Hi Filip, On 2011-10-08, at 2:26 AM, Filip Rembiałkowski wrote:
> Any suggests how to speed it up? Coming from MySQL, I'm brand-new to PostGIS > (and Postgresql FWIW) and all the awesome spatial functions it has. I would > think that maybe selecting a bounding box of rows, and then finding the one > with the closest distance? > > > Yes exactly. That's how people do it now, in pre-PostGIS-2.0 era :-) > > Make a search by bounding boxes, starting with some arbitraly selected > radius. Increase the radius until you have at least N=1 result found, than > sort these results by ST_Distance and select nearest neighbour. > > PostGIS 2.0 solution: see > http://blog.opengeo.org/2011/09/28/indexed-nearest-neighbour-search-in-postgis/ Thanks. Based on some further reading, this is what I came up with, in order to hopefully use the GiST index to greatest benefit: gc3=# SELECT datasetnam, r_hnumf, r_hnuml, r_stname_c, r_placenam, ST_Distance(ST_GeomFromText('POINT(-114.053205 51.069644)',4269),the_geom) AS distance gc3-# FROM nrn_ab_8_0_roadseg gc3-# WHERE the_geom && SetSRID('BOX3D(-114.1 49.9,-113.9 51.1)'::box3d,4269) gc3-# ORDER BY distance ASC LIMIT 5; datasetnam | r_hnumf | r_hnuml | r_stname_c | r_placenam | distance ------------+---------+---------+----------------------+------------+---------------------- Alberta | 407 | 459 | 19 Avenue North-east | Calgary | 5.74515867479735e-05 Alberta | 2004 | 2004 | 4 Street North-east | Calgary | 0.000663366090673065 Alberta | 0 | 0 | 4 Street North-east | Calgary | 0.000667603774783403 Alberta | 425 | 425 | 18 Avenue North-east | Calgary | 0.000835708003512673 Alberta | 407 | 449 | 20 Avenue North-east | Calgary | 0.000981910679856406 (5 rows) gc3=# EXPLAIN SELECT datasetnam, r_hnumf, r_hnuml, r_stname_c, r_placenam, ST_Distance(ST_GeomFromText('POINT(-114.053205 51.069644)',4269),the_geom) AS distance gc3-# FROM nrn_ab_8_0_roadseg gc3-# WHERE the_geom && SetSRID('BOX3D(-114.1 49.9,-113.9 51.1)'::box3d,4269) gc3-# ORDER BY distance ASC LIMIT 5; QUERY PLAN -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Limit (cost=33632.15..33632.16 rows=5 width=480) -> Sort (cost=33632.15..33693.00 rows=24341 width=480) Sort Key: (st_distance('0101000020AD100000F5BEF1B567835CC06A2E3718EA884940'::geometry, the_geom)) -> Bitmap Heap Scan on nrn_ab_8_0_roadseg (cost=812.99..33227.85 rows=24341 width=480) Recheck Cond: (the_geom && '0103000020AD10000001000000050000006666666666865CC03333333333F348406666666666865CC0CDCCCCCCCC8C49409A99999999795CC0CDCCCCCCCC8C49409A99999999795CC03333333333F348406666666666865CC03333333333F34840'::geometry) -> Bitmap Index Scan on nrn_ab_8_0_roadseg_the_geom_gist (cost=0.00..806.91 rows=24341 width=0) Index Cond: (the_geom && '0103000020AD10000001000000050000006666666666865CC03333333333F348406666666666865CC0CDCCCCCCCC8C49409A99999999795CC0CDCCCCCCCC8C49409A99999999795CC03333333333F348406666666666865CC03333333333F34840'::geometry) (7 rows) Does this appear optimal to you? Best regards, René Fournier
