Re: Problem analyzing performance of query - Mailing list pgsql-general
From | Greg Stark |
---|---|
Subject | Re: Problem analyzing performance of query |
Date | |
Msg-id | 87d61ofn2q.fsf@stark.xeocode.com Whole thread Raw |
In response to | Re: Problem analyzing performance of query (Tom Lane <tgl@sss.pgh.pa.us>) |
List | pgsql-general |
Tom Lane <tgl@sss.pgh.pa.us> writes: > Clear? It'd be nice to have more infrastructure for debugging plpgsql > code, but so far no one's got round to building any :-( Thank you. Very useful. Though one of my worries was that there was some cached plan in the plpgsql. What might be useful not just for plpgsql but for debugging other applications would be a "trace" functionality like Oracle's. It could be as simple as a guc variable which caused all queries to run under EXPLAIN ANALYZE and dumped the results somewhere for later analysis. As it happens I've narrowed the problem down and it wasn't related to any planning at all. I was running EXPLAIN ANALYZE on only the SELECT portion of the query but the full query was actually an "INSERT INTO foo () (SELECT ...)" Apparently the INSERT side of it was taking 90% of the time. Dropping a few gist indexes I was experimenting with have sped it up tenfold. Now I'm wondering whether it's inevitable slow down of maintaining these indexes or if something else was wrong. The gist indexes are not something I'm using currently, but I may need them in the future to deal with larger datasets. This table is a pre-generated "cache" of denormalized data. It's periodically truncated and regenerated. Perhaps each time I truncated it the gist indexes accumulated dead pages? Most rows are quite small but there are a few large rows (large integer arrays) perhaps they caused the gist indexes using gist__intbig_ops to have to do lots of extra work? How do I tell if the rows are getting toasted? I did run this under profiling and the gprof output didn't seem to be pointing the finger at gist functions. A significant amount of time was spent in them to be sure, but not 90%. That's what initially led me astray or I would have checked this much earlier. Flat profile: Each sample counts as 0.01 seconds. % cumulative self self total time seconds seconds calls s/call s/call name 14.66 14.54 14.54 6327634 0.00 0.00 FunctionCall3 6.42 20.91 6.37 96792 0.00 0.00 gistchoose 4.43 25.31 4.40 26 0.17 0.17 ArrayGetNItems 3.59 28.87 3.56 450164 0.00 0.00 MemoryContextAllocZero 3.38 32.22 3.35 9505045 0.00 0.00 AllocSetFreeIndex 2.93 35.12 2.91 181680 0.00 0.00 ExecMakeFunctionResultNoSets 2.41 37.51 2.39 6431187 0.00 0.00 gistdentryinit 2.28 39.77 2.26 5320723 0.00 0.00 AllocSetAlloc 2.24 41.99 2.22 3294701 0.00 0.00 tas 2.12 44.09 2.10 671001 0.00 0.00 hash_search 1.71 45.79 1.70 1538836 0.00 0.00 _bt_compare 1.47 47.25 1.46 1098578 0.00 0.00 nocachegetattr 1.41 48.65 1.40 1478208 0.00 0.00 ExecEvalVar 1.40 50.04 1.39 597373 0.00 0.00 StrategyBufferLookup 1.29 51.31 1.28 769755 0.00 0.00 comparetup_heap 1.14 52.44 1.13 5548263 0.00 0.00 gistpenalty 1.11 53.55 1.11 28058 0.00 0.00 XLogInsert 1.08 54.62 1.07 6687057 0.00 0.00 FunctionCall1 1.06 55.67 1.05 641646 0.00 0.00 hash_any 1.06 56.72 1.05 53305 0.00 0.00 gistlayerinsert 1.04 57.75 1.04 475840 0.00 0.00 gistDeCompressAtt 1.04 58.78 1.03 991639 0.00 0.00 AllocSetReset 1.04 59.81 1.03 295968 0.00 0.00 ExecTargetList [That's 60% of the time already] -- greg
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