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GeoSpark is a cluster computing system for processing large-scale spatial data. GeoSpark extends Apache Spark / SparkSQL with a set of out-of-the-box Spatial Resilient Distributed Datasets (SRDDs)/ SpatialSQL that efficiently load, process, and analyze large-scale spatial data across machines.

GeoSpark contains several modules:

Name API Spark compatibility Dependency
GeoSpark-core RDD Spark 2.X/1.X Spark-core
GeoSpark-SQL SQL/DataFrame SparkSQL 2.1 and later Spark-core, Spark-SQL, GeoSpark-core
GeoSpark-Viz RDD, SQL/DataFrame RDD - Spark 2.X/1.X, SQL - Spark 2.1 and later Spark-core, Spark-SQL, GeoSpark-core, GeoSpark-SQL
GeoSpark-Zeppelin Apache Zeppelin Spark 2.1+, Zeppelin 0.8.1+ Spark-core, Spark-SQL, GeoSpark-core, GeoSpark-SQL, GeoSpark-Viz
  • Core: GeoSpark SpatialRDDs and Query Operators.
  • SQL: SQL interfaces for GeoSpark core.
  • Viz: Visualization extension of GeoSpark Spatial RDD and DataFrame.
  • GeoSpark-Zeppelin: GeoSpark visualization plugin for Apache Zeppelin

Please visit GeoSpark website for details and documentations.

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GeoSpark development team has published four papers about GeoSpark. Please read Publications.

GeoSpark received an evaluation from PVLDB 2018 paper "How Good Are Modern Spatial Analytics Systems?" Varun Pandey, Andreas Kipf, Thomas Neumann, Alfons Kemper (Technical University of Munich), quoted as follows:

GeoSpark comes close to a complete spatial analytics system. It also exhibits the best performance in most cases.