-rewriting
> variants of [`ALTER TABLE`](#sql-altertable). These commands rewrite
> an entire new copy of the table and build new indexes for it. All
> these options require an `ACCESS EXCLUSIVE` 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.

> **Tip**
>
> If you have a table whose entire contents are deleted on a periodic
> basis, consider doing it with [`TRUNCATE`](#sql-truncate) rather than
> using `DELETE` followed by `VACUUM`. `TRUNCATE` removes the entire
> content of the table immediately, without requiring a subsequent
> `VACUUM` or `VACUUM
>     FULL` to reclaim the now-unused disk space. The disadvantage is
> that strict MVCC semantics are violated.

Updating Planner Statistics {#vacuum-for-statistics}
---------------------------

statistics

of the planner

ANALYZE

The PostgreSQL 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 [`ANALYZE`](#sql-analyze) command, which
can be invoked by itself or as an optional step in `VACUUM`. It is
important to have reasonably accurate statistics, otherwise poor choices
of plans might degrade database performance.

The autovacuum daemon, if enabled, will automatically issue `ANALYZE`
commands whenever the content of a table has changed sufficiently.
However, administrators might prefer to rely on manually-scheduled
`ANALYZE` operations, particularly if it is known that update activity
on a table will not affect the statistics of "interesting" columns. The
daemon schedules `ANALYZE` 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.

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 `ANALYZE` on the parent table manually in order to keep the
statistics up to date.

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
`timestamp` 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.

It is possible to run `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, it is usually best to just analyze the entire
database, because it is a fast operation. `ANALYZE` uses a statistically
random sampling of the rows of a table rather than reading every single
row.

> **Tip**
>
> Although per-column tweaking of `ANALYZE` 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 `ANALYZE`.
> Columns that are heavily used in `WHERE` clauses and have highly
> irregular data distributions might require a finer-grain data
> histogram than other columns. See `ALTER TABLE
>      SET STATISTICS`, or change the database-wide default using the
> [???](#guc-default-statistics-target) configuration parameter.
>
> 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.

> **Tip**
>
> The autovacuum daemon does not issue `ANALYZE` 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 `ANALYZE`
> commands on those tables on a suitable schedule.

> **Tip**
>
> The autovacuum daemon does not issue `ANALYZE` 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 `ANALYZE` on those tables to keep the statistics up to date.

Updating the Visibility Map {#vacuum-for-visibility-map}
---------------------------

Vacuum maintains a [visibility map](#storage-vm) 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.

Second, it allows PostgreSQL to answer some queries using only the
index, without reference to the underlying table. Since PostgreSQL
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 [index-only
scan](#indexes-index-only-scans), 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.

Preventing Transaction ID Wraparound Failures {#vacuum-for-wraparound}
---------------------------------------------

transaction ID

wraparound

wraparound

of transaction IDs

PostgreSQL\'s [MVCC](#mvcc-intro) transaction semantics depend on being
able to compare transaction ID (XID) numbers: a row version with an
insertion XID greater than the current transaction\'s XID is "in the
future" 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 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 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.

The reason that periodic vacuuming solves the problem is that `VACUUM`
will mark rows as *frozen*, 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-2^32^
arithmetic. This means that for every normal XID, there are two billion
XIDs that are "older" and two billion that are "newer"; 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 "in the past" 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, PostgreSQL reserves a special XID, `FrozenTransactionId`, 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 `FrozenTransactionId`, so that they will appear to be
"in the past" to all normal transactions regardless of wraparound
issues, and so such row versions will be valid until deleted, no matter
how long that is.

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

[???](#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.

`VACUUM` uses the [visibility map](#storage-vm) 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 `VACUUM`s won\'t always
freeze every old row version in the table. When that happens, `VACUUM`
will eventually need to perform an aggressive vacuum, 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. [???](#guc-vacuum-freeze-table-age)
controls when `VACUUM` 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 `vacuum_freeze_table_age` minus
`vacuum_freeze_min_age`. Setting `vacuum_freeze_table_age` to 0 forces
`VACUUM` to always use its aggressive strategy.

The maximum time that a table can go unvacuumed is two billion
transactions minus the `vacuum_freeze_min_age` 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
[???](#guc-autovacuum-freeze-max-age). (This will happen even if
autovacuum is disabled.)

This implies that if a table is not otherwise vacuumed, autovacuum will
be invoked on it approximately once every `autovacuum_freeze_max_age`
minus `vacuum_freeze_min_age` 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 `autovacuum_freeze_max_age` or
decreasing `vacuum_freeze_min_age`.

The effective maximum for `vacuum_freeze_table_age` is 0.95 \*
`autovacuum_freeze_max_age`; a setting higher than that will be capped
to the maximum. A value higher than `autovacuum_freeze_max_age`
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 `VACUUM` before that happens. As a rule
of thumb, `vacuum_freeze_table_age` should be set to a value somewhat
below `autovacuum_freeze_max_age`, leaving enough gap so that a
regularly scheduled `VACUUM` 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.

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

One disadvantage of decreasing `vacuum_freeze_min_age` is that it might
cause `VACUUM` 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.

To track the age of the oldest unfrozen XIDs in a database, `VACUUM`
stores XID statistics in the system tables pg\_class and pg\_database.
In particular, the relfrozenxid column of a table\'s pg\_class row
contains the oldest remaining unfrozen XID at the end of the most recent
`VACUUM` that successfully advanced relfrozenxid (typically the most
recent aggressive VACUUM). Similarly, the datfrozenxid column of a
database\'s pg\_database row is a lower bound on the unfrozen XIDs
appearing in that database MDASH it is just the minimum of the per-table
relfrozenxid values within the database. A convenient way to examine
this information is to execute queries such as:

    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;

The `age` column measures the number of transactions from the cutoff XID
to the current transaction\'s XID.

> **Tip**
>
> When the `VACUUM` command\'s `VERBOSE` parameter is specified,
> `VACUUM` prints various statistics about the table. This includes
> information about how relfrozenxid and relminmxid advanced. The same
> details appear in the server log when autovacuum logging (controlled
> by [???](#guc-log-autovacuum-min-duration)) reports on a `VACUUM`
> operation executed by autovacuum.

`VACUUM` normally only scans pages that have been modified since the
last vacuum, but relfrozenxid can only be advanced when every page of
the table that might contain unfrozen XIDs is scanned. This happens when
relfrozenxid is more than `vacuum_freeze_table_age` transactions old,
when `VACUUM`\'s `FREEZE` option is used, or when all pages that are not
already all-frozen happen to require vacuuming to remove dead row
versions. When `VACUUM` scans every page in the table that is not
already all-frozen, it should set `age(relfrozenxid)` to a value just a
little more than the `vacuum_freeze_min_age` setting that was used (more
by the number of transactions started since the `VACUUM` started).
`VACUUM` will set relfrozenxid 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 relfrozenxid-advancing `VACUUM` is issued
on the table until `autovacuum_freeze_max_age` is reached, an autovacuum
will soon be forced for the table.

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:

    WARNING:  database "mydb" must be vacuumed within 39985967 transactions
    HINT:  To avoid a database shutdown, execute a database-wide VACUUM in that database.

(A manual `VACUUM` should fix the problem, as suggested by the hint; but
note that the `VACUUM` must be performed by a superuser, else it will
fail to process system catalogs and thus not be able to advance the
database\'s datfrozenxid.) If these warnings are ignored, the system
will shut down and refuse to start any new transactions once there are
fewer than three million transactions left until wraparound:

    ERROR:  database is not accepting commands to avoid wraparound data loss in database "mydb"
    HINT:  Stop the postmaster and vacuum that database in single-user mode.

The three-million-transaction safety margin exists to let the
administrator recover without data loss, by manually executing the
required `VACUUM` commands. However, since the system will not execute
commands once it has gone into the safety shutdown mode, the only way to
do this is to stop the server and start the server in single-user mode
to execute `VACUUM`. The shutdown mode is not enforced in single-user
mode. See the [???](#app-postgres) reference page for details about
using single-user mode.

### Multixacts and Wraparound {#vacuum-for-multixact-wraparound}

MultiXactId

wraparound

of multixact IDs

Multixact IDs 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 "multiple transaction ID",
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
`pg_multixact` subdirectory, and only the multixact ID appears in the
xmax 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.

Whenever `VACUUM` scans any part of a table, it will replace any
multixact ID it encounters which is older than
[???](#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, pg\_class.relminmxid stores the oldest possible
multixact ID still appearing in any tuple of that table. If this value
is older than [???](#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. `mxid_age()` can be used on
pg\_class.relminmxid to find its age.

Aggressive `VACUUM`s, regardless of what causes them, are *guaranteed*
to be able to advance the table\'s relminmxid. 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.

As a safety device, an aggressive vacuum scan will occur for any table
whose multixact-age is greater than
[???](#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.

The Autovacuum Daemon {#autovacuum}
---------------------

autovacuum

general information

PostgreSQL has an optional but highly recommended feature called
autovacuum, whose purpose is to automate the execution of `VACUUM` and
`ANALYZE` 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 [???](#guc-track-counts) is set to `true`. In the default
configuration, autovacuuming is enabled and the related configuration
parameters are appropriately set.

The "autovacuum daemon" actually consists of multiple processes. There
is a persistent daemon process, called the autovacuum launcher, which is
in charge of starting autovacuum worker processes for all databases. The
launcher will distribute the work across time, attempting to start one
worker within each database every [???](#guc-autovacuum-naptime)
seconds. (Therefore, if the installation has N databases, a new worker
will be launched every `autovacuum_naptime`/N seconds.) A maximum of
[???](#guc-autovacuum-max-workers) worker processes are allowed to run
at the same time. If there are more than `autovacuum_max_workers`
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 `VACUUM` and/or `ANALYZE` as needed.
[???](#guc-log-autovacuum-min-duration) can be set to monitor autovacuum
workers\' activity.

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 [???](#guc-max-connections) or
[???](#guc-superuser-reserved-connections) limits.

Tables whose relfrozenxid value is more than
[???](#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 `VACUUM` exceeds the "vacuum
threshold", the table is vacuumed. The vacuum threshold is defined as:

    vacuum threshold = vacuum base threshold + vacuum scale factor * number of tuples

where the vacuum base threshold is
[???](#guc-autovacuum-vacuum-threshold), the vacuum scale factor is
[???](#guc-autovacuum-vacuum-scale-factor), and the number of tuples is
pg\_class.reltuples.

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:

    vacuum insert threshold = vacuum base insert threshold + vacuum insert scale factor * number of tuples

where the vacuum insert base threshold is
[???](#guc-autovacuum-vacuum-insert-threshold), and vacuum insert scale
factor is [???](#guc-autovacuum-vacuum-insert-scale-factor). Such
vacuums may allow portions of the table to be marked as all visible and
also allow tuples to be frozen, which can reduce the work required in
subsequent vacuums. For tables which receive `INSERT` operations but no
or almost no `UPDATE`/`DELETE` operations, it may be beneficial to lower
the table\'s [???](#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 a semi-accurate count updated by
each `UPDATE`, `DELETE` and `INSERT` operation. (It is only
semi-accurate because some information might be lost under heavy load.)
If the relfrozenxid value of the table is more than
`vacuum_freeze_table_age` transactions old, an aggressive vacuum is
performed to freeze old tuples and advance relfrozenxid; otherwise, only
pages that have been modified since the last vacuum are scanned.

For analyze, a similar condition is used: the threshold, defined as:

    analyze threshold = analyze base threshold + analyze scale factor * number of tuples

is compared to the total number of tuples inserted, updated, or deleted
since the last `ANALYZE`.

Partitioned tables are not processed by autovacuum. Statistics should be
collected by running a manual `ANALYZE` when it is first populated, and
again whenever the distribution of data in its partitions changes
significantly.

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

The default thresholds and scale factors are taken from
`postgresql.conf`, but it is possible to override them (and many other
autovacuum control parameters) on a per-table basis; see
[???](#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 [???](#runtime-config-autovacuum) for more details on the
global settings.

When multiple workers are running, the autovacuum cost delay parameters
(see [???](#runtime-config-resource-vacuum-cost)) are "balanced" 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
`autovacuum_vacuum_cost_delay` or `autovacuum_vacuum_cost_limit` storage
parameters have been set are not considered in the balancing algorithm.

Autovacuum workers generally don\'t block other commands. If a process
attempts to acquire a lock that conflicts with the
`SHARE UPDATE EXCLUSIVE` lock held by autovacuum, lock acquisition will
interrupt the autovacuum. For conflicting lock modes, see
[???](#table-lock-compatibility). However, if the autovacuum is running
to prevent transaction ID wraparound (i.e., the autovacuum query name in
the pg\_stat\_activity view ends with `(to prevent wraparound)`), the
autovacuum is not automatically interrupted.

> **Warning**
>
> Regularly running commands that acquire locks conflicting with a
> `SHARE UPDATE EXCLUSIVE` lock (e.g., ANALYZE) can effectively prevent
> autovacuums from ever completing.

Routine Reindexing {#routine-reindex}
==================

reindex

In some situations it is worthwhile to rebuild indexes periodically with
the [???](#sql-reindex) command or a series of individual rebuilding
steps.

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.

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.

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.

[???](#sql-reindex) can be used safely and easily in all cases. This
command requires an `ACCESS EXCLUSIVE` lock by default, hence it is
often preferable to execute it with its `CONCURRENTLY` option, which
requires only a `SHARE UPDATE EXCLUSIVE` lock.

Log File Maintenance {#logfile-maintenance}
====================

server log

log file maintenance

It is a good idea to save the database server\'s log output somewhere,
rather than just discarding it via `/dev/null`. The log output is
invaluable when diagnosing problems. However, the log output tends to be
voluminous (especially at higher debug levels) so you won\'t want to
save it indefinitely. You need to *rotate* the log files so that new log
files are started and old ones removed after a reasonable period of
time.

If you simply direct the stderr of `postgres` 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 PostgreSQL
in a development environment, but few production servers would find this
behavior acceptable.

A better approach is to send the server\'s stderr 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 `logging_collector`
to `true` in `postgresql.conf`. The control parameters for this program
are described in [???](#runtime-config-logging-where). You can also use
this approach to capture the log data in machine readable CSV
(comma-separated values) format.

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 rotatelogs tool included in the Apache distribution can
be used with PostgreSQL. One way to do this is to pipe the server\'s
stderr output to the desired program. If you start the server with
`pg_ctl`, then stderr is already redirected to stdout, so you just need
a pipe command, for example:

    pg_ctl start | rotatelogs /var/log/pgsql_log 86400

You can combine these approaches by setting up logrotate to collect log
files produced by PostgreSQL built-in logging collector. In this case,
the logging collector defines the names and location of the log files,
while logrotate periodically archives these files. When initiating log
rotation, logrotate must ensure that the application sends further
output to the new file. This is commonly done with a `postrotate` script
that sends a `SIGHUP` signal to the application, which then reopens the
log file. In PostgreSQL, you can run `pg_ctl` with the `logrotate`
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 [???](#runtime-config-logging-where)).

> **Note**
>
> 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 logrotate 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
> `prerotate` script to ignore open log files.

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

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

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.

[pgBadger](https://pgbadger.darold.net/) is an external project that
does sophisticated log file analysis.
[check\_postgres](https://bucardo.org/check_postgres/) provides Nagios
alerts when important messages appear in the log files, as well as
detection of many other extraordinary conditions.
