From: | Robert Haas <robertmhaas(at)gmail(dot)com> |
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To: | Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> |
Cc: | Jim Nasby <Jim(dot)Nasby(at)bluetreble(dot)com>, José Luis Tallón <jltallon(at)adv-solutions(dot)net>, pgsql-hackers <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: Parallel Seq Scan |
Date: | 2014-12-08 17:51:33 |
Message-ID: | CA+TgmobkqnWh=GwjpBtyoP0U9MKMr2TAge-ST4yoEkN=ZqH6WA@mail.gmail.com |
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Lists: | Postg토토SQL : Postg토토SQL |
On Sat, Dec 6, 2014 at 1:50 AM, Amit Kapila <amit(dot)kapila16(at)gmail(dot)com> wrote:
> I think we have access to this information in planner (RelOptInfo -> pages),
> if we want, we can use that to eliminate the small relations from
> parallelism, but question is how big relations do we want to consider
> for parallelism, one way is to check via tests which I am planning to
> follow, do you think we have any heuristic which we can use to decide
> how big relations should be consider for parallelism?
Surely the Path machinery needs to decide this in particular cases
based on cost. We should assign some cost to starting a parallel
worker via some new GUC, like parallel_startup_cost = 100,000. And
then we should also assign a cost to the act of relaying a tuple from
the parallel worker to the master, maybe cpu_tuple_cost (or some new
GUC). For a small relation, or a query with a LIMIT clause, the
parallel startup cost will make starting a lot of workers look
unattractive, but for bigger relations it will make sense from a cost
perspective, which is exactly what we want.
There are probably other important considerations based on goals for
overall resource utilization, and also because at a certain point
adding more workers won't help because the disk will be saturated. I
don't know exactly what we should do about those issues yet, but the
steps described in the previous paragraph seem like a good place to
start anyway.
--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company
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