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From: Konstantin Knizhnik <k.knizhnik@postgrespro.ru>
To: Andres Freund <andres@anarazel.de>
Cc: Tom Lane <tgl@sss.pgh.pa.us>
Cc: Bruce Momjian <bruce@momjian.us>
Cc: Douglas Doole <dougdoole@gmail.com>
Cc: Robert Haas <robertmhaas@gmail.com>
Cc: Pavel Stehule <pavel.stehule@gmail.com>
Cc: PostgreSQL Hackers <pgsql-hackers@postgresql.org>
Subject: Re: Cached plans and statement generalization
Date: Thu, 11 May 2017 23:30:46 +0300
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On 05/11/2017 10:52 PM, Andres Freund wrote:
> On 2017-05-11 22:48:26 +0300, Konstantin Knizhnik wrote:
>> On 05/11/2017 09:31 PM, Tom Lane wrote:
>>> Bruce Momjian <bruce@momjian.us> writes:
>>>> Good point.  I think we need to do some measurements to see if the
>>>> parser-only stage is actually significant.  I have a hunch that
>>>> commercial databases have much heavier parsers than we do.
>>> FWIW, gram.y does show up as significant in many of the profiles I take.
>>> I speculate that this is not so much that it eats many CPU cycles, as that
>>> the constant tables are so large as to incur lots of cache misses.  scan.l
>>> is not quite as big a deal for some reason, even though it's also large.
>>>
>>> 			regards, tom lane
>> Yes, my results shows that pg_parse_query adds not so much overhead:
>> 206k TPS for my first variant with string literal substitution and modified query text used as hash key vs.
>> 181k. TPS for version with patching raw parse tree constructed by pg_parse_query.
> Those numbers and your statement seem to contradict each other?

Oops, my parse error:( I incorrectly read Tom's statement.
Actually, I also was afraid that price of parsing is large enough and this is why my first attempt was to avoid parsing.
But then I find out that most of the time is spent in analyze and planning (see attached profile):

pg_parse_query: 4.23%
pg_analyze_and_rewrite 8.45%
pg_plan_queries: 15.49%

>
> - Andres


-- 
Konstantin Knizhnik
Postgres Professional: http://www.postgrespro.com
The Russian Postgres Company

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