Mark Mielke wrote:
> PFC wrote:
>> Actually, the memory used by the hash depends on the number of
>> distinct values, not the number of rows which are processed...
>> Consider :
>>
>> SELECT a GROUP BY a
>> SELECT a,count(*) GROUP BY a
>>
>> In both cases the hash only holds discinct values. So if you have
>> 1 million rows to process but only 10 distinct values of "a", the
>> hash will only contain those 10 values (and the counts), so it will
>> be very small and fast, it will absorb a huge seq scan without
>> problem. If however, you have (say) 100 million distinct values for
>> a, using a hash would be a bad idea. As usual, divide the size of
>> your RAM by the number of concurrent connections or something.
>> Note that "a" could be a column, several columns, anything, the
>> size of the hash will be proportional to the number of distinct
>> values, ie. the number of rows returned by the query, not the number
>> of rows processed (read) by the query. Same with hash joins etc,
>> that's why when you join a very small table to a large one Postgres
>> likes to use seq scan + hash join on the small table.
>
> This surprises me - hash values are lossy, so it must still need to
> confirm against the real list of values, which at a minimum should
> require references to the rows to check against?
>
> Is PostgreSQL doing something beyond my imagination? :-)
Hmmm... You did say distinct values, so I can see how that would work
for distinct. What about seq scan + hash join, though? To complete the
join, wouldn't it need to have a reference to each of the rows to join
against? If there is 20 distinct values and 200 rows in the small table
- wouldn't it need 200 references to be stored?
Cheers,
mark
--
Mark Mielke <mark@mielke.cc>