Re: How to clean/truncate / VACUUM FULL pg_largeobject without (much) downtime?
От | Jim Nasby |
---|---|
Тема | Re: How to clean/truncate / VACUUM FULL pg_largeobject without (much) downtime? |
Дата | |
Msg-id | 555F9CF8.8000708@BlueTreble.com обсуждение исходный текст |
Ответ на | How to clean/truncate / VACUUM FULL pg_largeobject without (much) downtime? ("Muthusamy, Sivaraman" <sivaraman.muthusamy@in.verizon.com>) |
Список | pgsql-performance |
On 5/11/15 4:55 AM, Muthusamy, Sivaraman wrote: > Hi Group, > > Facing a problem where pg_catalog.pg_largetobject has been growing fast > recently, in last two weeks. The actual data itself, in user tables, is > about 60GB, but pg_catalog.pg_largeobject table is 200GB plues. Please > let me know how to clean/truncate this table without losing any user > data in other table. Autovacuum should be taking care of it for you, though you could also try a manual vacuum (VACUUM pg_largeobject;). > With regards to this pg_largeobject, I have the following questions: > > -What is this pg_largetobject ? It stores large objects http://www.postgresql.org/docs/9.4/static/lo-interfaces.html > -what does it contain ? tried PostgreSQL documentation and lists, but > could not get much from it. > > -why does it grow ? > > -Was there any configuration change that may have triggered this to > grow? For last one year or so, there was no problem, but it started > growing all of sudden in last two weeks. The only change we had in last > two weeks was that we have scheduled night base-backup for it and > auto-vacuum feature enabled. Changes to autovacuum settings could certainly cause changes. Long-running transactions would prevent cleanup, as would any prepared transactions (which should really be disabled unless you explicitly need them). > -pg_largeobject contains so many duplicate rows (loid). Though there are > only about 0.6 million rows (LOIDs), but the total number of rows > including duplicates are about 59million records. What are all these ? Each row can only be ~2KB wide, so any LO that's larger than that will be split into multiple rows. -- Jim Nasby, Data Architect, Blue Treble Consulting Data in Trouble? Get it in Treble! http://BlueTreble.com
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