Re: Parallel Seq Scan vs kernel read ahead

From: Ranier Vilela <ranier(dot)vf(at)gmail(dot)com>
To: Thomas Munro <thomas(dot)munro(at)gmail(dot)com>
Cc: Amit Kapila <amit(dot)kapila16(at)gmail(dot)com>, pgsql-hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: Parallel Seq Scan vs kernel read ahead
Date: 2020-05-20 11:02:42
Message-ID: CAEudQAqAOaQ48+BCvz4mEyL4Mm9dMiN5Rsa7vGME2-YpbMJTpA@mail.gmail.com
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Em qua., 20 de mai. de 2020 às 00:09, Thomas Munro <thomas(dot)munro(at)gmail(dot)com>
escreveu:

> On Wed, May 20, 2020 at 2:23 PM Amit Kapila <amit(dot)kapila16(at)gmail(dot)com>
> wrote:
> > Good experiment. IIRC, we have discussed a similar idea during the
> > development of this feature but we haven't seen any better results by
> > allocating in ranges on the systems we have tried. So, we want with
> > the current approach which is more granular and seems to allow better
> > parallelism. I feel we need to ensure that we don't regress
> > parallelism in existing cases, otherwise, the idea sounds promising to
> > me.
>
> Yeah, Linux seems to do pretty well at least with smallish numbers of
> workers, and when you use large numbers you can probably tune your way
> out of the problem. ZFS seems to do fine. I wonder how well the
> other OSes cope.
>
Windows 10 (64bits, i5, 8GB, SSD)

postgres=# set max_parallel_workers_per_gather = 0;
SET
Time: 2,537 ms
postgres=# select count(*) from t;
count
-----------
200000000
(1 row)

Time: 47767,916 ms (00:47,768)
postgres=# set max_parallel_workers_per_gather = 1;
SET
Time: 4,889 ms
postgres=# select count(*) from t;
count
-----------
200000000
(1 row)

Time: 32645,448 ms (00:32,645)

How display " -> execution time 5.2s, average read size ="?

regards,
Ranier VIlela

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