Re: checkpointer continuous flushing
От | Tomas Vondra |
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Тема | Re: checkpointer continuous flushing |
Дата | |
Msg-id | 17100156-792a-43f6-8ba8-26d04122370e@2ndquadrant.com обсуждение исходный текст |
Ответ на | Re: checkpointer continuous flushing (Fabien COELHO <coelho@cri.ensmp.fr>) |
Ответы |
Re: checkpointer continuous flushing
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Список | pgsql-hackers |
Hi, On 03/22/2016 07:35 AM, Fabien COELHO wrote: > > Hello Tomas, > > Thanks again for these interesting benches. > >> Overall, this means ~300M transactions in total for the un-throttled >> case, so sample with ~15M transactions available when computing the >> following charts. > > Still a very sizable run! > >> There results (including scripts for generating the charts) are here: >> >> https://github.com/tvondra/flushing-benchmark-2 > > This repository seems empty. Strange. Apparently I forgot to push, or maybe it did not complete before I closed the terminal. Anyway, pushing now (it'll take a bit more time to complete). > >> 1) regular-latency.png > > I'm wondering whether it would be clearer if the percentiles where > relative to the largest sample, not to itself, so that the figures > from the largest one would still be between 0 and 1, but the other > (unpatched) one would go between 0 and 0.85, that is would be cut > short proportionnaly to the actual performance. > I'm not sure what you mean by 'relative to largest sample'? >> The two curves intersect at ~4ms, where both CDF reach ~85%. For >> the shorter transactions, the old code is slightly faster (i.e. >> apparently there's some per-transaction overhead). > > I'm not sure how meaningfull is the crossing, because both curves do > not reflect the same performance. I think that they may not cross at > all if the normalization is with the same reference, i.e. the better > run. Well, I think the curves illustrate exactly the performance difference, because with the old code the percentiles after p=0.85 get much higher. Which is the point of the crossing, although I agree the exact point does not have a particular meaning. >> 2) throttled-latency.png >> >> In the throttled case (i.e. when the system is not 100% utilized, >> so it's more representative of actual production use), the >> difference is quite clearly in favor of the new code. > > Indeed, it is a no brainer. Yep. > >> 3) throttled-schedule-lag.png >> >> Mostly just an alternative view on the previous chart, showing how >> much later the transactions were scheduled. Again, the new code is >> winning. > > No brainer again. I infer from this figure that with the initial > version 60% of transactions have trouble being processed on time, > while this is maybe about 35% with the new version. Yep. -- Tomas Vondra http://www.2ndQuadrant.com PostgreSQL Development, 24x7 Support, Remote DBA, Training & Services
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