Re: Parallel query execution

From: Claudio Freire <klaussfreire(at)gmail(dot)com>
To: Bruce Momjian <bruce(at)momjian(dot)us>
Cc: Jeff Janes <jeff(dot)janes(at)gmail(dot)com>, Stephen Frost <sfrost(at)snowman(dot)net>, Gavin Flower <GavinFlower(at)archidevsys(dot)co(dot)nz>, PostgreSQL-development <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: Parallel query execution
Date: 2013-01-17 02:56:21
Message-ID: CAGTBQpZnCeTY50TEDHMm-hj9s5V2j_98e_KTd3P+U_1W=da-8Q@mail.gmail.com
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On Wed, Jan 16, 2013 at 11:44 PM, Bruce Momjian <bruce(at)momjian(dot)us> wrote:
> On Wed, Jan 16, 2013 at 05:04:05PM -0800, Jeff Janes wrote:
>> On Tuesday, January 15, 2013, Stephen Frost wrote:
>>
>> * Gavin Flower (GavinFlower(at)archidevsys(dot)co(dot)nz) wrote:
>> > How about being aware of multiple spindles - so if the requested
>> > data covers multiple spindles, then data could be extracted in
>> > parallel. This may, or may not, involve multiple I/O channels?
>>
>> Yes, this should dovetail with partitioning and tablespaces to pick up
>> on exactly that.
>>
>>
>> I'd rather not have the benefits of parallelism be tied to partitioning if we
>> can help it. Hopefully implementing parallelism in core would result in
>> something more transparent than that.
>
> We will need a way to know we are not saturating the I/O channel with
> random I/O that could have been sequential if it was single-threaded.
> Tablespaces give us that info; not sure what else does.

I do also think tablespaces are a safe bet. But it wouldn't help for
parallelizing sorts or other operations with tempfiles (tempfiles
reside on the same tablespace), or even over a single table (same
tablespace again). And when the query is CPU-bound, it could be
parallelized by simply making a multithreaded memory sort. Well, not
so simply, but I do think it's an important building block.

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