A geospatial aggregation in Elasticsearch is a type of aggregation that enables you to group documents by their geographic location and perform calculations or aggregations on the results. Geospatial aggregations are useful for performing analytics on location-based data, such as customer locations, device locations, or store locations.
Elasticsearch provides several types of geospatial aggregations, including:
1. Geo Distance Aggregation: The geo distance aggregation groups documents by their proximity to a specific location or within a specific distance, and then performs aggregations on the results. For example, you can use the geo distance aggregation to calculate the average price of products sold within 10 kilometers of a specific store location.
2. Geo Bounds Aggregation: The geo bounds aggregation calculates the bounding box that contains all the documents in a given search context, and then performs aggregations on the results. For example, you can use the geo bounds aggregation to calculate the average price of products sold within the bounding box of a specific geographic region.
3. Geo Hash Grid Aggregation: The geo hash grid aggregation groups documents into a grid of cells based on their geographic location, and then performs aggregations on the results. This aggregation is useful for visualizing geospatial data at different zoom levels.
4. Geo Centroid Aggregation: The geo centroid aggregation calculates the centroid of all the documents in a given search context, and then performs aggregations on the results. For example, you can use the geo centroid aggregation to calculate the average price of products sold within the centroid of a specific geographic region.
Overall, geospatial aggregations in Elasticsearch enable you to perform advanced analytics on location-based data and gain insights and value from location-based information. By leveraging the power of geospatial aggregations, organizations can optimize their operations and improve their business outcomes by making data-driven decisions based on location-based insights.