The GeoMesa team would like to announce the release of LocationTech GeoMesa version 1.3.0. This minor release ships with the following significant new functionality.
- Deep integration with Spark SQL's Catalyst optimizer to enable efficient provisioning and analysis of spatial data frames over massive data sets. Users can filter, join, transform, and aggregate spatial data sets using standard SQL and many spatial functions in a manner similar to PostGIS:
select id,geom.st_buffer(geom,10) from geomesa_table where st_contains(geom,'POLYGON(())')
- Integration with notebook servers such as Jupyter and Zeppelin to enable ad-hoc interactive analysis and visualization of massive spatial data sets.
First class GeoJSON support
Refactored Index API and corresponding maturation of HBase, Bigtable, and Cassandra backends
Additionally, 1.3.0 includes many performance improvements and bug fixes. Check out this report for a list of issues closed.