Re: Parallel query execution introduces performance regressions
От | Peter Geoghegan |
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Тема | Re: Parallel query execution introduces performance regressions |
Дата | |
Msg-id | CAH2-Wz=wzQKkGBCRjB7f0yCo1ddPS7T3O51hHiQ1a63JnTpuyA@mail.gmail.com обсуждение исходный текст |
Ответ на | Parallel query execution introduces performance regressions (Jinho Jung <jinhojun@usc.edu>) |
Ответы |
Re: Parallel query execution introduces performance regressions
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Список | pgsql-bugs |
On Mon, Apr 1, 2019 at 11:30 AM Jinho Jung <jinhojun@usc.edu> wrote: > Surprisingly, we found that even on a larger TPC-C database (scale factor of 50, roughly 4GB of size), parallel scan isstill slower than the non-parallel execution plan in the old version. That's not a large database, and it's certainly not a large TPC-C database. If you attempt to stay under the spec's maximum tpmC/throughput per warehouse, which is 12.86 tpmC per warehouse, then you'll need several thousand warehouses on modern hardware. We're talking several hundred gigabytes. Otherwise, as far as the spec is concerned you're testing an unrealistic workload. There will be individual customers that make many more purchases than is humanly possible. You're modelling an app involving hypothetical warehouse employees that must enter data into their terminals at a rate that is not humanly possible. More importantly, this kind of analysis seems much too simplistic to be useful. *Any* change to the optimizer or optimizer settings is certain to regress some queries. We expect users that are very sensitive to small regressions to take an active interest in performance tuning their database. It would certainly be very useful if somebody came up with a less complicated way of assessing these questions, but that seems to be elusive. -- Peter Geoghegan
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