Обсуждение: costing of hash join

Поиск
Список
Период
Сортировка

costing of hash join

От
Jeff Janes
Дата:
I'm trying to figure out why hash joins seem to be systematically underused in my hands.  In the case I am immediately looking at it prefers a merge join with both inputs getting seq scanned and sorted, despite the hash join being actually 2 to 3 times faster, where inputs and intermediate working sets are all in memory.  I normally wouldn't worry about a factor of 3 error, but I see this a lot in many different situations.  The row estimates are very close to actual, the errors is only in the cpu estimates.

A hash join is charged cpu_tuple_cost for each inner tuple for inserting it into the hash table:

     * charge one cpu_operator_cost for each column's hash function.  Also,
     * tack on one cpu_tuple_cost per inner row, to model the costs of
     * inserting the row into the hashtable.

But a sort is not charged a similar charge to insert a tuple into the sort memory pool:

     * Also charge a small amount (arbitrarily set equal to operator cost) per
     * extracted tuple.  We don't charge cpu_tuple_cost because a Sort node
     * doesn't do qual-checking or projection, so it has less overhead than
     * most plan nodes.  Note it's correct to use tuples not output_tuples

Are these operations different enough to justify this difference?  The qual-checking (and I think projection) needed on a hash join should have already been performed by and costed to the seq scan feeding the hashjoin, right?

Cheers,

Jeff

Re: costing of hash join

От
Tom Lane
Дата:
Jeff Janes <jeff.janes@gmail.com> writes:
> I'm trying to figure out why hash joins seem to be systematically underused
> in my hands.  In the case I am immediately looking at it prefers a merge
> join with both inputs getting seq scanned and sorted, despite the hash join
> being actually 2 to 3 times faster, where inputs and intermediate working
> sets are all in memory.  I normally wouldn't worry about a factor of 3
> error, but I see this a lot in many different situations.  The row
> estimates are very close to actual, the errors is only in the cpu estimates.

Can you produce a test case for other people to look at?

What datatype(s) are the join keys?

> A hash join is charged cpu_tuple_cost for each inner tuple for inserting it
> into the hash table:

Doesn't seem like monkeying with that is going to account for a 3x error.

Have you tried using perf or oprofile or similar to see where the time is
actually, rather than theoretically, going?
        regards, tom lane