Re: Parallel Seq Scan

From: Jim Nasby <Jim(dot)Nasby(at)BlueTreble(dot)com>
To: Amit Kapila <amit(dot)kapila16(at)gmail(dot)com>, Stephen Frost <sfrost(at)snowman(dot)net>
Cc: pgsql-hackers <pgsql-hackers(at)postgresql(dot)org>
Subject: Re: Parallel Seq Scan
Date: 2014-12-22 02:04:56
Message-ID: 54977C48.5020600@BlueTreble.com
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On 12/21/14, 12:42 AM, Amit Kapila wrote:
> On Fri, Dec 19, 2014 at 6:21 PM, Stephen Frost <sfrost(at)snowman(dot)net <mailto:sfrost(at)snowman(dot)net>> wrote:
> a. Instead of passing value array, just pass tuple id, but retain the
> buffer pin till master backend reads the tuple based on tupleid.
> This has side effect that we have to retain buffer pin for longer
> period of time, but again that might not have any problem in
> real world usage of parallel query.
>
> b. Instead of passing value array, pass directly the tuple which could
> be directly propagated by master backend to upper layer or otherwise
> in master backend change some code such that it could propagate the
> tuple array received via shared memory queue directly to frontend.
> Basically save the one extra cycle of form/deform tuple.
>
> Both these need some new message type and handling for same in
> Executor code.
>
> Having said above, I think we can try to optimize this in multiple
> ways, however we need additional mechanism and changes in Executor
> code which is error prone and doesn't seem to be important at this
> stage where we want the basic feature to work.

Would b require some means of ensuring we didn't try and pass raw tuples to frontends? Other than that potential wrinkle, it seems like less work than a.

...

> I think there are mainly two things which can lead to benefit
> by employing parallel workers
> a. Better use of available I/O bandwidth
> b. Better use of available CPU's by doing expression evaluation
> by multiple workers.

...

> In the above tests, it seems to me that the maximum benefit due to
> 'a' is realized upto 4~8 workers

I'd think a good first estimate here would be to just use effective_io_concurrency.
--
Jim Nasby, Data Architect, Blue Treble Consulting
Data in Trouble? Get it in Treble! http://BlueTreble.com

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