Re: PostgreSQL clustering VS MySQL clustering
От | Darcy Buskermolen |
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Тема | Re: PostgreSQL clustering VS MySQL clustering |
Дата | |
Msg-id | 200501200929.37228.darcy@wavefire.com обсуждение исходный текст |
Ответ на | Re: PostgreSQL clustering VS MySQL clustering ("Joshua D. Drake" <jd@commandprompt.com>) |
Ответы |
Re: PostgreSQL clustering VS MySQL clustering
|
Список | 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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