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I am new to Postgres and I am trying to understand the
Explain Analyze so I can tune the following query. I run the same query using
mysql and it takes less than 50ms. I run it on postgres and it takes 10
seconds. I feel like I am missing something very obvious. (VehicleUsed is a big
table over 750,000records) and datasetgroupyearmakemodel has 150000 records. It looks like the cost is highest in the Hash Join on
Postalcode. Am I reading this correctly.? I do have indexes on the
lower(postalcode) in both tables. Why wouldn’t be using the index? Thanks
in advance for any help. Here is my query: select distinct VehicleMake.VehicleMake from VehicleUsed inner join PostalCodeRegionCountyCity on ( lower (
VehicleUsed.PostalCode ) = lower ( PostalCodeRegionCountyCity.PostalCode ) ) INNER JOIN DATASETGROUPYEARMAKEMODEL ON (
VEHICLEUSED.VEHICLEYEAR = DATASETGROUPYEARMAKEMODEL.VEHICLEYEAR ) AND ( VEHICLEUSED.VEHICLEMAKEID =
DATASETGROUPYEARMAKEMODEL.VEHICLEMAKEID ) AND ( VEHICLEUSED.VEHICLEMODELID =
DATASETGROUPYEARMAKEMODEL.VEHICLEMODELID ) inner join VehicleMake on ( VehicleUsed.VehicleMakeId =
VehicleMake.VehicleMakeId ) where ( DatasetGroupYearMakeModel.DatasetGroupId = 3 ) and ( VehicleUsed.DatasetId <> 113 ) and ( VehicleUsed.ProductGroupId <> 13 ) and ( PostalCodeRegionCountyCity.RegionId = 36 ) order by VehicleMake.VehicleMake limit 500000 Here is the explain analyze "Limit (cost=38292.53..38293.19 rows=261 width=8)
(actual time=10675.857..10675.892 rows=42 loops=1)" " -> Sort (cost=38292.53..38293.19 rows=261
width=8) (actual time=10675.855..10675.868 rows=42 loops=1)" " Sort Key: vehiclemake.vehiclemake" " Sort Method: quicksort Memory: 18kB" " -> HashAggregate (cost=38279.45..38282.06
rows=261 width=8) (actual time=10675.710..10675.728 rows=42 loops=1)" " -> Hash Join (cost=436.31..38270.51
rows=3576 width=8) (actual time=4.471..10658.291 rows=10425 loops=1)" " Hash Cond:
(vehicleused.vehiclemakeid = vehiclemake.vehiclemakeid)" " -> Hash Join
(cost=428.43..38213.47 rows=3576 width=4) (actual time=4.152..10639.742
rows=10425 loops=1)" " Hash Cond:
(lower((vehicleused.postalcode)::text) =
lower((postalcoderegioncountycity.postalcode)::text))" " -> Nested Loop
(cost=101.81..37776.78 rows=11887 width=10) (actual time=1.172..9876.586
rows=382528 loops=1)" " -> Bitmap Heap
Scan on datasetgroupyearmakemodel (cost=101.81..948.81 rows=5360 width=6)
(actual time=0.988..17.800 rows=5377 loops=1)" " Recheck Cond:
(datasetgroupid = 3)" " -> Bitmap
Index Scan on datasetgroupyearmakemodel_i04 (cost=0.00..100.47 rows=5360
width=0) (actual time=0.830..0.830 rows=5377 loops=1)" " Index
Cond: (datasetgroupid = 3)" " -> Index Scan
using vehicleused_i10 on vehicleused (cost=0.00..6.85 rows=1 width=12) (actual
time=0.049..1.775 rows=71 loops=5377)" " Index Cond:
((vehicleused.vehiclemodelid = datasetgroupyearmakemodel.vehiclemodelid) AND
(vehicleused.vehiclemakeid = datasetgroupyearmakemodel.vehiclemakeid) AND
(vehicleused.vehicleyear = datasetgroupyearmakemodel.vehicleyear))" " Filter:
((vehicleused.datasetid <> 113) AND (vehicleused.productgroupid <>
13))" " -> Hash
(cost=308.93..308.93 rows=1416 width=6) (actual time=2.738..2.738 rows=1435
loops=1)" " -> Bitmap Heap
Scan on postalcoderegioncountycity (cost=27.23..308.93 rows=1416 width=6)
(actual time=0.222..0.955 rows=1435 loops=1)" " Recheck Cond:
(regionid = 36)" " -> Bitmap
Index Scan on postalcoderegioncountycity_i05 (cost=0.00..26.87 rows=1416
width=0) (actual time=0.202..0.202 rows=1435 loops=1)" " Index
Cond: (regionid = 36)" " -> Hash (cost=4.61..4.61
rows=261 width=10) (actual time=0.307..0.307 rows=261 loops=1)" " -> Seq Scan on
vehiclemake (cost=0.00..4.61 rows=261 width=10) (actual time=0.033..0.154
rows=261 loops=1)" "Total runtime: 10676.058 ms"
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