Hexagonal spatial analytics in Elasticsearch
Blog post from Elastic
Elasticsearch 8.7.0 has introduced advanced hexagonal spatial analytics through the integration of the Uber H3 library, enhancing the capability to perform geo-spatial aggregations on a hexagonal grid, which offers significant advantages over traditional rectangular grids. Initially, the H3 library was ported from C to Java and integrated into Elasticsearch and Kibana, allowing for geo-point aggregations, but the recent update now supports geo_shape aggregations. This transition required performance enhancements through code refactoring and optimization of trigonometric calculations. The hexagonal grid system offers a more consistent area and distance between tiles globally, providing more accurate statistical results compared to rectangular grids. Kibana also supports these enhancements, enabling users to visualize and compare geohex and geotile aggregations, offering a more robust toolset for geospatial data analysis.