From: Tom Lane <tgl@sss.pgh.pa.us>
To: Sergey Koposov <Sergey.Koposov@ed.ac.uk>
Cc: pgsql-bugs@lists.postgresql.org <pgsql-bugs@lists.postgresql.org>
Subject: Re: BUG #18909: Query creates millions of temporary files and stalls
Date: Sat, 03 May 2025 12:27:06 -0400
Message-ID: <2177960.1746289626@sss.pgh.pa.us> (raw)
In-Reply-To: <5e98fba645682c40bf5f88ef858963ade9681956.camel@ed.ac.uk>
References: <18909-e5e1b702c9441b8a@postgresql.org>
<2051617.1746223978@sss.pgh.pa.us>
<beb051161520fc48248c2f90582eb15c6a71d239.camel@ed.ac.uk>
<5e98fba645682c40bf5f88ef858963ade9681956.camel@ed.ac.uk>
Sergey Koposov <Sergey.Koposov@ed.ac.uk> writes:
> #8 0x00005615d84f6a59 in ExecHashTableInsert (hashtable=0x5615da85e5c0, slot=0x5615da823378, hashvalue=2415356794)
> at nodeHash.c:1714
> shouldFree = true
> tuple = 0x5615da85f5e8
> bucketno = 32992122
> batchno = 3521863
Yeah, this confirms the idea that the hashtable has exploded into an
unreasonable number of buckets and batches. I don't know why a
parallel hash join would be more prone to do that than a non-parallel
one, though. I'm hoping some of the folks who worked on PHJ will
look at this.
What have you got work_mem set to? I hope it's fairly large, if
you need to join such large tables.
regards, tom lane
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To: pgsql-bugs@postgresql.org
Cc: tgl@sss.pgh.pa.us, Sergey.Koposov@ed.ac.uk, pgsql-bugs@lists.postgresql.org
Subject: Re: BUG #18909: Query creates millions of temporary files and stalls
In-Reply-To: <2177960.1746289626@sss.pgh.pa.us>
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