Re: Hardware/OS recommendations for large databases (

From: "Luke Lonergan" <llonergan(at)greenplum(dot)com>
To: "Scott Marlowe" <smarlowe(at)g2switchworks(dot)com>, "William Yu" <wyu(at)talisys(dot)com>
Cc: pgsql-performance(at)postgresql(dot)org
Subject: Re: Hardware/OS recommendations for large databases (
Date: 2005-11-16 17:49:28
Message-ID: BFA0B128.13D50%llonergan@greenplum.com
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Oops,

Last point should be worded: ³All CPUs on all machines used by a parallel
database²

- Luke

On 11/16/05 9:47 AM, "Luke Lonergan" <llonergan(at)greenplum(dot)com> wrote:

> Scott,
>
> On 11/16/05 9:09 AM, "Scott Marlowe" <smarlowe(at)g2switchworks(dot)com> wrote:
>
>> The biggest gain is going from 1 to 2 CPUs (real cpus, like the DC
>> Opterons or genuine dual CPU mobo, not "hyperthreaded"). Part of the
>> issue isn't just raw CPU processing power. The second CPU allows the
>> machine to be more responsive because it doesn't have to context switch
>> as much.
>>
>> While I've seen plenty of single CPU servers start to bog under load
>> running one big query, the dual CPU machines always seem more than just
>> twice as snappy under similar loads.
>>
> I agree, 2 CPUs are better than one in most cases.
>
> The discussion was kicked off by the suggestion to get 8 dual core CPUs to
> process a large database with postgres. Say your decision support query takes
> 15 minutes to run with one CPU. Add another and it still takes 15 minutes.
> Add 15 and the same ...
>
> OLTP is so different from Business intelligence and Decision Support that very
> little of this thread¹s discussion is relevant IMO.
>
> The job is to design a system that can process sequential scan as fast as
> possible and uses all resources (CPUs, mem, disk channels) on each query.
> Sequential scan is 100x more important than random seeks.
>
> Here are the facts so far:
> * Postgres can only use 1 CPU on each query
> * Postgres I/O for sequential scan is CPU limited to 110-120 MB/s on the
> fastest modern CPUs
> * Postgres disk-based sort speed is 1/10 or more slower than commercial
> databases and memory doesn¹t improve it (much)
>
> These are the conclusions that follow about decision support / BI system
> architecture for normal Postgres:
> * I/O hardware with more than 110MB/s of read bandwidth is not useful
> * More than 1 CPU is not useful
> * More RAM than a nominal amount for small table caching is not useful
>
> In other words, big SMP doesn¹t address the problem at all. By contrast,
> having all CPUs on multiple machines, or even on a big SMP with lots of I/O
> channels, solves all of the above issues.
>
> Regards,
>
- Luke

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