2015 31st IEEE International Conference on Data Engineering Workshops (ICDEW) (2015)
Seoul, South Korea
April 13, 2015 to April 17, 2015
Simin You , Dept. of Computer Science, CUNY Graduate Center, New York, USA
Jianting Zhang , Dept. of Computer Science, The City College of New York, USA
Le Gruenwald , Dept. of Computer Science, The University of Oklahoma, Norman, USA
The rapidly increasing amount of location data available in many applications has made it desirable to process their large-scale spatial queries in Cloud for performance and scalability. We report our designs and implementations of two prototype systems that are ready for Cloud deployments: SpatialSpark based on Apache Spark and ISP-MC based on Cloudera Impala. Both systems support indexed spatial joins based on point-in-polygon test and point-to-polyline distance computation. Experiments on the pickup locations of ∼170 million taxi trips in New York City and ∼10 million global species occurrences records have demonstrated both efficiency and scalability using Amazon EC2 clusters.
Sparks, Spatial databases, Query processing, Hardware, Scalability, Data processing, Filtering
S. You, J. Zhang and L. Gruenwald, "Large-scale spatial join query processing in Cloud," 2015 31st IEEE International Conference on Data Engineering Workshops (ICDEW), Seoul, South Korea, 2015, pp. 34-41.