From: | Robert Haas <robertmhaas(at)gmail(dot)com> |
---|---|
To: | Jeff Janes <jeff(dot)janes(at)gmail(dot)com> |
Cc: | Kevin Grittner <Kevin(dot)Grittner(at)wicourts(dot)gov>, rsmogura <rsmogura(at)softperience(dot)eu>, PG Hackers <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: 2nd Level Buffer Cache |
Date: | 2011-03-22 19:53:08 |
Message-ID: | AANLkTimhWo=rNeQ55OeXgVzder3-e8fMxHz7oP7n08UN@mail.gmail.com |
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Lists: | pgsql-hackers |
On Tue, Mar 22, 2011 at 11:24 AM, Jeff Janes <jeff(dot)janes(at)gmail(dot)com> wrote:
> On Fri, Mar 18, 2011 at 9:19 AM, Robert Haas <robertmhaas(at)gmail(dot)com> wrote:
>> On Fri, Mar 18, 2011 at 11:14 AM, Kevin Grittner
>> <Kevin(dot)Grittner(at)wicourts(dot)gov> wrote:
>>> Maybe the thing to focus on first is the oft-discussed "benchmark
>>> farm" (similar to the "build farm"), with a good mix of loads, so
>>> that the impact of changes can be better tracked for multiple
>>> workloads on a variety of platforms and configurations. Without
>>> something like that it is very hard to justify the added complexity
>>> of an idea like this in terms of the performance benefit gained.
>>
>> A related area that could use some looking at is why performance tops
>> out at shared_buffers ~8GB and starts to fall thereafter.
>
> Under what circumstances does this happen? Can a simple pgbench -S
> with a large scaling factor elicit this behavior?
To be honest, I'm mostly just reporting what I've heard Greg Smith say
on this topic. I don't have any machine with that kind of RAM.
--
Robert Haas
EnterpriseDB: http://www.enterprisedb.com
The Enterprise PostgreSQL Company
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