Re: Parallel Append implementation
От | Andres Freund |
---|---|
Тема | Re: Parallel Append implementation |
Дата | |
Msg-id | 20170404201348.4zqigiub654bpgxh@alap3.anarazel.de обсуждение исходный текст |
Ответ на | Re: [HACKERS] Parallel Append implementation (Robert Haas <robertmhaas@gmail.com>) |
Список | pgsql-hackers |
On 2017-04-04 08:01:32 -0400, Robert Haas wrote: > On Tue, Apr 4, 2017 at 12:47 AM, Andres Freund <andres@anarazel.de> wrote: > > I don't think the parallel seqscan is comparable in complexity with the > > parallel append case. Each worker there does the same kind of work, and > > if one of them is behind, it'll just do less. But correct sizing will > > be more important with parallel-append, because with non-partial > > subplans the work is absolutely *not* uniform. > > Sure, that's a problem, but I think it's still absolutely necessary to > ramp up the maximum "effort" (in terms of number of workers) > logarithmically. If you just do it by costing, the winning number of > workers will always be the largest number that we think we'll be able > to put to use - e.g. with 100 branches of relatively equal cost we'll > pick 100 workers. That's not remotely sane. I'm quite unconvinced that just throwing a log() in there is the best way to combat that. Modeling the issue of starting more workers through tuple transfer, locking, startup overhead costing seems a better to me. If the goal is to compute the results of the query as fast as possible, and to not use more than max_parallel_per_XXX, and it's actually beneficial to use more workers, then we should. Because otherwise you really can't use the resources available. - Andres
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