Use ST_ClusterKMeans for K-means clustering on geometry objects - ApsaraDB RDS

Assigns a cluster ID to each geometry object using the 2D K-means algorithm.

Syntax

integer ST_ClusterKMeans(geometry winset geom, integer numberOfClusters);

Return value: An integer representing the cluster ID assigned to each geometry object.

Parameters

Parameter	Description
`geom`	The geometry objects to cluster.
`numberOfClusters`	The number of clusters to generate.

Usage notes

ST_ClusterKMeans is a window function. Call it with an OVER() clause.
Clustering distance is calculated as the distance between the centroids of the input geometry objects.

Examples

Basic clustering

The following example clusters four 2D points into two groups.

SELECT ST_ClusterKMeans(geom, 2) OVER(), ST_AsText(geom)
FROM (
    SELECT unnest(ARRAY[
        'POINT (0 0)'::geometry,
        'POINT(1 1)'::geometry,
        'POINT (-1 -1)'::geometry,
        'POINT (-2 -2)'::geometry
    ]) AS geom
) AS test;

Output:

 st_clusterkmeans |  st_astext
------------------+--------------
                0 | POINT(0 0)
                0 | POINT(1 1)
                1 | POINT(-1 -1)
                1 | POINT(-2 -2)
(4 rows)