CODEWITHSUNDEEP
postgresqlquery-optimizationquery-performance
adaminasabi
adaminasabi

Reputation: 39

postgresql hashaggregate query optimization

I am trying to optimize the query below.

select cellid2 as cellid, max(endeks) as turkcell 
from (select a.cellid2 as cellid2, b.endeks 
    from (select geom, cellid as cellid2 from grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000 ) a join (select endeks, st_transform(geom,    2320) as geom_tmp from  turkcell_data ) b on st_intersects(a.geom, b.geom_tmp) ) x
group by cellid2 limit 5

and explain analyze returns

"Limit  (cost=81808.31..81808.36 rows=5 width=12) (actual time=271376.201..271376.204 rows=5 loops=1)"
"  ->  HashAggregate  (cost=81808.31..81879.63 rows=7132 width=12) (actual time=271376.200..271376.203 rows=5 loops=1)"
"        ->  Nested Loop  (cost=0.00..81772.65 rows=7132 width=12) (actual time=5.128..269753.647 rows=1237707 loops=1)"
"              Join Filter: _st_intersects(grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000.geom, st_transform(turkcell_data.geom, 2320))"
"              ->  Seq Scan on turkcell_data  (cost=0.00..809.40 rows=3040 width=3045) (actual time=0.031..7.426 rows=3040 loops=1)"
"              ->  Index Scan using grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_geom_gist on grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000  (cost=0.00..24.76 rows=7 width=124) (actual time=0.012..0.799 rows=647 loops=3040)"
"                    Index Cond: (geom && st_transform(turkcell_data.geom, 2320))"
"Total runtime: 271387.499 ms"

There exist indexes on geometry column and cellid columns. I read that instead of using max, order by desc and limit 1 works better. However, since I have group by clause, it does not work I think. Is there any way to do this or any other way which improves the performance?

Table Definitions:

CREATE TABLE grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000
(
  regionid numeric,
  geom geometry(Geometry,2320),
  cellid integer,
  turkcell double precision
)
WITH (
  OIDS=FALSE
);
ALTER TABLE grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000
  OWNER TO postgres;

-- Index: grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_cellid

-- DROP INDEX grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_cellid;

CREATE INDEX grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_cellid
  ON grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000
  USING btree
  (cellid );

-- Index: grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_geom_gist

-- DROP INDEX grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_geom_gist;

CREATE INDEX grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000_geom_gist
  ON grd_90098780_7c48_11e3_8876_f0bf97e0dd001000000000
  USING gist
  (geom );

CREATE TABLE turkcell_data
(
  gid serial NOT NULL,
  objectid_1 integer,
  objectid integer,
  neighbourh numeric,
  endeks numeric,
  coorx numeric,
  coory numeric,
  shape_leng numeric,
  shape_le_1 numeric,
  shape_area numeric,
  geom geometry(MultiPolygon,4326),
  CONSTRAINT turkcell_data_pkey PRIMARY KEY (gid )
)
WITH (
  OIDS=FALSE
);
ALTER TABLE turkcell_data
  OWNER TO postgres;

-- Index: turkcell_data_geom_gist

-- DROP INDEX turkcell_data_geom_gist;

CREATE INDEX turkcell_data_geom_gist
  ON turkcell_data
  USING gist
  (geom );

Upvotes: 2

Views: 3328

Answers (1)

yieldsfalsehood
yieldsfalsehood

Reputation: 3085

Either store your data re-projected to 2320, index that column, and use it in your join, or create an index on the transformed projection of the geometry in turkcell_data. I usually prefer the latter:

CREATE INDEX turkcell_data_geom_gist2320
  ON turkcell_data
  USING gist
  (st_transform(geom, 2320) );

The other issue might be if your geometries are very complex - if any of your polygons have a relatively large number of points you might get stuck crunching away on the intersection. Try the index first, though.

Upvotes: 2

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