<->
Name
<-> — Returns the 2D distance between A and B.
Synopsis
double precision
<->
(
geometry
A
,
geometry
B
)
;
double precision
<->
(
geography
A
,
geography
B
)
;
Description
The
<->
operator returns the 2D distance between
two geometries. Used in the "ORDER BY" clause provides index-assisted
nearest-neighbor result sets. For PostgreSQL below 9.5 only gives
centroid distance of bounding boxes and for PostgreSQL 9.5+, does true
KNN distance search giving true distance between geometries, and distance
sphere for geographies.
Index only kicks in if one of the geometries is a constant (not in a subquery/cte). e.g. 'SRID=3005;POINT(1011102 450541)'::geometry instead of a.geom |
Refer to OpenGeo workshop: Nearest-Neighbour Searching for real live example.
Enhanced: 2.2.0 -- True KNN ("K nearest neighbor") behavior for geometry and geography for PostgreSQL 9.5+. Note for geography KNN is based on sphere rather than spheroid. For PostgreSQL 9.4 and below, geography support is new but only supports centroid box.
Changed: 2.2.0 -- For PostgreSQL 9.5 users, old Hybrid syntax may be slower, so you'll want to get rid of that hack if you are running your code only on PostGIS 2.2+ 9.5+. See examples below.
Availability: 2.0.0 -- Weak KNN provides nearest neighbors based on geometry centroid distances instead of true distances. Exact results for points, inexact for all other types. Available for PostgreSQL 9.1+
Examples
SELECT ST_Distance(geom, 'SRID=3005;POINT(1011102 450541)'::geometry) as d,edabbr, vaabbr FROM va2005 ORDER BY d limit 10; d | edabbr | vaabbr ------------------+--------+-------- 0 | ALQ | 128 5541.57712511724 | ALQ | 129A 5579.67450712005 | ALQ | 001 6083.4207708641 | ALQ | 131 7691.2205404848 | ALQ | 003 7900.75451037313 | ALQ | 122 8694.20710669982 | ALQ | 129B 9564.24289057111 | ALQ | 130 12089.665931705 | ALQ | 127 18472.5531479404 | ALQ | 002 (10 rows)
Then the KNN raw answer:
SELECT st_distance(geom, 'SRID=3005;POINT(1011102 450541)'::geometry) as d,edabbr, vaabbr FROM va2005 ORDER BY geom <-> 'SRID=3005;POINT(1011102 450541)'::geometry limit 10; d | edabbr | vaabbr ------------------+--------+-------- 0 | ALQ | 128 5541.57712511724 | ALQ | 129A 5579.67450712005 | ALQ | 001 6083.4207708641 | ALQ | 131 7691.2205404848 | ALQ | 003 7900.75451037313 | ALQ | 122 8694.20710669982 | ALQ | 129B 9564.24289057111 | ALQ | 130 12089.665931705 | ALQ | 127 18472.5531479404 | ALQ | 002 (10 rows)
If you run "EXPLAIN ANALYZE" on the two queries you would see a performance improvement for the second.
For users running with PostgreSQL < 9.5, use a hybrid query to find the true nearest neighbors. First a CTE query using the index-assisted KNN, then an exact query to get correct ordering:
WITH index_query AS ( SELECT ST_Distance(geom, 'SRID=3005;POINT(1011102 450541)'::geometry) as d,edabbr, vaabbr FROM va2005 ORDER BY geom <-> 'SRID=3005;POINT(1011102 450541)'::geometry LIMIT 100) SELECT * FROM index_query ORDER BY d limit 10; d | edabbr | vaabbr ------------------+--------+-------- 0 | ALQ | 128 5541.57712511724 | ALQ | 129A 5579.67450712005 | ALQ | 001 6083.4207708641 | ALQ | 131 7691.2205404848 | ALQ | 003 7900.75451037313 | ALQ | 122 8694.20710669982 | ALQ | 129B 9564.24289057111 | ALQ | 130 12089.665931705 | ALQ | 127 18472.5531479404 | ALQ | 002 (10 rows)