From: | Merlin Moncure <mmoncure(at)gmail(dot)com> |
---|---|
To: | Craig James <cjames(at)emolecules(dot)com> |
Cc: | "Joshua D(dot) Drake" <jd(at)commandprompt(dot)com>, "Graeme B(dot) Bell" <graeme(dot)bell(at)nibio(dot)no>, postgres performance list <pgsql-performance(at)postgresql(dot)org> |
Subject: | Re: Hmmm... why does CPU-intensive pl/pgsql code parallelise so badly when queries parallelise fine? Anyone else seen this? |
Date: | 2015-07-08 18:46:53 |
Message-ID: | CAHyXU0wO_WMzrbdcdtWwpk-78j_4P-M-Kr0xOyJVg1K15dQNAQ@mail.gmail.com |
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Lists: | pgsql-performance |
On Wed, Jul 8, 2015 at 12:48 PM, Craig James <cjames(at)emolecules(dot)com> wrote:
> On Tue, Jul 7, 2015 at 10:31 PM, Joshua D. Drake <jd(at)commandprompt(dot)com>
> wrote:
>>
>>
>> On 07/07/2015 08:05 PM, Craig James wrote:
>>>
>>>
>>>
>>> No ideas, but I ran into the same thing. I have a set of C/C++ functions
>>> that put some chemistry calculations into Postgres as extensions (things
>>> like, "calculate the molecular weight of this molecule"). As SQL
>>> functions, the whole thing bogged down, and we never got the scalability
>>> we needed. On our 8-CPU setup, we couldn't get more than 2 CPUs busy at
>>> the same time, even with dozens of clients.
>>>
>>> When I moved these same functions into an Apache fast-CGI HTTP service
>>> (exact same code, same network overhead), I could easily scale up and
>>> use the full 100% of all eight CPUs.
>>>
>>> I have no idea why, and never investigated further. The convenience of
>>> having the functions in SQL wasn't that important.
>>
>>
>> I admit that I haven't read this whole thread but:
>>
>> Using Apache Fast-CGI, you are going to fork a process for each instance
>> of the function being executed and that in turn will use all CPUs up to the
>> max available resource.
>>
>> With PostgreSQL, that isn't going to happen unless you are running (at
>> least) 8 functions across 8 connections.
>
>
> Well, right, which is why I mentioned "even with dozens of clients."
> Shouldn't that scale to at least all of the CPUs in use if the function is
> CPU intensive (which it is)?
only in the absence of inter-process locking and cache line bouncing.
merlin
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