Re: bad estimation together with large work_mem generates terrible slow hash joins

From: Robert Haas <robertmhaas(at)gmail(dot)com>
To: Tomas Vondra <tv(at)fuzzy(dot)cz>
Cc: "pgsql-hackers(at)postgresql(dot)org" <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: bad estimation together with large work_mem generates terrible slow hash joins
Date: 2014-09-12 21:22:58
Message-ID: CA+Tgmoa+bw+JDnNW+PGR7GeFZEpOfSJae+YvwQSbM5MUHX7ZJA@mail.gmail.com
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On Fri, Sep 12, 2014 at 4:55 PM, Tomas Vondra <tv(at)fuzzy(dot)cz> wrote:
>> I'm actually quite surprised that you find batching to be a better
>> strategy than skimping on buckets, because I would have expect the
>> opposite, almost categorically. Batching means having to write out
>> the tuples we can't process right away and read them back in. If
>> that involves disk I/O, I think the cost of that I/O is going to be
>> FAR more than the overhead we would have incurred by searching
>> slightly longer bucket chains. If it didn't, then you could've set
>> work_mem higher and avoided batching in the first place.
>
> No, I don't find batching to be a better strategy. I just think this
> really needs more discussion than a simple "let's use NTUP_PER_BUCKET=4
> to avoid batching" follow-up patch.
>
> For example, let's say we switch to NTUP_PER_BUCKET=4 to avoid batching,
> and then discover we need to start batching anyway. Should we keep the
> settings, or should we revert NTUP_PER_BUCKET=1? Or maybe not doing that
> for nbatch=2, but for nbatch=16?

My first thought is to revert to NTUP_PER_BUCKET=1, but it's certainly
arguable. Either method, though, figures to be better than doing
nothing, so let's do something.

--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company

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