From PostgreSQL blog
VACUUM reclaims storage occupied by dead tuples. In normal PostgreSQL operation, tuples that are deleted or obsoleted by an update are not physically removed from their table; they remain present until a VACUUM is done. Therefore it's necessary to do VACUUM periodically, especially on frequently-updated tables.
So, i had a performance optimization issue in java application with jdbc. So my question is did VACUUM executed on somewhere in JDBC transaction or need to set explicitly?
While that quotation is saying the truth, it omits the fact that for a decade or so PostgreSQL has been having the autovacuum daemon that does this job for you automatically.
So normally you don't have to concern yourself with that. Only on tables with very high write activity you have to tune autovacuum to be more aggressive, and you may need the occasional VACUUM (FULL) if you bulk-delete a large percentage of a table.
Performance issues are normally not connected with VACUUM (except that sequential scans take longer on bloated tables), so the connection is not clear to me.
You may control the running of VACUUM by do appropriate settings described in the section
https://www.postgresql.org/docs/current/static/runtime-config-autovacuum.html#GUC-AUTOVACUUM-FREEZE-MAX-AGE
Related
Postgres doc tells that partitioned tables are not processed by autovacuum. But still I see that last_autovacuum column from pg_stat_user_tables is populated with recent timestamps for live partitions.
Does it mean that these timestamps are set by the background worker which only prevents transaction ID wraparound, without actually performing ANALYZE&VACUUM? Or whatever else could populate them?
Besides, taken that partitions are large and active enough, should I run the both ANALYZE and VACUUM manually on those partitions? If yes, does the order matter?
UPDATE
I'm trying to elaborate, thanks to the comments given.
Taking that vacuum should work the same way on partition as on the regular table, what could be a reason for much faster growth of the occupied disk space after partitioning? Before partitioning it was nearly a linear function of records count.
What is confusing as well, when looking for autovacuum processes running I see that those related to partitions are denoted with "to prevent wraparound", while others are not. Is it absolutely a coincidence or there is something to check?
Documentation describes partitioned table as rather a virtual entity, without its own storage. What is the point in denoting that it is not vacuumed?
The statement from the documentation is true, but misleading. Autovacuum does not process the partitioned table itself, but it processes the partitions, which are regular PostgreSQL tables. So dead tuples get removed, the visibility map gets updated, and so on. In short, there is nothing to worry about as far as vacuuming is concerned. Remember that the partitioned table itself does not hold any data!
What the documentation warns you about is ANALYZE. Autovacuum also launches automatic ANALYZE jobs to collect accurate table statistics. This will be work fine on the partitions, but there are no table statistics collected on the partitioned table itself, so you have to run ANALYZE manually on the partitioned table to get these data. In practice, I find that not to be a problem, since the optimizer generates plans for each individual partition anyway, and there it has accurate statistics.
My long running SELECT queries against Hot stand-by are failing apparently due to replay on the standby leading to vacuum of some of the rows matching my query.
Is there support for an option where I can ask the Hot stand-by server to not bother about such changes to the rows (even the rows that were updated/deleted) and continue with the scan, for my query?
Or, is dropping all queries where a matching row was cleaned up during replay, vaccumm something the server always does and there's no other way supported.
You can use hot_standby_feedback to tell the primary server to not vacuum rows that the standby server is still using. If you are concerned about affecting the primary in this way, you could instead use one of max_standby_streaming_delay or max_standby_archive_delay (depending on if you are streaming or copying log files).
These are all detailed here: https://www.postgresql.org/docs/current/runtime-config-replication.html
Postgresql has the functionality of Vacuum for recollecting the space occupied by dead tuples. Auto vacuum is on by default and runs according to the configuration setting.
When I check the output of pg_stat_all_tables i.e. last_vacuum and last_autovacuum, autovacuum was never run for most of the tables in the database which have enough number of dead tuples(more than 1K). We also get a time window of 2-3 hours when these tables are used rarely.
Below are autovacuum settings for my database
below is the output of pg_stat_all_tables
I want to ask that is it a good idea to depend only on auto vacuum?
Are there any special setting required for autovacuum to function properly?
Should we set up a manual vacuum? Should we use both in parallel or just turn off autovacuum and use manual vacuum only?
You should definitely use autovacuum.
Are there any autovacuum processes running currently?
Does a manual VACUUM on such a table succeed?
Set log_autovacuum_min_duration = 0 to get information about autovacuum processing in the logs.
If system activity is too high, autovacuum may not be able to keep up. In this case it is advisable to configure autovacuum to be more aggressive, e.g. by setting autovacuum_vacuum_cost_limit = 1000.
https://www.postgresql.org/docs/current/static/routine-vacuuming.html
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.
vacuum creates significant IO, asjust https://www.postgresql.org/docs/current/static/runtime-config-resource.html#RUNTIME-CONFIG-RESOURCE-VACUUM-COST to fit your needs.
Also you can set autovacuum settings per table, to be more "custom" https://www.postgresql.org/docs/current/static/sql-createtable.html#SQL-CREATETABLE-STORAGE-PARAMETERS
the above will give you the idea why your 1K dead tuples might be not enough for autovacuum and how to change it.
manual VACUUM is a perfect solution for one time run, while to run the system I'd definitely rely on autovacuum daemon
I have found a bug in my application code where I have started a transaction, but never commit or do a rollback. The connection is used periodically, just reading some data every 10s or so. In the pg_stat_activity table, its state is reported as "idle in transaction", and its backend_start time is over a week ago.
What is the impact on the database of this? Does it cause additional CPU and RAM usage? Will it impact other connections? How long can it persist in this state?
I'm using postgresql 9.1 and 9.4.
Since you only SELECT, the impact is limited. It is more severe for any write operations, where the changes are not visible to any other transaction until committed - and lost if never committed.
It does cost some RAM and permanently occupies one of your allowed connections (which may or may not matter).
One of the more severe consequences of very long running transactions: It blocks VACUUM from doing it's job, since there is still an old transaction that can see old rows. The system will start bloating.
In particular, SELECT acquires an ACCESS SHARE lock (the least blocking of all) on all referenced tables. This does not interfere with other DML commands like INSERT, UPDATE or DELETE, but it will block DDL commands as well as TRUNCATE or VACUUM (including autovacuum jobs). See "Table-level Locks" in the manual.
It can also interfere with various replication solutions and lead to transaction ID wraparound in the long run if it stays open long enough / you burn enough XIDs fast enough. More about that in the manual on "Routine Vacuuming".
Blocking effects can mushroom if other transactions are blocked from committing and those have acquired locks of their own. Etc.
You can keep transactions open (almost) indefinitely - until the connection is closed (which also happens when the server is restarted, obviously.)
But never leave transactions open longer than needed.
There are two major impacts to the system.
The tables that have been used in those transactions:
are not vacuumed which means they are not "cleaned up" and their statistics aren't updated which might lead to bad (=slow) execution plans
cannot be changed using ALTER TABLE
I'm nearly out of disk space because of a query that tried to update every row in a huge table. I don't have enough space for CLUSTER (though it would barely fit if I dropped indexes first and recreated them afterwards).
How can I estimate how long VACUUM will take? How about VACUUM FULL? How do the three (with CLUSTER) compare in terms of running time and disk usage?
It's PostgreSQL 8.3.
use cluster, until 8.4 vacuum full is broke. if it takes to long you might as well dump and reload the table.