Re: PostgreSQL clustering VS MySQL clustering - Mailing list pgsql-performance

From Darcy Buskermolen
Subject Re: PostgreSQL clustering VS MySQL clustering
Date
Msg-id 200501200929.37228.darcy@wavefire.com
Whole thread Raw
In response to Re: PostgreSQL clustering VS MySQL clustering  ("Joshua D. Drake" <jd@commandprompt.com>)
Responses Re: PostgreSQL clustering VS MySQL clustering
List pgsql-performance
On January 20, 2005 06:49 am, Joshua D. Drake wrote:
> Stephen Frost wrote:
> >* Herv? Piedvache (herve@elma.fr) wrote:
> >>Le Jeudi 20 Janvier 2005 15:30, Stephen Frost a écrit :
> >>>* Herv? Piedvache (herve@elma.fr) wrote:
> >>>>Is there any solution with PostgreSQL matching these needs ... ?
> >>>
> >>>You might look into pg_pool.  Another possibility would be slony, though
> >>>I'm not sure it's to the point you need it at yet, depends on if you can
> >>>handle some delay before an insert makes it to the slave select systems.
> >>
> >>I think not ... pgpool or slony are replication solutions ... but as I
> >> have said to Christopher Kings-Lynne how I'll manage the scalabilty of
> >> the database ? I'll need several servers able to load a database growing
> >> and growing to get good speed performance ...
> >
> >They're both replication solutions, but they also help distribute the
> >load.  For example:
> >
> >pg_pool will distribute the select queries amoung the servers.  They'll
> >all get the inserts, so that hurts, but at least the select queries are
> >distributed.
> >
> >slony is similar, but your application level does the load distribution
> >of select statements instead of pg_pool.  Your application needs to know
> >to send insert statements to the 'main' server, and select from the
> >others.
>
> You can put pgpool in front of replicator or slony to get load
> balancing for reads.

Last time I checked load ballanced reads was only available in pgpool if you
were using pgpools's internal replication.  Has something changed recently?

>
> >>>>Is there any other solution than a Cluster for our problem ?
> >>>
> >>>Bigger server, more CPUs/disks in one box.  Try to partition up your
> >>>data some way such that it can be spread across multiple machines, then
> >>>if you need to combine the data have it be replicated using slony to a
> >>>big box that has a view which joins all the tables and do your big
> >>>queries against that.
> >>
> >>But I'll arrive to limitation of a box size quickly I thing a 4
> >> processors with 64 Gb of RAM ... and after ?
>
> Opteron.

IBM Z-series, or other big iron.

>
> >Go to non-x86 hardware after if you're going to continue to increase the
> >size of the server.  Personally I think your better bet might be to
> >figure out a way to partition up your data (isn't that what google
> >does anyway?).
> >
> >    Stephen

--
Darcy Buskermolen
Wavefire Technologies Corp.
ph: 250.717.0200
fx:  250.763.1759
http://www.wavefire.com

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