Spatially Stratified Sampling Scala Object

`spatiallyStratifiedSample`

Spatially stratified sampling of a DataFrame containing spatial data. DataFrame containing spatial data to be sampled. Must contain a geometryColumn column. SpatiallyStratifiedSampling rate between 0 and 1 Number of partitions to divide the data into. If not a perfect square, the number of partitions in each dimension will be rounded to the nearest integer. Column containing the geometry data. Default is “geometry” Seed for sampling the data

def spatiallyStratifiedSample(
      dataframe: Dataset[Row],
      fraction: Double,
      partitionCount: Int,
      geometry: String = null,
      seed: Long = 42): Dataset[Row] =

Parameters

Dataset[Row]

DataFrame containing spatial data to be sampled. Must contain a geometryColumn column.

Double

SpatiallyStratifiedSampling rate between 0 and 1

Int

Number of partitions to divide the data into. If not a perfect square, the number of partitions in each dimension will be rounded to the nearest integer.

String

Column containing the geometry data. Default is “geometry”

Long

Seed for sampling the data

Returns

The input DataFrame sampled down to the specified rate

Usage Examples

import org.apache.sedona.stats.clustering.SpatiallyStratifiedSampling

// Example usage
val result = SpatiallyStratifiedSampling.spatiallyStratifiedSample(dataframe, epsilon, minPts)

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Spatially Stratified Sampling Scala Object

`spatiallyStratifiedSample`

Parameters

Returns

Usage Examples

​spatiallyStratifiedSample

​Parameters

​Returns

​Usage Examples

`spatiallyStratifiedSample`

Parameters

Returns

Usage Examples