Re: track_planning causing performance regression - Mailing list pgsql-hackers
From | Fujii Masao |
---|---|
Subject | Re: track_planning causing performance regression |
Date | |
Msg-id | d4a15deb-8a85-b78c-b447-bc5df7c4a926@oss.nttdata.com Whole thread Raw |
In response to | Re: track_planning causing performance regression (Julien Rouhaud <rjuju123@gmail.com>) |
Responses |
Re: track_planning causing performance regression
Re: track_planning causing performance regression Re: track_planning causing performance regression |
List | pgsql-hackers |
On 2020/06/29 16:05, Julien Rouhaud wrote: > Hi, > > On Mon, Jun 29, 2020 at 7:49 AM Tharakan, Robins <tharar@amazon.com> wrote: >> >> During fully-cached SELECT-only test using pgbench, Postgres v13Beta1 shows Thanks for the benchmark! >> ~45% performance drop [2] at high DB connection counts (when compared with v12.3) That's bad :( >> >> Disabling pg_stat_statements.track_planning (which is 'On' by default) >> brings the TPS numbers up to v12.3 levels. >> >> The inflection point (in this test-case) is 128 Connections, beyond which the >> TPS numbers are consistently low. Looking at the mailing list [1], this issue >> didn't surface earlier possibly since the regression is trivial at low connection counts. >> >> It would be great if this could be optimized further, or track_planning >> disabled (by default) so as to not trip users upgrading from v12 with pg_stat_statement >> enabled (but otherwise not particularly interested in track_planning). Your benchmark result seems to suggest that the cause of the problem is the contention of per-query spinlock in pgss_store(). Right? This lock contention is likely to happen when multiple sessions run the same queries. One idea to reduce that lock contention is to separate per-query spinlock into two; one is for planning, and the other is for execution. pgss_store() determines which lock to use based on the given "kind" argument. To make this idea work, also every pgss counters like shared_blks_hit need to be separated into two, i.e., for planning and execution. >> These are some details around the above test: >> >> pgbench: scale - 100 / threads - 16 >> test-duration - 30s each >> server - 96 vCPUs / 768GB - r5.24xl (AWS EC2 instance) >> client - 72 vCPUs / 144GB - c5.18xl (AWS EC2 instance) (co-located with the DB server - Same AZ) >> v12 - REL_12_STABLE (v12.3) >> v13Beta1 - REL_13_STABLE (v13Beta1) >> max_connections = 10000 >> shared_preload_libraries = 'pg_stat_statements' >> shared_buffers 128MB > > I can't reproduce this on my laptop, but I can certainly believe that > running the same 3 queries using more connections than available cores > will lead to extra overhead. > > I disagree with the conclusion though. It seems to me that if you > really have this workload that consists in these few queries and want > to get better performance, you'll anyway use a connection pooler > and/or use prepared statements, which will make this overhead > disappear entirely, and will also yield an even bigger performance > improvement. A quick test using pgbench -M prepared, with > track_planning enabled, with still way too many connections already > shows a 25% improvement over the -M simple without track_planning. I understand your point. But IMO the default setting basically should be safer value, i.e., off at least until the problem disappears. Regards, -- Fujii Masao Advanced Computing Technology Center Research and Development Headquarters NTT DATA CORPORATION
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