postgresql hashaggregate query optimization - postgresql

Question

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 );

Answer 1

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.