commit | 2546b10ae8c78ec447549cdf391ba0c3c9eca9eb | [log] [tgz] |
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author | Jia Yu <jiayu2@asu.edu> | Mon Mar 04 02:36:53 2019 -0700 |
committer | Jia Yu <jiayu2@asu.edu> | Mon Mar 04 02:36:53 2019 -0700 |
tree | adc4c43751bed3cf3e5221db12f6164bcc8bc952 | |
parent | aa9ec969d6c6eacfee6306c7bd4e4985a0d460c7 [diff] |
Adjust the code to Spark 2.2 API
Stable | Latest | Source code |
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GeoSpark@Twitter || GeoSpark Discussion Board || || (since Jan. 2018)
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 |
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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 |
Please visit GeoSpark website for details and documentations.
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.