From: | Scott Marlowe <scott(dot)marlowe(at)gmail(dot)com> |
---|---|
To: | Gregg Jaskiewicz <gryzman(at)gmail(dot)com> |
Cc: | "pgsql-general(at)postgresql(dot)org" <pgsql-general(at)postgresql(dot)org> |
Subject: | Re: table spaces |
Date: | 2013-03-10 13:38:50 |
Message-ID: | CAOR=d=0qeTTZoR2yevC-W1=aPTQFH5=+z7QHRN+Kobqs+3W6Mw@mail.gmail.com |
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Lists: | pgsql-general |
On Sun, Mar 10, 2013 at 6:23 AM, Gregg Jaskiewicz <gryzman(at)gmail(dot)com> wrote:
>
>
>
> On 10 March 2013 02:19, Scott Marlowe <scott(dot)marlowe(at)gmail(dot)com> wrote:
>>
>> First get a baseline for how things work with just pg_xlog on one
>> small set (RAID 1 is often plenty) and RAID-10 on all the rest with
>> all the data (i.e. base directory) there. With a fast HW RAID
>> controller this is often just about as fast as any amount of breaking
>> things out will be. But if you do break things out and they are fster
>> then you'll know by how much. If it's slower then you know you've got
>> a really busy set and some not so busy ones. And so on...
>
> (side note, google mail in their infinite evilness make it tricky if not
> careful to reply below post using their webapp, beware).
>
> I might have a table that needs some heavy writes, and while it doesn't
> necessarily have to be fast TPS wise, I don't want it to bog down rest of
> the database.
> Reads are ok, as I'm planning for the DB to fit in RAM cache, so once read -
> it will be there - more or less.
> It's distributing writes that I care about mostly.
A large drive set with a HW caching RAID controller is usually pretty
good at that. There are times breaking the data up onto separate disks
help. Often what happens is that when you split your data up one set
or another gets suboptimal performance by having fewer drives
available to it etc. So at least have a benchmark of all the disks
together first to compare to. Often it's nice to have two machines
one with one big array and one you can reconfigured to test on to
compare with in real time.
> I'll try iostat, whilst running characterisation scenarios. That was my plan
> anyway.
> I had no idea separating indexes from tables might help too. Would have
> thought, they both are interconnected so much in the code, that dividing
> them up won't help as much.
It can definitely help if you only have a few drives. The more drives
you have the less each read or write is likely to bump into another
read or write on the same drive. I.e. as the number of drives
approaches infinity the chance of collision is zero.
> What about table partitioning ? For heavy writes, would some sort of a
> strategy there make difference ?
Partitioning is more about handling large data sets and splitting off
the most used parts into separate partitions so you're not
sequentially scanning a huge data set to get to the small, more
commonly used parts.
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