Re: 15,000 tables - next step - Mailing list pgsql-performance

From William Yu
Subject Re: 15,000 tables - next step
Date
Msg-id dmucf7$20ff$1@news.hub.org
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In response to Re: 15,000 tables - next step  (Michael Riess <mlriess@gmx.de>)
Responses Re: 15,000 tables - next step  (Michael Riess <mlriess@gmx.de>)
List pgsql-performance
Michael Riess wrote:
>> Well, I'd think that's were your problem is.  Not only you have a
>> (relatively speaking) small server -- you also share it with other
>> very-memory-hungry services!  That's not a situation I'd like to be in.
>> Try putting Apache and Tomcat elsewhere, and leave the bulk of the 1GB
>> to Postgres.
>
>
> No can do. I can try to switch to a 2GB machine, but I will not use
> several machines. Not for a 5GB database. ;-)
>
>> With 1500 shared buffers you are not really going
>> anywhere -- you should have ten times that at the very least.
>>
>
> Like I said - I tried to double the buffers and the performance did not
> improve in the least. And I also tried this on a 2GB machine, and
> swapping was not a problem. If I used 10x more buffers, I would in
> essence remove the OS buffers.

Increasing buffers do improve performance -- if you have enough memory.
You just don't have enough memory to play with. My servers run w/ 10K
buffers (128MB on 64-bit FC4) and it definitely runs better w/ it at 10K
versus 1500.

With that many tables, your system catalogs are probably huge. To keep
your system catalog from continually cycling in-out of buffers/OS
cache/disk, you need a lot more memory. Ordinarily, I'd say the 500MB
you have available for Postgres to cache 5GB is a workable ratio. My
servers all have similar ratios of ~1:10 and they perform pretty good --
*except* when the system catalogs bloated due to lack of vacuuming on
system tables. My app regularly creates & drops thousands of temporary
tables leaving a lot of dead rows in the system catalogs. (Nearly the
same situation as you -- instead of 15K live tables, I had 200 live
tables and tens of thousands of dead table records.) Even with almost
8GB of RAM dedicated to postgres, performance on every single query --
not matter how small the table was -- took forever because the query
planner had to spend a significant period of time scanning through my
huge system catalogs to build the execution plan.

While my situtation was fixable by scheduling a nightly vacuum/analyze
on the system catalogs to get rid of the bazillion dead table/index
info, you have no choice but to get more memory so you can stuff your
entire system catalog into buffers/os cache. Personally, w/ 1GB of ECC
RAM at ~$85, it's a no brainer. Get as much memory as your server can
support.

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