From: | David Rowley <dgrowleyml(at)gmail(dot)com> |
---|---|
To: | Andreas Karlsson <andreas(at)proxel(dot)se> |
Cc: | Alexander Korotkov <aekorotkov(at)gmail(dot)com>, pgsql-hackers <pgsql-hackers(at)postgresql(dot)org>, Andres Freund <andres(at)2ndquadrant(dot)com>, Martijn van Oosterhout <kleptog(at)svana(dot)org> |
Subject: | Re: PoC: Partial sort |
Date: | 2013-12-31 08:18:42 |
Message-ID: | CAApHDvodCHCj9=W8k5huEs6WwxBSbRQq63pwto--bcK+RmcK4g@mail.gmail.com |
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Lists: | pgsql-hackers |
On Tue, Dec 31, 2013 at 2:41 PM, Andreas Karlsson <andreas(at)proxel(dot)se> wrote:
> On 12/29/2013 08:24 AM, David Rowley wrote:
>
>> If it was possible to devise some way to reuse any
>> previous tuplesortstate perhaps just inventing a reset method which
>> clears out tuples, then we could see performance exceed the standard
>> seqscan -> sort. The code the way it is seems to lookup the sort
>> functions from the syscache for each group then allocate some sort
>> space, so quite a bit of time is also spent in palloc0() and pfree()
>>
>> If it was not possible to do this then maybe adding a cost to the number
>> of sort groups would be better so that the optimization is skipped if
>> there are too many sort groups.
>>
>
> It should be possible. I have hacked a quick proof of concept for reusing
> the tuplesort state. Can you try it and see if the performance regression
> is fixed by this?
>
> One thing which have to be fixed with my patch is that we probably want to
> close the tuplesort once we have returned the last tuple from ExecSort().
>
> I have attached my patch and the incremental patch on Alexander's patch.
>
>
Thanks, the attached is about 5 times faster than it was previously with my
test case upthread.
The times now look like:
No pre-sortable index:
Total runtime: 86.278 ms
With pre-sortable index with partial sorting
Total runtime: 47.500 ms
With the query where there is no index the sort remained in memory.
I spent some time trying to find a case where the partial sort is slower
than the seqscan -> sort. The only places partial sort seems slower are
when the number of estimated sort groups are around the crossover point
where the planner would be starting to think about performing a seqscan ->
sort instead. I'm thinking right now that it's not worth raising the costs
around this as the partial sort is less likely to become a disk sort than
the full sort is.
I'll keep going with trying to break it.
Regards
David Rowley
> --
> Andreas Karlsson
>
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