Re: Choosing parallel_degree

Hey,

I think are definitely use cases for using parallel agg on a small table
when the time for each agg operation is very high. PostGIS can be used to
create many examples of low row count and table size but high CPU
operations.

This does bring up an interesting point I don't quite understand though. If
I run parallel agg on a table with 4 rows with 2 workers will it run on two
workers (2 rows each) or will the first one grab all 4 rows?

Cheers,

James Sewell,
PostgreSQL Team Lead / Solutions Architect
______________________________________

Level 2, 50 Queen St, Melbourne VIC 3000

*P *(+61) 3 8370 8000 *W* www.lisasoft.com *F *(+61) 3 8370 8099

On Thu, Mar 17, 2016 at 10:30 PM, Julien Rouhaud <julien(dot)rouhaud(at)dalibo(dot)com>
wrote:

> On 17/03/2016 12:21, David Rowley wrote:
> > On 18 March 2016 at 00:13, Julien Rouhaud <julien(dot)rouhaud(at)dalibo(dot)com>
> wrote:
> >> With the current threshold, you need a table bigger than 8 MB to be able
> >> to force parallel workers. I'm not sure there'll be benefits for
> >> multiple workers on a table smaller than 8 MB, since setting up all the
> >> parallel stuff takes time.
> >
> > It would be really nice if it were possible to drop the setting really
> > low, so that combined with a low parallel_setup_cost we could enable
> > parallel query on small tables in the regression test suite.
> >
> >
>
> Indeed. That could also be a use case for moving parallel_threshold to a
> GUC, but not sure what'd be best.
>
> --
> Julien Rouhaud
> http://dalibo.com - http://dalibo.org
>

--

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