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PG 9.5 same SQL 2 different plans
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* PG 9.5 same SQL 2 different plans
@ 2016-08-03 22:20 ghiureai <isabella.ghiurea@nrc-cnrc.gc.ca>
  2016-08-04 21:40 ` Re: PG 9.5 same SQL 2 different plans Tom Lane <tgl@sss.pgh.pa.us>
  0 siblings, 1 reply; 2+ messages in thread

From: ghiureai @ 2016-08-03 22:20 UTC (permalink / raw)
  To: pgsql-admin

Hi Gurus,

we upgrade to PG 9.5.3,  in last days  we are seeing a strange 
optimization issues with one of the SQL :
  running same SQL every  15-20 times optimizer will choose( wrong 
plan)/ most expensive which  generates approx
50 GB temp files  and runs for aprox 20 min , we can not understand the 
reason ( we run vacuum analyze daily),
Pg conf values:
random_page_cost=3.0
defalult_statistics_taget=100
work_mem=400MB

Here is the SQL :

explain analyze SELECT 
ObservationSkeleton.lastModified,ObservationSkeleton.maxLastModified,ObservationSkeleton.stateCode,ObservationSkeleton.obsID,PlaneSkeleton.lastModified,PlaneSkeleton.maxLastModified,PlaneSkeleton.stateCode,PlaneSkeleton.planeID,ArtifactSkeleton.lastModified,ArtifactSkeleton.maxLastModified,ArtifactSkeleton.stateCode,ArtifactSkeleton.artifactID,PartSkeleton.lastModified,PartSkeleton.maxLastModified,PartSkeleton.stateCode,PartSkeleton.partID,ChunkSkeleton.lastModified,ChunkSkeleton.maxLastModified,ChunkSkeleton.stateCode,ChunkSkeleton.chunkID 
FROM cvodb.caom2.Observation AS ObservationSkeleton LEFT OUTER JOIN 
cvodb.caom2.Plane AS PlaneSkeleton LEFT OUTER JOIN cvodb.caom2.Artifact 
AS ArtifactSkeleton LEFT OUTER JOIN cvodb.caom2.Part AS PartSkeleton 
LEFT OUTER JOIN cvodb.caom2.Chunk AS ChunkSkeleton ON 
PartSkeleton.partID = ChunkSkeleton.partID ON 
ArtifactSkeleton.artifactID = PartSkeleton.artifactID ON 
PlaneSkeleton.planeID = ArtifactSkeleton.planeID ON 
ObservationSkeleton.obsID = PlaneSkeleton.obsID WHERE 
ObservationSkeleton.obsID = '00000000-0000-0000-0603-e3ee45c5b6b7' ORDER 
BY 
ObservationSkeleton.obsID,PlaneSkeleton.planeID,ArtifactSkeleton.artifactID,PartSkeleton.partID;

***Here is the wrong plan( using > 40GB temp files , running SEQ SCAN on 
aprox 60 mill rows,  and exec time 20 min)

|  QUERY PLAN
---------------------------------------------------------------------------------------------------------------------
  Sort  (cost=34130921.12..34130939.82  rows=7480  width=180)
    SortKey: planeskeleton.planeid, artifactskeleton.artifactid, partskeleton.partid
    ->  Nested Loop Left Join  (cost=8160852.43..34130439.82  rows=7480  width=180)
          JoinFilter:(observationskeleton.obsid = planeskeleton.obsid)
          ->   Index Scan using observation_pkeyon  observation observationskeleton  (cost=0.43..6.45  rows=1  width=36)
                IndexCond:(obsid ='00000000-0000-0000-07a6-0143085f9ddf'::uuid)
          ->   Hash Right Join  (cost=8160851.99..34130339.87  rows=7480  width=160)
                HashCond:(artifactskeleton.planeid = planeskeleton.planeid)
                ->   Hash Right Join  (cost=8158554.13..33707311.38  rows=112174888  width=124)
                      HashCond:(partskeleton.artifactid = artifactskeleton.artifactid)
                      ->   Hash Right Join  (cost=6305604.98..22889335.83  rows=112174888  width=88)
                            HashCond:(chunkskeleton.partid = partskeleton.partid)
                            ->   Seq Scanon  chunk chunkskeleton  (cost=0.00..5047469.16  rows=60691316  width=52)
                            ->  Hash  (cost=3807960.88..3807960.88  rows=112174888  width=52)
                                  ->  Seq Scanon  part partskeleton  (cost=0.00..3807960.88  rows=112174888  width=52)
                      ->  Hash  (cost=1194034.40..1194034.40  rows=29593340  width=52)
                            ->  Seq Scanon  artifact artifactskeleton  (cost=0.00..1194034.40  rows=29593340  width=52)
                ->  Hash  (cost=2288.29..2288.29  rows=766  width=52)
                      ->  Bitmap Heap Scanon  plane planeskeleton  (cost=21.50..2288.29  rows=766  width=52)
                            RecheckCond:(obsid ='00000000-0000-0000-07a6-0143085f9ddf'::uuid)
                            ->   Bitmap Index Scanon  i_obsid  (cost=0.00..21.30  rows=766  width=0)
                                  IndexCond: (obsid ='00000000-0000-0000-07a6-0143085f9ddf'::uuid)
(22  rows)|


**** And the correct plan ( no temp files , no seq scan, exec time 6ms)
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------
  Sort  (cost=24779053.69..24779054.41 rows=289 width=180) (actual 
time=4.539..4.564 rows=264 loops=1)
    Sort Key: planeskeleton.planeid, artifactskeleton.artifactid, 
partskeleton.partid
    Sort Method: quicksort  Memory: 95kB
    ->  Nested Loop Left Join  (cost=2.69..24779041.88 rows=289 
width=180) (actual time=0.375..3.967 rows=264 loops=1)
          Join Filter: (observationskeleton.obsid = planeskeleton.obsid)
          ->  Index Scan using observation_pkey on observation 
observationskeleton  (cost=0.43..6.45 rows=1 width=36) (actual 
time=0.077..0.077 rows=1 loops=1)
                Index Cond: (obsid = 
'00000000-0000-0000-0603-e3ee45c5b6b7'::uuid)
          ->  Nested Loop Left Join  (cost=2.25..24779031.81 rows=289 
width=160) (actual time=0.285..3.702 rows=264 loops=1)
                ->  Index Scan using i_obsid on plane planeskeleton  
(cost=0.56..88.02 rows=28 width=52) (actual time=0.078..0.109 rows=8 
loops=1)
                      Index Cond: (obsid = 
'00000000-0000-0000-0603-e3ee45c5b6b7'::uuid)
                ->  Nested Loop Left Join  (cost=1.69..884948.84 
rows=1344 width=124) (actual time=0.143..0.436 rows=33 loops=8)
                      ->  Nested Loop Left Join (cost=1.13..878643.86 
rows=1344 width=88) (actual time=0.099..0.154 rows=33 loops=8)
                            ->  Index Scan using i_planeid on artifact 
artifactskeleton  (cost=0.56..1077.84 rows=356 width=52) (actual 
time=0.051..0.053 rows=2 loops=8)
                                  Index Cond: (planeskeleton.planeid = 
planeid)
                            ->  Index Scan using i_artifactid on part 
partskeleton  (cost=0.57..2453.44 rows=1163 width=52) (actual 
time=0.035..0.052 rows=22 loops=12)
                                  Index Cond: 
(artifactskeleton.artifactid = artifactid)
                      ->  Index Scan using i_partid on chunk 
chunkskeleton  (cost=0.56..4.68 rows=1 width=52) (actual 
time=0.006..0.007 rows=1 loops=264)
                            Index Cond: (partskeleton.partid = partid)
  Planning time: 8.030 ms
  Execution time: 5.128 ms

Isabella

^ permalink  raw  reply  [nested|flat] 2+ messages in thread

* Re: PG 9.5 same SQL 2 different plans
  2016-08-03 22:20 PG 9.5 same SQL 2 different plans ghiureai <isabella.ghiurea@nrc-cnrc.gc.ca>
@ 2016-08-04 21:40 ` Tom Lane <tgl@sss.pgh.pa.us>
  0 siblings, 0 replies; 2+ messages in thread

From: Tom Lane @ 2016-08-04 21:40 UTC (permalink / raw)
  To: ghiureai <isabella.ghiurea@nrc-cnrc.gc.ca>; +Cc: pgsql-admin

ghiureai <isabella.ghiurea@nrc-cnrc.gc.ca> writes:
> we upgrade to PG 9.5.3,  in last days  we are seeing a strange 
> optimization issues with one of the SQL :
>   running same SQL every  15-20 times optimizer will choose( wrong 
> plan)/ most expensive which  generates approx
> 50 GB temp files  and runs for aprox 20 min , we can not understand the 
> reason ( we run vacuum analyze daily),

It looks like it's flipping between two different plans depending on the
estimate of the number of "planeskeleton" rows matching the particular
"obsid" value you're requesting.  The cost estimates for those plans
aren't that far apart (34M units vs 25M), but reality is way different.

> Pg conf values:
> random_page_cost=3.0
> defalult_statistics_taget=100

I think you have two problems here.  The big one is that the planner is
way overestimating the actual costs of indexscans, which probably means
your database is entirely held in RAM and you ought to knock
random_page_cost down to 1.  (But see the usual caveats that fooling with
cost parameters on the basis of a single example query is dangerous.)
A lesser problem is that the rowcount estimates aren't very close, which
also contributes to overestimating the costs of indexscans.  It's possible
that would get better if you increased default_statistics_target, though
it's hard to be sure.

			regards, tom lane


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2016-08-03 22:20 PG 9.5 same SQL 2 different plans ghiureai <isabella.ghiurea@nrc-cnrc.gc.ca>
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