I have postgres table with jsonb field. Field size is about 2-4kb per row. My application updates 100k rows per day 2000 times (changing 0.1-0.5% of data in field). Autovacuum is off, vacuum full runs every day at night.
Vacuum frees about 100-300gb every day and takes a long time to go causing application downtime.
The question is: can I solve this problem with jsonb field or I must split that field onto other simple tables?
If your concern is long down time then yes VACUUM FULL requires exclusive lock on the table being vacuumed for entire period of run.
I'll suggest you to try pg_repack extension or pg_squeeze extension - depending upon postgres version. Unlike CLUSTER and VACUUM FULL it works online, without holding an exclusive lock on the processed tables during processing. These extensions are really easy to install and use in postgres. These extensions can reduce your downtime significantly and also will help to reduce runs of VACUUM FULL.
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I have 900+ postgres schemas (which collectively hold 40,000 tables) that I'd like to drop. However, it appears that it wants me to vacuum everything first, because I get this whenever I try to drop a schema.
ERROR: database is not accepting commands to avoid wraparound data loss in database
Is there a way to drop a large number of schemas without having to vacuum first?
IS there any problem is running the vacuum command. It is like a garbage collection for a database. I use postgre database and I use this command before doing any major work like backup or creating a sql scripts of the whole database.
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.
You've got two choices. Do the vacuum, or drop the whole database. xid wrap-around must be avoided.
https://blog.sentry.io/2015/07/23/transaction-id-wraparound-in-postgres
There is not much you can do, except VACUUM oder dropping the database.
In addition, if you don't do the VACUUM, the database will not work for anything, not just for the schemas you want to drop.
How to find in PostgreSQL 9.5 what is causing deadlock error/failure when doing full vacuumdb over database with option --jobs to run full vacuum in parallel.
I just get some process numbers and table names... How to prevent this so I could successfuly do full vacuum over database in parallel?
Completing a VACUUM FULL under load is a pretty hard task. The problem is that Postgres is contracting space taken by the table, thus any data manipulation interferes with that.
To achieve a full vacuum you have these options:
Lock access to the vacuumed table. Not sure if acquiring some exclusive lock will help, though. You may need to prevent access to the table on application level.
Use a create new table - swap (rename tables) - move data - drop original technique. This way you do not contract space under the original table, you free it by simply dropping the table. Of course you are rebuilding all indexes, redirecting FKs, etc.
Another question is: do you need to VACUUM FULL? The only thing it does that VACUUM ANALYZE does not is contracting the table on the file system. If you are not very limited by disk space you do not need doing a full vacuum that much.
Hope that helps.
Am newbie in PostgreSQL(Version 9.2) Database development. While looking one of my table a saw an option called autovaccum.
many of my table contains 20000+ rows.For testing purpose I've altered one of that table like below
ALTER TABLE theTable SET (
autovacuum_enabled = true
);
So,I wish to know the benefits/advantages/disadvantages(if any) autovacuuming a table ?
Autovacuum is enabled by default in current versions of Postgres (and has been for a while). It's generally a good thing to have enabled for performance and other reasons.
Prior to autovacuuming, you would need to explicitly vacuum tables yourself (via cronjobs which executed psql commands to vacuum them, or similar) in order to get rid of dead tuples, etc. Postgres has for a while now managed this for you via autovacuum.
I have in some cases, with tables that have immense churn (i.e. very high rates of insertions and deletions) found it necessary to still explicitly vacuum via a cron in order to keep the dead tuple count low and performance high, because the autovacuum doesn't kick in fast enough, but this is something of a niche case.
More info: http://www.postgresql.org/docs/current/static/runtime-config-autovacuum.html
I have given a postgres 9.2 DB around 20GB of size.
I looked through the database and saw that it has been never run vacuum and/or analyze on any tables.
Autovacuum is on and the transaction wraparound limit is very far (only 1% of it).
I know nothing about the data activity (number of deletes,inserts, updates), but I see, it uses a lot of index and sequence.
My question is:
does the lack of vacuum and/or analyze affect data integrity (for example a select doesn't show all the rows matches the select from a table or from an index)? The speed of querys and writes doesn't matter.
is it possible that after the vacuum and/or analyze the same query gives a different answer than it would executed before the vacuum/analyze command?
I'm fairly new to PG, thank you for your help!!
Regards,
Figaro88
Running vacuum and/or analyze will not change the result set produced by any select operation (unless there was a bug in PostgreSQL). They may effect the order of results if you do not supply an ORDER BY clause.
I've got PostgreSQL 9.2 and a tiny database with just a bit of seed data for a website that I'm working on.
The following query seems to run forever:
ALTER TABLE diagnose_bodypart ADD description text NOT NULL;
diagnose_bodypart is a table with less than 10 rows. I've let the query run for over a minute with no results. What could be the problem? Any recommendations for debugging this?
Adding a column does not require rewriting a table (unless you specify a DEFAULT). It is a quick operation absent any locks. pg_locks is the place to check, as Craig pointed out.
In general the most likely cause are long-running transactions. I would be looking at what work-flows are hitting these tables and how long the transactions are staying open for. Locks of this sort are typically transactional and so committing transactions will usually fix the problem.