On Fri, Jan 06, 2006 at 06:36:52PM -0500, Greg Stark wrote:
> Josh Berkus <josh@agliodbs.com> writes:
>
> > > These numbers don't make much sense to me. It seems like 5% is about as
> > > slow as reading the whole file which is even worse than I expected. I
> > > thought I was being a bit pessimistic to think reading 5% would be as
> > > slow as reading 20% of the table.
> >
> > It's about what *I* expected. Disk seeking is the bane of many access
> > methods.
>
> Sure, but that bad? That means realistic random_page_cost values should be
> something more like 20 rather than 4. And that's with seeks only going to
> subsequent blocks in a single file, which one would expect to average less
> than the half rotation that a random seek would average. That seems worse than
> anyone expects.
>
> > Anyway, since the proof is in the pudding, Simon and I will be working on
> > some demo code for different sampling methods so that we can debate
> > results rather than theory.
>
> Note that if these numbers are realistic then there's no i/o benefit to any
> sampling method that requires anything like 5% of the entire table and is
> still unreliable. Instead it makes more sense to implement an algorithm that
> requires a full table scan and can produce good results more reliably.
>
> --
> greg
>
I have not looked closely at the sampling process in PostgreSQL, but given
that getting an accurate answer is expensive in terms of read/seeks, would
it be possible to iteratively refine the estimate overtime? Ideally we could
use the same disk blocks that are already being read to satisfy a query.
The initial estimate could be done with a minimal impact and then we piggy-
back the I/O needed to refine the estimate on the normal query I/O. The
obvious limit would be if the entire table were scanned we would get a 100%
exact estimate of the distict value at that time, and otherwise a progressively
more accurate approximation as queries are run. This would allow us to
hide the I/O in other normal block accesses.
Ken
