A demonstration of GeoSpark: A cluster computing framework for processing big spatial data

Jia Yu; Jinxuan Wu; Mohamed Elsayed

doi:10.1109/ICDE.2016.7498357

A demonstration of GeoSpark: A cluster computing framework for processing big spatial data

Jia Yu, Jinxuan Wu, Mohamed Elsayed

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

32 Scopus citations

Abstract

This paper demonstrates GEOSPARK a cluster computing framework for developing and processing large-scale spatial data analytics programs. GEOSPARK consists of three main layers: Apache Spark Layer, Spatial RDD Layer and Spatial Query Processing Layer. Apache Spark Layer provides basic Apache Spark functionalities as regular RDD operations. Spatial RDD Layer consists of three novel Spatial Resilient Distributed Datasets (SRDDs) which extend regular Apache Spark RDD to support geometrical and spatial objects with data partitioning and indexing. Spatial Query Processing Layer executes spatial queries (e.g., Spatial Join) on SRDDs. The dynamic status of SRDDs and spatial operations are visualized by GEOSPARK monitoring map interface. We demonstrate GEOSPARK using three spatial analytics applications (spatial aggregation, autocorrelation and co-location) to show how users can easily define their spatial analytics tasks and efficiently process such tasks on large-scale spatial data at interactive performance.

Original language	English (US)
Title of host publication	2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1410-1413
Number of pages	4
ISBN (Electronic)	9781509020195
DOIs	https://doi.org/10.1109/ICDE.2016.7498357
State	Published - Jun 22 2016
Event	32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland Duration: May 16 2016 → May 20 2016

Other

Other	32nd IEEE International Conference on Data Engineering, ICDE 2016
Country/Territory	Finland
City	Helsinki
Period	5/16/16 → 5/20/16

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics
Computer Graphics and Computer-Aided Design
Computer Networks and Communications
Information Systems
Information Systems and Management

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10.1109/ICDE.2016.7498357

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A demonstration of GeoSpark: A cluster computing framework for processing big spatial data. / Yu, Jia; Wu, Jinxuan; Elsayed, Mohamed.
2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1410-1413 7498357.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yu, J, Wu, J & Elsayed, M 2016, A demonstration of GeoSpark: A cluster computing framework for processing big spatial data. in 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016., 7498357, Institute of Electrical and Electronics Engineers Inc., pp. 1410-1413, 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, 5/16/16. https://doi.org/10.1109/ICDE.2016.7498357

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A demonstration of GeoSpark: A cluster computing framework for processing big spatial data

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