On Thu, 2005-12-08 at 12:26 +0100, Pål Stenslet wrote:
> I'm currently benchmarking several RDBMSs with respect to analytical
> query performance on medium-sized multidimensional data sets. The data
> set contains 30,000,000 fact rows evenly distributed in a
> multidimensional space of 9 hierarchical dimensions. Each dimension
> has 8000 members.
> I have established similar conditions for the query in PostgreSQL, and
> it runs in about 30 seconds. Again the CPU utilization is high with no
> noticable I/O. The query plan is of course very different from that of
> Oracle, since PostgreSQL lacks the bitmap index merge operation. It
> narrows down the result one dimension at a time, using the
> single-column indexes provided. It is not an option for us to provide
> multi-column indexes tailored to the specific query, since we want
> full freedom as to which dimensions each query will use.
> Are these the results we should expect when comparing PostgreSQL to
> Oracle for such queries, or are there special optimization options for
> PostgreSQL that we may have overlooked? (I wouldn't be suprised if
> there are, since I spent at least 2 full days trying to trigger the
> star optimization magic in my Oracle installation.)
Yes, I'd expect something like this right now in 8.1; the numbers stack
up to PostgreSQL doing equivalent join speeds, but w/o star join.
You've confused the issue here since:
- Oracle performs star joins using a bit map index transform. It is the
star join that is the important bit here, not the just the bitmap part.
- PostgreSQL does actually provide bitmap index merge, but not star join
(YET!)
[I've looked into this, but there seem to be multiple patent claims
covering various aspects of this technique, yet at least other 3 vendors
manage to achieve this. So far I've not dug too deeply, but I understand
the optimizations we'd need to perform in PostgreSQL to do this.]
Best Regards, Simon Riggs