Re: track_planning causing performance regression

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От Fujii Masao
Тема Re: track_planning causing performance regression
Дата
Msg-id d4a15deb-8a85-b78c-b447-bc5df7c4a926@oss.nttdata.com
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Ответ на Re: track_planning causing performance regression  (Julien Rouhaud <rjuju123@gmail.com>)
Ответы Re: track_planning causing performance regression  (Julien Rouhaud <rjuju123@gmail.com>)
Re: track_planning causing performance regression  (Peter Geoghegan <pg@bowt.ie>)
Re: track_planning causing performance regression  (Andres Freund <andres@anarazel.de>)
Список 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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