clustering
CORE
This module contains functions that perform clustering on geographies.
ST_CLUSTERKMEANS(geog, numberOfClusters)
Description
Takes a set of points as input and partitions them into clusters using the k-means algorithm. Returns an array of tuples with the cluster index for each of the input features and the input geometry.
geog:ARRAY<GEOGRAPHY>points to be clustered.numberOfClusters:INT64|NULLnumberOfClusters that will be generated. IfNULLthe default valueMath.sqrt(<NUMBER OF POINTS>/2)is used.
Return type
ARRAY<STRUCT<cluster INT64, geom GEOGRAPHY>>Example
carto-un
carto-un-eu
carto-os
manual
SELECT `carto-un`.carto.ST_CLUSTERKMEANS([ST_GEOGPOINT(0, 0), ST_GEOGPOINT(0, 1), ST_GEOGPOINT(5, 0), ST_GEOGPOINT(1, 0)], 2);
-- {cluster: 1, geom: POINT(0 0)}
-- {cluster: 1, geom: POINT(0 1)}
-- {cluster: 0, geom: POINT(5 0)}
-- {cluster: 1, geom: POINT(1 0)}
SELECT `carto-un-eu`.carto.ST_CLUSTERKMEANS([ST_GEOGPOINT(0, 0), ST_GEOGPOINT(0, 1), ST_GEOGPOINT(5, 0), ST_GEOGPOINT(1, 0)], 2);
-- {cluster: 1, geom: POINT(0 0)}
-- {cluster: 1, geom: POINT(0 1)}
-- {cluster: 0, geom: POINT(5 0)}
-- {cluster: 1, geom: POINT(1 0)}
SELECT `carto-os`.carto.ST_CLUSTERKMEANS([ST_GEOGPOINT(0, 0), ST_GEOGPOINT(0, 1), ST_GEOGPOINT(5, 0), ST_GEOGPOINT(1, 0)], 2);
-- {cluster: 1, geom: POINT(0 0)}
-- {cluster: 1, geom: POINT(0 1)}
-- {cluster: 0, geom: POINT(5 0)}
-- {cluster: 1, geom: POINT(1 0)}
SELECT carto.ST_CLUSTERKMEANS([ST_GEOGPOINT(0, 0), ST_GEOGPOINT(0, 1), ST_GEOGPOINT(5, 0), ST_GEOGPOINT(1, 0)], 2);
-- {cluster: 1, geom: POINT(0 0)}
-- {cluster: 1, geom: POINT(0 1)}
-- {cluster: 0, geom: POINT(5 0)}
-- {cluster: 1, geom: POINT(1 0)}
Additional examples
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 960401.
Last modified 1mo ago