Point clustering - basic configuration
This sample demonstrates how to enable point clustering on a GeoJSONLayer. Clustering is a method of reducing points in a FeatureLayer, CSVLayer, GeoJSONLayer, WFSLayer, or OGCFeatureLayer by grouping them based on their spatial proximity to one another. Typically, clusters are proportionally sized based on the number of features within each cluster.
Clustering is configured in the featureReduction property of the layer. You can enable clustering with a default configuration with minimal code by setting the type to cluster
.
The feature reduction property gives you control over many other cluster properties. The clusterRadius defines area of influence that determines each cluster's region for including features. You may also define popupTemplates and labels for clusters that summarize the features comprised by the cluster.
Suggestions for basic configuration
- Turn off label deconfliction when labeling clusters with a count in the center of the cluster. If label placement is outside the cluster, keep label deconfliction enabled.
- Increase the clusterMinSize to fit labels inside smaller clusters (16pt is a good starting point).
- For larger layers, format the cluster count in the label with either a rounded value or a meaningful abbreviated value (e.g.
10k
instead of10000
). See the Point clustering - generate suggested configuration for an example of this.
Point clustering only applies to layers with point
geometries in a MapView containing either a SimpleRenderer, UniqueValueRenderer, or a ClassBreaksRenderer. It does not apply to layers with polyline and polygon geometries.
Related samples and resources

Point clustering - filter popup features
This sample demonstrates how to filter clustered features within a cluster's popup.

Point clustering - generate suggested configuration
Point clustering - generate suggested configuration

Point clustering - query clusters
Point clustering - query clusters

Point clustering - advanced configuration
Point clustering - advanced configuration

Popup charts for point clusters
This sample demonstrates how to summarize clustered features using charts within a cluster's popup.

Point clustering with visual variables
Point clustering with visual variables
FeatureReductionCluster
Read the API Reference for more information.