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A Cluster Computing System for Processing Large-Scale Spatial Data

License: Apache License 2.0

Java 74.26% Scala 18.30% JavaScript 0.42% Jupyter Notebook 1.42% Shell 0.05% Python 5.56%

geospark-1's Introduction

Stable	Latest	Source code

GeoSpark@Twitter || GeoSpark Discussion Board ||

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	Introduction
Core	RDD	Spark 2.X/1.X	SpatialRDDs and Query Operators.
SQL	SQL/DataFrame	SparkSQL 2.1+	SQL interfaces for GeoSpark core.
Viz	RDD, SQL/DataFrame	RDD - Spark 2.X/1.X, SQL - Spark 2.1+	Visualization for Spatial RDD and DataFrame.
Zeppelin	Apache Zeppelin	Spark 2.1+, Zeppelin 0.8.1+	GeoSpark plugin for Apache Zeppelin

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

Please visit GeoSpark website for detailed documentations

News!

A research paper about "GeoSparkSim: A Microscopic Road Network Traffic Simulator in Apache Spark" is accepted to MDM 2019, Hong Kong China. The next release of GeoSpark will come with a built-in scalable traffic simulator. Please stay tuned!
A 1.5-hour tutorial about "Geospatial Data Management in Apache Spark" was presented by Jia Yu and Mohamed Sarwat in ICDE 2019, Macau, China. Visit our tutorial website to learn how to craft your "GeoSpark" from scratch.
GeoSpark 1.2.0 is released.