Richard Rowell wrote:
-> Subquery Scan "*SELECT* 1" (cost=0.00..64034.15 rows=10540 width=24) (actual time=279.089..4419.371 rows=161 loops=1)
estimating 10,000 when only 161 is a little bit different.
-> Seq Scan on da_answer a (cost=0.00..63928.75 rows=10540 width=24) (actual time=279.080..4418.808 rows=161 loops=1)Though this could be a lack of cross-column statistics. If 2 columns are correlated, the planner isn't as accurate as it could be. Also, date_effective <= 9999999999 doesn't seem very restrictive, could you use a between statement? (date between 0 and 9999999). I know for timestamps usually giving a between is better than a single sided query.
Filter: ((date_effective <= 9999999999::double precision) AND (inactive <> 1) AND (subplan))
This one was underestimated.
-> Subquery Scan "*SELECT* 2" (cost=988627.58..989175.52 rows=2799 width=24) (actual time=290.730..417.720 rows=7556 loops=1)This is one of the ones that looks like it didn't have any ideas. It could be because of the function. You might consider adding a function index, though I think there are some caveats there.
-> Hash Join (cost=988627.58..989147.53 rows=2799 width=24) (actual time=290.722..395.739 rows=7556 loops=1)
Hash Cond: ("outer".main_id = "inner".uid)
-> Function Scan on svp_getparentproviderids (cost=0.00..12.50 rows=1000 width=4) (actual time=0.473..0.474 rows=1 loops=1)Another very poor estimation. It might be a need to increase the statistics for this column (ALTER TABLE, ALTER COLUMN, SET STATISTICS). IIRC, compared with other db's postgres defaults to a much lower statistics value. Try changing it from 10 (?) to 100 or so. There was a discussion that every column with an index should use higher statistics.
-> Index Scan using in_da_dr_type_provider on da_data_restrict (cost=0.00..145.50 rows=46 width=8) (actual time=0.041..26.627 rows=7280 loops=1)I'm not a great optimizer, these are just some first things to look at. Your sort mem seems pretty low to me (considering you have 1GB of RAM). Perhaps you could bump that up to 40MB instead of 4MB. Also, if you run this query twice in a row, is it still slow? (Sometimes it takes a bit of work to get the right indexes loaded into ram, but then it is faster.)
Just some guesses, John =:->
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