I should also specify how my inserts are happening I guess. I'm
actually doing the logs to flat files and then inserting them into the
database on an hourly basis using COPY, so I don't need to worry as much
about the log insert speed as I do the reporting.
On 5/21/2009 2:36 PM, Scott Marlowe wrote:
On Thu, May 21, 2009 at 1:13 PM, Alex Thurlow<a...@blastro.com> wrote:
I have a postgresql database that I'm using for logging of data. There's
basically one table where each row is a line from my log files. It's
getting to a size where it's running very slow though. There are about 10
million log lines per day and I keep 30 days of data in it. All the columns
I filter on are indexed (mostly I just use date).
**DING DING DING** you've just said the magic phrase that says that
partitioning would be a help.
And I tend to pull one
day of data at a time with grouped counts by 1 or 2 other columns. There
also tends to be only 1 or 2 of these large queries running at any given
time, so a lot of resources can be thrown at each one.
I'm wondering what my resource parameters should be for optimal speed of the
selects on this database, since I haven't seen a good example where someone
has done anything like this.
With a logging database you're optimizing two often opposing actions.
Lots of small inserts in a stream that HAVE to get processed and put
in efficiently. This is often accomplished with minimum
shared_buffers and work_mem, because there's no need for the overhead
of large shared_buffers and insert queries for logging dbs don't need
much work_mem.
With a reporting database you run queries that chew up tons of memory
both shared_buffers and work_mem for efficient operation.
The machine is an 8 core opteron (I know I won't really use those, but Dell
threw in the 2nd proc for free) with 8 Gb RAM. The database is on a RAID 10
JFS partition.
Yeah CPUs are cheap, might as well stock up on them. A reporting
database can quickly go cpu bound if everything the users want to see
fits in memory.
This is what I have in postgresql.conf right now..
shared_buffers = 64MB
Small for reporting, just right for logging. I'd try something bigger
but not insanely huge. Let the OS do the caching of 90% of the data,
let the db cache a good sized working set. 256M to 1G is reasonable
based on benchmarks of your own queries.
work_mem = 128MB
Bigger than needed for logging, good for reporting. You can probably
just leave it.
maintenance_work_mem = 256MB
max_fsm_pages = 614400
If you're not partitioning then this needs to be big enough to contain
1 days+ worth of dead rows.
Look at lowering your random_page_cost, and increasing default stats
target to 100 to 1000 depending on your data and explain analyze query
testing.
--
Alex Thurlow
Blastro Networks
http://www.blastro.com
http://www.roxwel.com
http://www.yallwire.com
