Routine Database Maintenance Tasks
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
.
The other main category of maintenance task is periodic vacuuming>
of the database. This activity is discussed in
. Closely related to this is updating
the statistics that will be used by the query planner, as discussed in
.
Another task that might need periodic attention is log file management.
This is discussed in .
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 . 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
PostgreSQL's
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
PostgreSQL query planner.
To protect against loss of very old data due to
transaction 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 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
.
Recovering Disk Space
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 ): 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 vacuumings.
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 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
or one of the table-rewriting variants of
.
These commands rewrite an entire new copy of the table and build
new indexes for it. All these options require 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
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
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 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.
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 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.
Preventing Transaction ID Wraparound Failures
transaction ID
wraparound
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
PostgreSQL reserves a special XID
as FrozenXID>. This XID does not follow the normal XID
comparison rules and is always considered older
than every normal XID. Normal XIDs are
compared using modulo-231> 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, old row versions must be reassigned the XID
FrozenXID> sometime before they reach the
two-billion-transactions-old mark. Once they are assigned this
special XID, 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.
This reassignment of old XIDs is handled by VACUUM>.
controls how old an XID value has to be before it's replaced with
FrozenXID>. Larger values of this setting
preserve transactional information longer, while smaller values increase
the number of transactions that can elapse before the table must be
vacuumed again.
VACUUM> normally skips pages that don't have any dead row
versions, but those pages might still have row versions with old XID
values. To ensure all old XIDs have been replaced by
FrozenXID>, a scan of the whole table is needed.
controls when
VACUUM> does that: a whole table sweep is forced if
the table hasn't been fully scanned for vacuum_freeze_table_age>
minus vacuum_freeze_min_age> transactions. Setting it to 0
forces VACUUM> to always scan all pages, effectively ignoring
the visibility map.
The maximum time that a table can go unvacuumed is two billion
transactions minus the vacuum_freeze_min_age> value at
the time VACUUM> last scanned the whole table. 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 XIDs older than the
age specified by the configuration parameter . (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 whole-table scans.
The sole disadvantage of increasing autovacuum_freeze_max_age>
(and vacuum_freeze_table_age> along with it)
is that the pg_clog> subdirectory of the database cluster
will take more space, because it must store the commit status 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
a little less than two billion, pg_clog> can be expected to
grow to about half a gigabyte. 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_clog> storage.
(The default, 200 million transactions, translates to about 50MB of
pg_clog> storage.)
One disadvantage of decreasing vacuum_freeze_min_age> is that
it might cause VACUUM> to do useless work: changing a table row's
XID to FrozenXID> 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. Another disadvantage of decreasing this setting is
that details about exactly which transaction inserted or modified a
row will be lost sooner. This information sometimes comes in handy,
particularly when trying to analyze what went wrong after a database
failure. For these two reasons, decreasing this setting is not
recommended except for completely static tables.
To track the age of the oldest 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 whole-table VACUUM> for that table. All normal
XIDs older than this cutoff XID are guaranteed to have been replaced by
FrozenXID> within the table. Similarly,
the datfrozenxid> column of a database's
pg_database> row is a lower bound on the normal 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 relname, age(relfrozenxid) FROM pg_class WHERE relkind = 'r';
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 the whole table is
scanned. The whole table is scanned when relfrozenxid> is
more than vacuum_freeze_table_age> transactions old, when
VACUUM>'s FREEZE> option is used, or when all pages
happen to
require vacuuming to remove dead row versions. When VACUUM>
scans the whole table, after it's finished age(relfrozenxid)>
should be 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 whole-table-scanning 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 ten million transactions from the wraparound
point:
WARNING: database "mydb" must be vacuumed within 177009986 transactions
HINT: To avoid a database shutdown, execute a database-wide VACUUM in "mydb".
(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 use a standalone backend to VACUUM in "mydb".
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 use a single-user
backend to execute VACUUM>. The shutdown mode is not enforced
by a single-user backend. See the reference
page for details about using a single-user backend.
The Autovacuum Daemon
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 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
seconds. (Therefore, if the installation has N> databases,
a new worker will be launched every
autovacuum_naptime>/N> seconds.)
A maximum of 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.
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 became
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 or
limits.
Tables whose relfrozenxid> value is more than
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
,
the vacuum scale factor is
,
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, the whole
table is scanned 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.
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
on a table-by-table basis; see
for more information.
If a setting
has been changed via storage parameters, that value is used; otherwise the
global settings are used. See for
more details on the global settings.
Besides the base threshold values and scale factors, there are six
more autovacuum parameters that can be set for each table via
storage parameters.
The first parameter, autovacuum_enabled>,
can be set to false to instruct the autovacuum daemon
to skip that particular table entirely. In this case
autovacuum will only touch the table if it must do so
to prevent transaction ID wraparound.
Another two parameters,
autovacuum_vacuum_cost_delay> and
autovacuum_vacuum_cost_limit>, are used to set
table-specific values for the cost-based vacuum delay feature
(see ).
autovacuum_freeze_min_age>,
autovacuum_freeze_max_age> and
autovacuum_freeze_table_age> are used to set
values for ,
and
respectively.
When multiple workers are running, the cost limit is
balanced
among all the running workers, so that the
total impact on the system is the same, regardless of the number
of workers actually running.
Routine Reindexing
reindex
In some situations it is worthwhile to rebuild indexes periodically
with the
command.
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.
Log File 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 . 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. To do this,
just 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
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.
pgFouine
is an external project that does sophisticated log file analysis.
check_postgres
provides Nagios alerts when important messages appear in the log
files, as well as detection of many other extraordinary conditions.