On Thu, 2007-05-03 at 21:37, Merlin Moncure wrote:
> On 5/3/07, Fei Liu <fei.liu@aepnetworks.com> wrote:
> > Hello, Andreas, I too am having exactly the same issue as you do.
> > Comparing my partitioned and plain table performance, I've found that
> > the plain tables perform about 25% faster than partitioned table. Using
> > 'explain select ...', I see that constraints are being used so in
> > partitioned tables fewer rows are examined. But still partitioned tables
> > are 25% slower, what a let down.
>
> That's a little bit harsh. The main use of partitioning is not to
> make the table faster but to make the maintenance easier. When
> constraint exclusion works well for a particular query you can get a
> small boost but many queries will break down in a really negative way.
> So, you are sacrificing flexibility for easier maintenance. You have
> to really be careful how you use it.
>
> The best case for partitioning is when you can logically divide up
> your data so that you really only have to deal with one sliver of it
> at a time...for joins and such. If the OP could force the constraint
> exclusion (maybe by hashing the timestamp down to a period and using
> that for where clause), his query would be fine. The problem is it's
> not always easy to do that.
Agree++
I've been testing partitioning for a zip code lookup thing that was
posted here earlier, and I partitioned a 10,000,000 row set into about
400 partitions. I found that selecting a range of areas defined by x/y
coordinates was faster without any indexes. The same selection with one
big table and one big (x,y) index took 3 to 10 seconds typically, same
select against the partitions with no indexes took 0.2 to 0.5 seconds.
For that particular application, the only way to scale it was with
partitioning.
