Merge pull request #106 from jiayuasu/GeoSpark-for-Spark-1.X

Push GeoSpark 0.8.0 and Babylon 0.2.1 for Spark 1.X
tree: 18066e194879c230e57205d76ec460f517e49971
  1. babylon/
  2. core/
  3. .gitignore
  4. .travis.yml
  5. LICENSE
  6. pom.xml
  7. README.md
README.md

GeoSpark Logo

VersionGeoSpark CoreBabylon Viz System
Stable0.7.00.2.0
LatestMaven CentralMaven Central
Source codeBuild StatusBuild Status

Join the chat at https://gitter.im/geospark-datasys/Lobby

Supported Apache Spark version: 2.0+(Master branch) 1.0+(1.X branch)

GeoSpark is listed as Infrastructure Project on Apache Spark Official Third Party Project Page

GeoSpark is a cluster computing system for processing large-scale spatial data. GeoSpark extends Apache Spark with a set of out-of-the-box Spatial Resilient Distributed Datasets (SRDDs) that efficiently load, process, and analyze large-scale spatial data across machines. GeoSpark provides APIs for Apache Spark programmer to easily develop their spatial analysis programs with Spatial Resilient Distributed Datasets (SRDDs) which have in house support for geometrical and Spatial Queries (Range, K Nearest Neighbors, Join).

GeoSpark artifacts are hosted in Maven Central: Maven Central Coordinates

Version release notes: click here

News!

  • GeoSpark (0.6.2 and later) is able to load, query and save NASA Petabytes NetCDF/HDF Earth Data! (Scala Example,Java Example)
  • Babylon (0.2.0 and later) is able to visualize NASA Petabytes NetCDF/HDF Earth Data and output to distributed PNG/SVG images! (Scala Example,Java Example)

Important features (more)

Spatial Resilient Distributed Datasets (SRDDs)

Supported Spatial RDDs: PointRDD, RectangleRDD, PolygonRDD, LineStringRDD

Supported input data format

Native input format support: CSV, TSV, WKT, GeoJSON, NASA Earth Data NetCDF/HDF (New!)

User-supplied input format mapper: Any input formats

Spatial Partitioning

Supported Spatial Partitioning techniques: R-Tree, Voronoi diagram, Uniform grids (Experimental), Hilbert Curve (Experimental)

Spatial Index

Supported Spatial Indexes: Quad-Tree and R-Tree. R-Tree supports Spatial K Nearest Neighbors query.

Geometrical operation

Inside, Overlap, DatasetBoundary, Minimum Bounding Rectangl, Polygon Union

Spatial Operation

Spatial Range Query, Spatial Join Query, and Spatial K Nearest Neighbors Query.

Coordinate Reference System (CRS) Transformation (aka. Coordinate projection)

GeoSpark allows users to transform the original CRS (e.g., degree based coordinates such as EPSG:4326 and WGS84) to any other CRS (e.g., meter based coordinates such as EPSG:3005) so that it can accurately process both geographic data and geometrical data. Please specify your desired CRS in GeoSpark Spatial RDD constructor (Example).

Users

Companies that are using GeoSpark (incomplete list)

Please make a Pull Request to add yourself!

GeoSpark Tutorial (more)

GeoSpark full tutorial is available at GeoSpark GitHub Wiki: https://github.com/DataSystemsLab/GeoSpark/wiki

Babylon Visualization System on GeoSpark

Babylon is a large-scale in-memory geospatial visualization system.

Babylon provides native support for general cartographic design by extending GeoSpark to process large-scale spatial data. It can visulize Spatial RDD and Spatial Queries and render super high resolution image in parallel.

Babylon and GeoSpark are integrated together. You just need to import GeoSpark and enjoy them! More details are available here: Babylon GeoSpatial Visualization

Babylon Gallery

Publication

Jia Yu, Jinxuan Wu, Mohamed Sarwat. “A Demonstration of GeoSpark: A Cluster Computing Framework for Processing Big Spatial Data”. (demo paper) In Proceeding of IEEE International Conference on Data Engineering ICDE 2016, Helsinki, FI, May 2016

Jia Yu, Jinxuan Wu, Mohamed Sarwat. “GeoSpark: A Cluster Computing Framework for Processing Large-Scale Spatial Data”. (short paper) In Proceeding of the ACM International Conference on Advances in Geographic Information Systems ACM SIGSPATIAL GIS 2015, Seattle, WA, USA November 2015

Acknowledgement

GeoSpark makes use of JTS Plus (An extended JTS Topology Suite Version 1.14) for some geometrical computations.

Please refer to JTS Topology Suite website and JTS Plus for more details.

Contact

Questions

  • Please join Join the chat at https://gitter.im/geospark-datasys/Lobby

  • Email us!

Contact

Project website

Please visit GeoSpark project wesbite for latest news and releases.

Data Systems Lab

GeoSpark is one of the projects under Data Systems Lab at Arizona State University. The mission of Data Systems Lab is designing and developing experimental data management systems (e.g., database systems).

Thanks for the help from GeoSpark community

We appreciate the help and suggestions from GeoSpark users: Thanks List