|From:||Heikki Linnakangas <hlinnaka(at)iki(dot)fi>|
|To:||John Naylor <john(dot)naylor(at)enterprisedb(dot)com>|
|Cc:||Jaime Casanova <jcasanov(at)systemguards(dot)com(dot)ec>, vignesh C <vignesh21(at)gmail(dot)com>, pgsql-hackers <pgsql-hackers(at)postgresql(dot)org>, Peter Geoghegan <pg(at)bowt(dot)ie>, Tomas Vondra <tomas(dot)vondra(at)2ndquadrant(dot)com>, Zhihong Yu <zyu(at)yugabyte(dot)com>|
|Subject:||Re: Polyphase merge is obsolete|
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On 05/10/2021 20:24, John Naylor wrote:
> I've had a chance to review and test out the v5 patches.
Thanks! I fixed the stray reference to PostgreSQL 14 that Zhihong
mentioned, and pushed.
> I've done some performance testing of master versus both patches
> applied. The full results and test script are attached, but I'll give a
> summary here. A variety of value distributions were tested, with
> work_mem from 1MB to 16MB, plus 2GB which will not use external sort at
> all. I settled on 2 million records for the sort, to have something
> large enough to work with but also keep the test time reasonable. That
> works out to about 130MB on disk. We have recent improvements to datum
> sort, so I used both single values and all values in the SELECT list.
> The system was on a Westmere-era Xeon with gcc 4.8. pg_prewarm was run
> on the input tables. The raw measurements were reduced to the minimum of
> five runs.
> I can confirm that sort performance is improved with small values of
> work_mem. That was not the motivating reason for the patch, but it's a
> nice bonus. Even as high as 16MB work_mem, it's possible some of the
> 4-6% differences represent real improvement and not just noise or binary
> effects, but it's much more convincing at 4MB and below, with 25-30%
> faster with non-datum integer sorts at 1MB work_mem. The nominal
> regressions seem within the noise level, with one exception that only
> showed up in one set of measurements (-10.89% in the spreadsheet). I'm
> not sure what to make of that since it only happens in one combination
> of factors and nowhere else.
That's a bit odd, but given how many data points there are, I think we
can write it off as random noise.
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