From: | Atri Sharma <atri(dot)jiit(at)gmail(dot)com> |
---|---|
To: | Jeff Janes <jeff(dot)janes(at)gmail(dot)com> |
Cc: | Amit Kapila <amit(dot)kapila(at)huawei(dot)com>, Pg Hackers <pgsql-hackers(at)postgresql(dot)org> |
Subject: | Re: Page replacement algorithm in buffer cache |
Date: | 2013-03-24 07:20:02 |
Message-ID: | CAOeZVicR8pQEERYmF2nxwJ8E1smHPkJKmd0y0wz-+=VVJC3=_g@mail.gmail.com |
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Lists: | pgsql-hackers |
> Perhaps this isn't the help you were looking for, but I spent a long time
> looking into this a few years ago. Then I stopped and decided to work on
> other things. I would recommend you do so too.
Agreed. It seems that my concerns were not valid, and since you have
already done some testing here, it further closes the matter.
> 4) If most, but not quite all, of the highly-used data fits shared_buffers
> and shared_buffers takes most of RAM (or at least, most of RAM not already
> needed for other things like work_mem and executables), then the replacement
> policy matters a lot. But different policies suit different work-loads, and
> there is little reason to think we can come up with a way to choose between
> them. (Also, in these conditions, performance is very chaotic. You can run
> the same algorithm for a long time, and it can suddenly switch from good to
> bad or the other way around, and then stay in that new mode for a long
> time). Also, even if you come up with a good algorithm, if you make the
> data set 20% smaller or 20% larger, it is no longer a good algorithm.
Does that mean that an ideal, high performance postgres setup should
*never* set the shared_buffers to a large percentage of the system's
RAM? If so, have we ever encountered issues with low specs systems?
> 5) Having buffers enter with usage_count=0 rather than 1 would probably be
> slightly better most of the time under conditions described in 4, but there
> is no way get enough evidence of this over enough conditions to justify
> making a change. And besides, how often do people run with shared_buffers
> being most of RAM, and the hot data just barely not fitting in it?
Agreed.
> 1) If all data fits in RAM but not shared_buffers, and you have a very large
> number of CPUs and a read-only or read-mostly workload, then BufFreelistLock
> can be a major bottle neck. (But, on a Amazon high-CPU instance, I did not
> see this very much. I suspect the degree of problem depends a lot on
> whether you have a lot of sockets with a few CPUs each, versus one chip with
> many CPUs). This is very easy to come up with model cases for, pgbench -S
> -c8 -j8, for example, can often show it.
I will try that, thanks.
> 2) A major reason that people run with shared_buffers much lower than RAM is
> that performance seems to suffer with shared_buffers > 8GB under write-heavy
> workloads, even with spread-out checkpoints. This is frequently reported as
> a real world problem, but as far as I know has never been reduced to a
> simple reproducible test case. (Although there was a recent thread, maybe
> "High CPU usage / load average after upgrading to Ubuntu 12.04", that I
> thought might be relevant to this. I haven't had the time to seriously
> study the thread, or the hardware to investigate it myself)
>
This seems interesting.Do we have some indications as to what the
problems could be?
Regards,
Atri
--
Regards,
Atri
l'apprenant
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