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 24.1.6. 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 19.4.4.
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 But eventually, an outdated or deleted row version is no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 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 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 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.
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 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 — 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-232 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.
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.
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
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.
Periodically, VACUUM
will perform an aggressive
vacuum, skipping only those pages which contain neither dead rows nor
any unfrozen XID or MXID values.
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
use this more aggressive strategy for all scans.
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 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 freeze cutoff XID that was used
by the last aggressive VACUUM
for that table. All rows
inserted by transactions with XIDs 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.
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). 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 eleven million transactions from the wraparound point:
WARNING: database "mydb" must be vacuumed within 10985967 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 1 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 1-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 postgres reference
page for details about using single-user mode.
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
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
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
scans, regardless of
what causes them, enable advancing the value for that table.
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 autovacuum_multixact_freeze_max_age. Aggressive vacuum scans will also occur progressively for all tables, starting with those that have the oldest multixact-age, if the amount of used member storage space exceeds the amount 50% of the addressable storage space. Both of these kinds of aggressive scans will occur even if autovacuum is nominally disabled.
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 number of obsolete tuples is obtained from the statistics
collector; it is a semi-accurate count updated by each
UPDATE
and DELETE
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
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 19.10 for more details on
the global settings.
When multiple workers are running, the autovacuum cost delay parameters
(see Section 19.4.4) 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.