On 10 May 2005, at 16:02, Adam Haberlach wrote:
I think that perhaps he was trying to avoid having to buy "Big Iron" at all.
You would be right. Although we are not against paying a bit more than $300 for a server ;)
With all the Opteron v. Xeon around here, and talk of $30,000 machines,
perhaps it would be worth exploring the option of buying 10 cheapass
machines for $300 each. At the moment, that $300 buys you, from Dell, a
2.5Ghz Pentium 4 w/ 256mb of RAM and a 40Gb hard drive and gigabit ethernet.
The aggregate CPU and bandwidth is pretty stupendous, but not as easy to
harness as a single machine.
Yes, clustering solutions can distribute the data, and can even do it on a
per-table basis in some cases. This still leaves it up to the application's
logic to handle reunification of the data.
If your going to be programming that sort of logic into your API in the beginning, it's not too much more work to add basic replication, load balancing and partitioning into it either. But the DB should be able to do it for you, adding that stuff in later is often more difficult and less likely to get done.
1. Create a table/storage type that consists of a select statement
on another machine. While I don't think the current executor is capable of
working on multiple nodes of an execution tree at the same time, it would be
great if it could offload a select of tuples from a remote table to an
entirely different server and merge the resulting data into the current
execution. I believe MySQL has this, and Oracle may implement it in another
MySQL sort of has this, it's not as good as Oracle's though. Apparently there is a much better version of it in 5.1 though, that should make it to stable sometime next year I imagine.
2. There is no #2 at this time, but I'm sure one can be hypothesized.
I would of thought a particularly smart version of pg_pool could do it. It could partition data to different servers if it knew which columns to key by on each table.
...Google and other companies have definitely proved that one can harness
huge clusters of cheap hardware. It can't be _that_ hard, can it. :)
I shudder to think how much the "Big Iron" equivalent of a google data-center would cost.
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of John A Meinel
Sent: Tuesday, May 10, 2005 7:41 AM
To: Alex Stapleton
Subject: Re: [PERFORM] Partitioning / Clustering
Alex Stapleton wrote:
What is the status of Postgres support for any sort of multi-machine scaling support? What are you meant to do once you've upgraded your box and tuned the conf files as much as you can? But your query load is just too high for a single machine?
Upgrading stock Dell boxes (I know we could be using better machines, but I am trying to tackle the real issue) is not a hugely price efficient way of getting extra performance, nor particularly scalable in the long term.
Switch from Dell Xeon boxes, and go to Opterons. :) Seriously, Dell is far
away from Big Iron. I don't know what performance you are looking for, but
you can easily get into inserting 10M rows/day with quality hardware.
But actually is it your SELECT load that is too high, or your INSERT load,
or something inbetween.
Because Slony is around if it is a SELECT problem. http://gborg.postgresql.org/project/slony1/projdisplay.php
Basically, Slony is a Master/Slave replication system. So if you have INSERT
going into the Master, you can have as many replicated slaves, which can
handle your SELECT load.
Slony is an asynchronous replicator, so there is a time delay from the
INSERT until it will show up on a slave, but that time could be pretty
This would require some application level support, since an INSERT goes to a
different place than a SELECT. But there has been some discussion about
pg_pool being able to spread the query load, and having it be aware of the
difference between a SELECT and an INSERT and have it route the query to the
correct host. The biggest problem being that functions could cause a SELECT
func() to actually insert a row, which pg_pool wouldn't know about. There
are 2 possible solutions, a) don't do that when you are using this system,
b) add some sort of comment hint so that pg_pool can understand that the
select is actually an INSERT, and needs to be done on the master.
So, when/is PG meant to be getting a decent partitioning system? MySQL is getting one (eventually) which is apparently meant to be similiar to Oracle's according to the docs. Clusgres does not appear to be widely/or at all used, and info on it seems pretty thin on the ground, so I am not too keen on going with that. Is the real solution to multi- machine partitioning (as in, not like MySQLs MERGE tables) on PostgreSQL actually doing it in our application API? This seems like a less than perfect solution once we want to add redundancy and things into the mix.
There is also PGCluster http://pgfoundry.org/projects/pgcluster/
Which is trying to be more of a Synchronous multi-master system. I haven't
heard of Clusgres, so I'm guessing it is an older attempt, which has been
overtaken by pgcluster.
Just realize that clusters don't necessarily scale like you would want them
too. Because at some point you have to insert into the same table, which
means you need to hold a lock which prevents the other machine from doing
anything. And with synchronous replication, you have to wait for all of the
machines to get a copy of the data before you can say it has been committed,
which does *not* scale well with the number of machines.
If you can make it work, I think having a powerful master server, who can
finish an INSERT quickly, and then having a bunch of Slony slaves with a
middleman (like pg_pool) to do load balancing among them, is the best way to
scale up. There are still some requirements, like not having to see the
results of an INSERT instantly (though if you are using hinting to pg_pool,
you could hint that this query must be done on the master, realizing that
the more you do it, the more you slow everything down).
PS> I don't know what functionality has been actually implemented in
pg_pool, just that it was discussed in the past. Slony-II is also in the
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