Publication | Closed Access
Processing multi-way spatial joins on map-reduce
40
Citations
21
References
2013
Year
Unknown Venue
Cluster ComputingMulti-way Spatial JoinsEngineeringData ScienceMap-reduce PlatformJoin QueriesCloud ComputingKnowledge DiscoveryManagementData IntegrationComputer ScienceDistributed Query ProcessingMap-reduceBig DataDistributed Data StoreData ManagementMassive Data ProcessingQuery Optimization
In this paper we investigate the problem of processing multi-way spatial joins on map-reduce platform. We look at two common spatial predicates - overlap and range. We address these two classes of join queries, discuss the challenges and outline novel approaches for executing these queries on a map-reduce framework. We then discuss how we can process join queries involving both overlap and range predicates. Specifically we present a Controlled-Replicate framework using which we design the approaches presented in this paper. The Controlled-Replicate framework is carefully engineered to minimize the communication among cluster nodes. Through experimental evaluations we discuss the complexity of the problem under investigation, details of Controlled-Replicate framework and demonstrate that the proposed approaches comfortably outperform naive approaches.
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