2014-10-20 21:59 GMT-02:00 Tom Lane <tgl@xxxxxxxxxxxxx>:
Marco Di Cesare <Marco.DiCesare@xxxxxxxxxxxxxxxxxx> writes:
> We are using a BI tool that generates a query with an unusually large number of joins. My understanding is that with this many joins Postgres query planner can't possibly use an exhaustive search so it drops into a heuristics algorithm. Unfortunately, the query runs quite slow (~35 seconds) and seems to ignore using primary keys and indexes where available.
> Query plan here (sorry had to anonymize):
> http://explain.depesz.com/s/Uml
It's difficult to make any detailed comments when you've shown us only an
allegedly-bad query plan, and not either the query itself or the table
definitions.
However, it appears to me that the query plan is aggregating over a rather
large number of join rows, and there are very few constraints that would
allow eliminating rows. So I'm not at all sure there is a significantly
better plan available. Are you claiming this query was instantaneous
on SQL Server?
The only thing that jumps out at me as possibly improvable is that with
a further increase in work_mem, you could probably get it to change the
last aggregation step from Sort+GroupAggregate into HashAggregate,
which'd likely run faster ... assuming you can spare some more memory.
regards, tom lane
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Hi,
As Tom said, WORK_MEM seems a nice place to start.
Here are other considerations you might take in account:
There's also the opportunity to tune the query itself (if it's not automatically generated by your BI tool). You can always speed up a query response by using filtered sub-selects instead of calling the the entire tables themselves on the joins.
BR
Felipe
