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Home -> Community -> Usenet -> c.d.o.server -> Oracle - solving performance problem
I am a sysadmin tasked with developing a solution to improve our Oracle
10g performance. I inherited the following server and problem. I'm not
a DBA, so if my terminology is off please forgive me, if you are kind
enough to help but need more info, I can get you that info.
Server Spec:
Red Hat Enterprise Server 3.0 2.4.21-27.0.4.ELsmp
Dual Intel Xeon CPU @ 3.00GHz w/ hyper threading
12 gigs of RAM
3 x RAID 5 arrays with 7 disks each, attached externally. Each array
has its own SCSI channel.
Problem:
We have a 230 gig database that contains 101 million rows. Indexes are
placed on mount point/SCSI channel, data on another mount point/SCSI
channel. I'm told that the size of this database can't be changed by
our development staff. In fact it will be growing by about 20-30% each
year. Certain queries are taking a dogs age to run. One is a mass load
of data each day, the other a more critical one is a client query that
takes about 2 minutes. We want to bring this value down to something
like 5-10 seconds, if thats not possible at least 30-45 seconds or so.
We know our bottle necks are I/O in both reads and writes.
Things we have tried:
- Enable and use Async I/O
Consultant was hired to look at our environment they recommended:
- We need 5-10% of db size in SGA, therefore 23 gigs of SGA for today's
size.
- 64 bit architecture, to allow for huge SGA
I need to figure out what we can do to achieve our goals and have it last at least 2 years of increasing data. I've been researching the following.
Anyone have any opinions on the best course of action? How should one handle this amount of data and maintain performance?
Grid seems like a good option, but perhaps not necessary because I/O is our problem, not really CPU. Dumb question, but how do multiple grid members access the same data efficiently? Can the SGA be spread around the members of the Grid .Any caveats?
Thanks for any advice you may be able to provide.
Mark Received on Fri Oct 07 2005 - 16:42:52 CDT
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