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From: Tomas Vondra <[email protected]>
To: Pavel Stehule <[email protected]>
To: John Naylor <[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 18:07:54 +0100
Message-ID: <[email protected]> (raw)
In-Reply-To: <CAFj8pRCO5ocbr-wFWx5QsKdfkW-=XuQ6zkW5FES7ERQZQHtpwQ@mail.gmail.com>
References: <[email protected]>
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On 12/11/25 07:12, Pavel Stehule wrote:
> 
> 
> čt 11. 12. 2025 v 3:53 odesílatel John Naylor <[email protected]
> <mailto:[email protected]>> napsal:
> 
>     On Wed, Dec 10, 2025 at 5:20 PM Tomas Vondra <[email protected]
>     <mailto:[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.
> 

Depends on what you mean by "really complex". TPC-DS queries are not
trivial, but the complexity may not be in the number of joins.

Of course, setting geqo_threshold to 2 may be too aggressive. Not sure.


regards

-- 
Tomas Vondra

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