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A cluster computing framework for processing large-scale geospatial data

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Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona equips cluster computing systems such as Apache Spark and Apache Flink with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines.

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Apache Sedona 180k/month Downloads Downloads
Archived GeoSpark releases 10k/month DownloadsDownloads

System architecture

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Modules in the source code

Name API Introduction
Core Scala/Java Distributed Spatial Datasets and Query Operators
SQL Spark RDD/DataFrame in Scala/Java/SQL Geospatial data processing on Apache Spark
Flink Flink DataStream/Table in Scala/Java/SQL Geospatial data processing on Apache Flink
Viz Spark RDD/DataFrame in Scala/Java/SQL Geospatial data visualization on Apache Spark
Python Spark RDD/DataFrame in Python Python wrapper for Sedona
R Spark RDD/DataFrame in R R wrapper for Sedona
Zeppelin Apache Zeppelin Plugin for Apache Zeppelin 0.8.1+

Sedona supports several programming languages: Scala, Java, SQL, Python and R.

Compile the source code

Please refer to Sedona website

Contact

Feedback to improve Apache Sedona: Google Form

Twitter: Sedona@Twitter

Sedona JIRA: Bugs, Pull Requests, and other similar issues

Sedona Mailing Lists: [email protected]: project development, general questions or tutorials.

  • Please first subscribe and then post emails. To subscribe, please send an email (leave the subject and content blank) to [email protected]

Please visit Apache Sedona website for detailed information

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  • Java 38.3%
  • Scala 27.9%
  • Python 18.1%
  • Jupyter Notebook 9.8%
  • R 3.5%
  • C 2.0%
  • Other 0.4%