Elasticsearch 2.2 introduces significant improvements to its geospatial capabilities, particularly with the enhancement of geo_point fields through a new GeoPointField type built on the internal inverted index structure. This update leverages a quad-tree raster graphics approach to encode latitude and longitude values, improving efficiency and reducing index size by minimizing the terms dictionary. The two-phase query approach has been optimized to maximize the coverage area and minimize brute force checks, resulting in better performance for complex geo queries. Additionally, the update streamlines mapping parameters by removing or simplifying certain options, such as coerce and doc_values, which are now inherently managed by the new structure. Despite these advancements, ongoing efforts aim to further enhance Elasticsearch’s geospatial capabilities with specialized data structures for multi-dimensional spatial data in future releases.