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ISPRS Int. J. Geo-Inf. 2018, 7(5), 179; https://doi.org/10.3390/ijgi7050179

2DPR-Tree: Two-Dimensional Priority R-Tree Algorithm for Spatial Partitioning in SpatialHadoop

1
Department of Information Systems, Kafr El-Sheikh University, Kafr El-Sheikh 33511, Egypt
2
Department of Information Systems, Mansoura University, Mansoura 35516, Egypt
*
Author to whom correspondence should be addressed.
Received: 23 March 2018 / Revised: 1 May 2018 / Accepted: 7 May 2018 / Published: 9 May 2018
(This article belongs to the Special Issue Cognitive Aspects of Human-Computer Interaction for GIS)
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Abstract

Among spatial information applications, SpatialHadoop is one of the most important systems for researchers. Broad analyses prove that SpatialHadoop outperforms the traditional Hadoop in managing distinctive spatial information operations. This paper presents a Two Dimensional Priority R-Tree (2DPR-Tree) as a new partitioning technique in SpatialHadoop. The 2DPR-Tree employs a top-down approach that effectively reduces the number of partitions accessed to answer the query, which in turn improves the query performance. The results were evaluated in different scenarios using synthetic and real datasets. This paper aims to study the quality of the generated index and the spatial query performance. Compared to other state-of-the-art methods, the proposed 2DPR-Tree improves the quality of the generated index and the query execution time. View Full-Text
Keywords: SpatialHadoop; spatial data processing; cloud computing; PR-Tree; geospatial data SpatialHadoop; spatial data processing; cloud computing; PR-Tree; geospatial data
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Elashry, A.; Shehab, A.; Riad, A.M.; Aboul-Fotouh, A. 2DPR-Tree: Two-Dimensional Priority R-Tree Algorithm for Spatial Partitioning in SpatialHadoop. ISPRS Int. J. Geo-Inf. 2018, 7, 179.

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