24.1. Routine Vacuuming
Postgres Pro 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.
24.1.1. Vacuuming Basics
VACUUM command has to process each table on a regular basis for several reasons:
- To recover or reuse disk space occupied by updated or deleted rows.
- To update data statistics used by the Postgres Pro query planner.
- To update the visibility map, which speeds up index-only scans.
- To shrink
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 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
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 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.
24.1.2. Recovering Disk Space
In Postgres Pro, an
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 But eventually, an outdated or deleted row version is no longer of interest to any transaction.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
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.
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
TRUNCATE removes the entire content of the table immediately, without requiring a subsequent
VACUUM FULL to reclaim the now-unused disk space. The disadvantage is that strict MVCC semantics are violated.
24.1.3. Updating Planner Statistics
The Postgres Pro 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.
24.1.4. Updating the Visibility Map
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 Postgres Pro to answer some queries using only the index, without reference to the underlying table. Since Postgres Pro 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.
24.1.5. Forced shrinking
Postgres Pro'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. In older versions transaction IDs have limited size (32 bits), and 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 data loss as their output become invisible.
Postgres Pro Enterprise 9.6 introduced 64-bit transaction IDs, which are not subject to wraparound and do not need modulo-232 arithmetic to be compared. Each tuple header contains two XIDs, so extending them would lead to high overhead. For that reason on-page XIDs are still 32-bit, but each page's header contains an offset, called epoch, to which they are added before comparing with each other. To accommodate this change, 64-bit transaction IDs use the
bigint type instead of the
integer type previously used for this purpose.
When new xid can't fit existing page according to its epoch, those epoch is shifted. Single page freeze takes place if needed. Both actions are performed "on the fly". Page-level wraparound can happen only when someone holds snapshot which is more than 4 billions transaction oid.
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. Postgres Pro reserves a special XID,
FrozenTransactionId, which 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.
Freezing data by
VACUUM is not needed anymore for preventing wraparound, since page-level freeze happens "on the fly". However, freezing data by
VACUUM is still needed for shrink
pg_multixact. For historical reasons, wording "autovacuum to prevent wraparound" is preserved for forced autovacuum for shrink
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
VACUUMs 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 to 0 forces
VACUUM to use this more aggressive strategy for all scans.
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
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
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 autovacuum to shrink
pg_multixact 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 autovacuums to shrink
pg_multixact, even though the table was recently vacuumed to reclaim space, whereas lower values lead to more frequent aggressive vacuuming.
The sole disadvantage of increasing
vacuum_freeze_table_age along with it) is that the
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_commit_ts storage. (The default, 200 million transactions, translates to about 50MB of
pg_xact storage and about 2GB of
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_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;
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
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
VACUUM is issued on the table until
autovacuum_freeze_max_age is reached, an autovacuum will soon be forced for the table.
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 on disk page as a 64-bit counter with an offset relative to epoch, and corresponding storage, which requires careful aging management, and storage cleanup. There is a separate storage area which holds the list of members in each multixact, which uses a 64-bit counter.
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,
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
relminmxid to find its age.
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.
An aggressive vacuum scan will occur for any table whose multixact-age is greater than autovacuum_multixact_freeze_max_age.
24.1.6. The Autovacuum Daemon
Postgres Pro has an optional but highly recommended feature called autovacuum, whose purpose is to automate the execution of
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
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
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.
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
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, which can reduce the work required in subsequent vacuums. For tables which receive
INSERT operations but no or almost no
DELETE operations, it may be beneficial to lower the table's 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 statistics collector; it is a semi-accurate count updated by each
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
Partitioned tables do not directly store tuples and consequently are not processed by autovacuum. (Autovacuum does process table partitions just like other tables.) Unfortunately, this means that autovacuum does not run
ANALYZE on partitioned tables, and this can cause suboptimal plans for queries that reference partitioned table statistics. You can work around this problem by manually running
ANALYZE on partitioned tables when they are first populated, and again whenever the distribution of data in their 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_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.