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 Section 25.1.6. 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.
PostgreSQL's
VACUUM command has to
process each table on a regular basis for several reasons:
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 — see
Section 20.4.4.
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 Chapter 13): 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 But eventually, an outdated or deleted row version is no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 VACUUMs
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 VACUUMs 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 vacuumdb might be helpful.
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
or one of the table-rewriting variants of
ALTER TABLE.
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.
If you have a table whose entire contents are deleted on a periodic
basis, consider doing it with
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.
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 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.
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 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.
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.
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.
Vacuum maintains a visibility map 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, 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.
VACUUM freezes a page's tuples (by processing
the tuple header fields described in Section 73.6.1) as a way of avoiding long term
dependencies on transaction status metadata referenced therein.
Heap pages that only contain frozen tuples are suitable for long
term storage. Larger databases are often mostly comprised of cold
data that is modified very infrequently, plus a relatively small
amount of hot data that is updated far more frequently.
VACUUM applies a variety of techniques that
allow it to concentrate most of its efforts on hot data.
PostgreSQL's MVCC 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 the on-disk representation of transaction IDs is only 32-bits, the system is incapable of representing distances between any two XIDs that exceed about 2 billion transaction IDs.
One of the purposes of periodic vacuuming is to manage the
Transaction Id address space. 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.
There is, in effect, an infinite distance between a frozen
transaction ID and any unfrozen transaction ID. This allows the
on-disk representation of transaction IDs to recycle the 32-bit
address space efficiently.
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. All rows inserted by transactions
older than this cutoff XID are guaranteed to have been frozen.
Similarly, the datfrozenxid column of
a database's pg_database row is a lower
bound on the unfrozen XIDs appearing in that database — 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.
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.
A separate relminmxid field can be
advanced any time relfrozenxid is
advanced. VACUUM manages the MultiXactId
address space by implementing rules that are analogous to the
approach taken with Transaction IDs. Many of the XID-based
settings that influence VACUUM's behavior have
direct MultiXactId analogs. A convenient way to examine
information about the MultiXactId address space is to execute
queries such as:
SELECT c.oid::regclass as table_name,
mxid_age(c.relminmxid)
FROM pg_class c
WHERE c.relkind IN ('r', 'm');
SELECT datname, mxid_age(datminmxid) FROM pg_database;
When VACUUM is configured to freeze more
aggressively it will typically set the table's
relfrozenxid and
relminmxid fields to relatively recent
values. However, there can be significant variation among tables
with varying workload characteristics. There can even be
variation in how relfrozenxid
advancement takes place over time for the same table, across
successive VACUUM operations. Sometimes
VACUUM will be able to advance
relfrozenxid and
relminmxid by relatively many
XIDs/MXIDs despite performing relatively little freezing work. On
the other hand VACUUM can sometimes freeze many
individual pages while only advancing
relfrozenxid by as few as one or two
XIDs (this is typically seen following bulk loading).
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, as well as
information about how many pages were newly frozen. The same
details appear in the server log when autovacuum logging
(controlled by log_autovacuum_min_duration)
reports on a VACUUM operation executed by
autovacuum.
As a general rule, the design of VACUUM
prioritizes stable and predictable performance characteristics
over time, while still leaving some scope for freezing lazily when
a lazy strategy is likely to avoid unnecessary work altogether. Tables
whose heap relation on-disk size is less than vacuum_freeze_strategy_threshold at the start of
VACUUM will have page freezing triggered based
on “lazy” criteria. Freezing will only take place
when one or more XIDs attain an age greater than vacuum_freeze_min_age, or when one or more MXIDs
attain an age greater than vacuum_multixact_freeze_min_age.
Tables that are larger than vacuum_freeze_strategy_threshold will have
VACUUM trigger freezing for any and all pages
that are eligible to be frozen under the lazy criteria, as well as
pages that VACUUM considers all visible pages.
This is the eager freezing strategy. The design makes the soft
assumption that larger tables will tend to consist of pages that
will only need to be processed by VACUUM once.
The overhead of freezing each page is expected to be slightly
higher in the short term, but much lower in the long term, at
least on average. Eager freezing also limits the accumulation of
unfrozen pages, which tends to improve performance
stability over time.
vacuum_freeze_min_age and vacuum_multixact_freeze_min_age also act as
limits on the age of the final values that
relfrozenxid and
relminmxid can be set to. Note that
lazy strategy VACUUMs don't necessarily have to
advance either field by any amount, but may nevertheless advance
each field frequently in practice.
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 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 autovacuum_naptime
seconds. (Therefore, if the installation has N databases,
a new worker will be launched every
autovacuum_naptime/N seconds.)
A maximum of 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.
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 max_connections or superuser_reserved_connections limits.
Tables whose relfrozenxid value is
more than 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 autovacuum_vacuum_threshold, the vacuum scale
factor is 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 autovacuum_vacuum_insert_threshold, and
vacuum insert scale factor is 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. 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.)
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.
If no relfrozenxid-advancing
VACUUM is issued on the table before
autovacuum_freeze_max_age is reached, an
anti-wraparound autovacuum will soon be launched against the
table. This reliably advances
relfrozenxid when there is no other
reason for VACUUM to run, or when a smaller
table had VACUUM operations that lazily opted
not to advance relfrozenxid.
An anti-wraparound autovacuum will also be triggered for any table whose multixact-age is greater than autovacuum_multixact_freeze_max_age. However, if the storage occupied by multixacts members exceeds 2GB, anti-wraparound vacuum might occur more often than this.
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 by manually executing the required
VACUUM commands. It is usually sufficient to
allow autovacuum to finish against the table with the oldest
relfrozenxid and/or
relminmxid value. The wraparound
failsafe mechanism controlled by vacuum_failsafe_age and vacuum_multixact_failsafe_age will typically
trigger before warning messages are first emitted. This happens
dynamically, in any antiwraparound autovacuum worker that is
tasked with advancing very old table ages. It will also happen
during manual VACUUM operations.
The shutdown mode is not enforced in single-user mode, which can be useful in some disaster recovery scenarios. See the postgres reference page for details about using single-user mode.
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
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 Section 20.10 for more details on
the global settings.
When multiple workers are running, the autovacuum cost delay parameters
(see Section 20.4.4) 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 13.2. 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.
Regularly running commands that acquire locks conflicting with a
SHARE UPDATE EXCLUSIVE lock (e.g., ANALYZE) can
effectively prevent autovacuums from ever completing.