From: | Andres Freund <andres(at)anarazel(dot)de> |
---|---|
To: | Justin Pryzby <pryzby(at)telsasoft(dot)com> |
Cc: | Pavel Stehule <pavel(dot)stehule(at)gmail(dot)com>, pgsql-hackers(at)lists(dot)postgresql(dot)org |
Subject: | Re: possible memory leak in VACUUM ANALYZE |
Date: | 2023-02-11 07:18:26 |
Message-ID: | 20230211071826.kupqanpfzh6zrxvr@awork3.anarazel.de |
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Lists: | pgsql-hackers |
Hi,
On 2023-02-11 00:53:48 -0600, Justin Pryzby wrote:
> On Sat, Feb 11, 2023 at 07:06:45AM +0100, Pavel Stehule wrote:
> > pá 10. 2. 2023 v 23:01 odesílatel Justin Pryzby <pryzby(at)telsasoft(dot)com> napsal:
> > > On Fri, Feb 10, 2023 at 09:23:11PM +0100, Pavel Stehule wrote:
> > > > pá 10. 2. 2023 v 21:18 odesílatel Andres Freund <andres(at)anarazel(dot)de> napsal:
> > > > > On 2023-02-10 21:09:06 +0100, Pavel Stehule wrote:
> > > > > > Just a small note - I executed VACUUM ANALYZE on one customer's database,
> > > > > > and I had to cancel it after a few hours, because it had more than 20GB RAM
> > > > > > (almost all physical RAM).
> > > > >
> > > > > Just to make sure: You're certain this was an actual memory leak, not just
> > > > > vacuum ending up having referenced all of shared_buffers? Unless you use huge
> > > > > pages, RSS increases over time, as a process touched more and more pages in
> > > > > shared memory. Of course that couldn't explain rising above
> > > > > shared_buffers + overhead.
> > > > >
> > > > > > The memory leak is probably not too big. This database is a little bit
> > > > > > unusual. This one database has more than 1 800 000 tables. and the same
> > > > > > number of indexes.
> > > > >
> > > > > If you have 1.8 million tables in a single database, what you saw might just
> > > > > have been the size of the relation and catalog caches.
> > > >
> > > > can be
> > >
> > > Well, how big was shared_buffers on that instance ?
> >
> > 20GB RAM
> > 20GB swap
> > 2GB shared buffers
>
> Thanks; so that can't explain using more than 2GB + a bit of overhead.
I think my theory of 1.8 million relcache / catcache entries is pretty good...
I'd do the vacuum analyze again, interrupt once memory usage is high, and
check
SELECT * FROM pg_backend_memory_contexts ORDER BY total_bytes DESC
> BTW I'm interested about this because I have an VM instance running v15
> which has been killed more than a couple times in the last 6 months, and
> I haven't been able to diagnose why. But autovacuum/analyze could
> explain it. On this one particular instance, we don't have many
> relations, though...
Killed in what way? OOM?
If you'd set up strict overcommit you'd get a nice memory dump in the log...
Greetings,
Andres Freund
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