Spatial Connected Components Scala Object

Spatial connected components identify groups of geometries that are transitively connected through a spatial predicate. Unlike density-based clustering (DBSCAN), they do not require a minimum density: any chain of pairwise-related geometries forms a single component. The spatialConnectedComponents method adds a component ID to each row in a DataFrame.

def spatialConnectedComponents(
      dataframe: DataFrame,
      predicate: String,
      geometry: String = null,
      componentColumnName: String = "component_id",
      distance: Double = 0.0,
      useSpheroid: Boolean = false,
      partitionColumn: String = null): DataFrame

Parameters

DataFrame

DataFrame containing at least one geometry column. All rows must be unique.

String

Spatial predicate to use for connectivity. One of: "intersects", "touches", "overlaps", "contains", "covers", "within", "coveredby", "crosses", or "dwithin".

String

Name of the geometry column.If not provided, the algorithm automatically selects the geometry column:

If only one GeometryType column exists, it is used.
If multiple GeometryType columns exist and one is named geometry, it is used.
If multiple GeometryType columns exist and none are named geometry, the column name must be explicitly provided.

String

Name of the output column for the component ID. Default is "component_id".

Double

Distance threshold for the "dwithin" predicate. Ignored for other predicates. Default is 0.0.

Boolean

Whether to use spheroidal distance for the "dwithin" predicate. Default is false.

String

Optional column name for partitioning. When non-null, only rows with the same value in this column are considered for edge construction. Default is null.

Returns

The input DataFrame with a component ID column (BIGINT) added. Every row receives a component ID, including singletons.

Usage Examples

import org.apache.sedona.stats.clustering.SpatialConnectedComponents.spatialConnectedComponents

// Intersection-based connected components
val result = spatialConnectedComponents(dataframe, "intersects")

// Distance-based connected components
val result = spatialConnectedComponents(dataframe, "dwithin", distance = 1.0)

// With partition column for performance
val result = spatialConnectedComponents(dataframe, "intersects", partitionColumn = "state")

Column Function API

The ST_*CC functions are also available as Spark column functions via st_functions:

import org.apache.spark.sql.sedona_sql.expressions.st_functions._

// Intersection-based predicate
val result = df.select(col("*"), ST_IntersectsCC(col("geometry")).as("component_id"))

// With partition_by
val result = df.select(
  col("*"),
  ST_IntersectsCC(col("geometry"), col("category")).as("component_id")
)

// Distance-based
val result = df.select(
  col("*"),
  ST_DWithinCC(col("geometry"), lit(1.0), lit(false)).as("component_id")
)

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Rasterflow

Spatial Connected Components Scala Object

Parameters

Returns

Usage Examples

Column Function API

​Parameters

​Returns

​Usage Examples

​Column Function API

Parameters

Returns

Usage Examples

Column Function API