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From: Pavel Stehule <[email protected]>
To: John Naylor <[email protected]>
Cc: Tomas Vondra <[email protected]>
Cc: Chengpeng Yan <[email protected]>
Cc: [email protected] <[email protected]>
Subject: Re: Add a greedy join search algorithm to handle large join problems
Date: Thu, 11 Dec 2025 07:12:29 +0100
Message-ID: <CAFj8pRCO5ocbr-wFWx5QsKdfkW-=XuQ6zkW5FES7ERQZQHtpwQ@mail.gmail.com> (raw)
In-Reply-To: <CANWCAZY529EPHyo1kLnEzjFBq-UaDPc3KErK=ApqDZZ1Oc-XHg@mail.gmail.com>
References: <[email protected]>
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čt 11. 12. 2025 v 3:53 odesílatel John Naylor <[email protected]>
napsal:

> On Wed, Dec 10, 2025 at 5:20 PM Tomas Vondra <[email protected]> wrote:
> > I did however notice an interesting thing - running EXPLAIN on the 99
> > queries (for 3 scales and 0/4 workers, so 6x 99) took this much time:
> >
> > master:       8s
> > master/geqo: 20s
> > master/goo:   5s
>
> > It's nice that "goo" seems to be faster than "geqo" - assuming the plans
> > are comparable or better. But it surprised me switching to geqo makes it
> > slower than master. That goes against my intuition that geqo is meant to
> > be cheaper/faster join order planning. But maybe I'm missing something.
>
> Yeah, that was surprising. It seems that geqo has a large overhead, so
> it takes a larger join problem for the asymptotic behavior to win over
> exhaustive search.
>

If I understand correctly to design - geqo should be slower for any queries
with smaller complexity. The question is how many queries in the tested
model are really complex.



>
> --
> John Naylor
> Amazon Web Services
>
>
>


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