Tom Lane <tgl@sss.pgh.pa.us> writes:
> I think the problem may well be that we use hash buckets that are too
> large (ie, whole pages). After we fetch the page, we have to grovel
> through every tuple on it to find the one(s) that really match the
> query, whereas btree has a much more intelligent strategy (viz binary
> search) to do its intrapage searches. Smaller buckets would help make
> up for this.
Hm, you would expect hash indexes to still be a win for very large indexes
where you're worried more about i/o than cpu resources.
> Another issue is that we don't store the raw hashcode in the index
> tuples, so the only way to test a tuple is to actually invoke the
> datatype equality function. If we stored the whole 32-bit hashcode
> we could eliminate non-matching hashcodes cheaply. I'm not sure how
> painful it'd be to do this though ... hash uses the same index tuple
> layout as everybody else, and so there's no convenient place to put
> the hashcode.
I looked a while back and was suspicious about the actual hash functions too.
It seemed like a lot of them were vastly suboptimal. That would mean we're
often dealing with mostly empty and mostly full buckets instead of well
distributed hash tables.
-- Gregory Stark EnterpriseDB http://www.enterprisedb.com
