Re: PostgreSQL and Ultrasparc T1

Ok. That is what I wanted to know. Right now this database is a PostgreSQL
7.4.8 system. I am using it in a sort of DSS role. I have weekly summaries
of the sales for our division going back three years. I have a PHP based
webapp that I wrote to give the managers access to this data. The webapp
lets them make selections for reports and then it submits a parameterized
query to the database for execution. The returned data rows are displayed
and formatted in their web browser. My largest sales table is about 13
million rows along with all the indexes it takes up about 20 gigabytes. I
need to scale this application up to nearly 100 gigabytes to handle daily
sales summaries. Once we start looking at daily sales figures our database
size could grow ten to twenty times. I use postgresql because it gives me
the kind of enterprise database features I need to program the complex logic
for the queries. I also need the transaction isolation facilities it
provides so I can optimize the queries in plpgsql without worrying about
multiple users temp tables colliding with each other. Additionally, I hope
to rewrite the front end application in JSP so maybe I could use the
multithreaded features of the Java to exploit a multicore multi-cpu system.
There are almost no writes to the database tables. The bulk of the
application is just executing parameterized queries and returning huge
amounts of data. I know bizgres is supposed to be better at this but I want
to stay away from anything that is beta. I cannot afford for this thing to
go wrong. My reasoning for looking at the T1000/2000 was simply the large
number of cores. I know postgresql uses a super server that forks copies of
itself to handle incoming requests on port 5432. But I figured the number of
cores on the T1000/2000 processors would be utilized by the forked copies of
the postgresql server. From the comments I have seen so far it does not look
like this is the case. We had originally sized up a dual processor dual core
AMD opteron system from HP for this but I thought I could get more bang for
the buck on a T1000/2000. It now seems I may have been wrong. I am stronger
in Linux than Solaris so I am not upset I am just trying to find the best
hardware for the anticipated needs of this application.

Thanks,
Juan

On Monday 19 December 2005 01:25, Scott Marlowe wrote:
> From: pgsql-performance-owner(at)postgresql(dot)org on behalf of Juan Casero
>
> QUOTE:
>
> Hi -
>
>
> Can anyone tell me how well PostgreSQL 8.x performs on the new Sun
> Ultrasparc T1 processor and architecture on Solaris 10? I have a custom
> built retail sales reporting that I developed using PostgreSQL 7.48 and PHP
> on a Fedora Core 3 intel box. I want to scale this application upwards to
> handle a database that might grow to a 100 GB. Our company is green
> mission conscious now so I was hoping I could use that to convince
> management to consider a Sun Ultrasparc T1 or T2 system provided that if I
> can get the best performance out of it on PostgreSQL.
>
> ENDQUOTE:
>
> Well, generally, AMD 64 bit is going to be a better value for your dollar,
> and run faster than most Sparc based machines.
>
> Also, PostgreSQL is generally faster under either BSD or Linux than under
> Solaris on the same box. This might or might not hold as you crank up the
> numbers of CPUs.
>
> PostgreSQL runs one process for connection. So, to use extra CPUs, you
> really need to have >1 connection running against the database.
>
> Mostly, databases tend to be either I/O bound, until you give them a lot of
> I/O, then they'll be CPU bound.
>
> After that lots of memory, THEN more CPUs. Two CPUs is always useful, as
> one can be servicing the OS and another the database. But unless you're
> gonna have lots of users hooked up, more than 2 to 4 CPUs is usually a
> waste.
>
> So, I'd recommend a dual core or dual dual core (i.e. 4 cores) AMD64 system
> with 2 or more gigs ram, and at least a pair of fast drives in a mirror
> with a hardare RAID controller with battery backed cache. If you'll be
> trundling through all 100 gigs of your data set regularly, then get all the
> memory you can put in a machine at a reasonable cost before buying lots of
> CPUs.
>
> But without knowing what you're gonna be doing we can't really make solid
> recommendations...