Gregory Stark wrote:
> 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.
>
>
>
This is now sounding like a lot of low hanging fruit ... highly
performant hash indexed tables could possibly be a very big win.
cheers
andrew