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Parallel algorithms for spatial data partition and join processing

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3 Author(s)
Yanchun Zhang ; Dept. of Maths & Comput., Univ. of Southern Queensland, Toowoomba, Qld., Australia ; Jitian Xiao ; A. J. Roberts

The spatial join operations combine two sets of spatial data by their spatial relationships. They are among the most important, yet most time-consuming operations in spatial databases. We consider the problem of binary polygon intersection joins based on the filter-and-refine strategy. Our objective is to minimize the I/O cost and the response time for the refinement step. First, a graph model is proposed to formalize the refinement cost and matrix-based sequential data partition algorithms are introduced. Then a parallel data partitioning algorithm is developed with a detailed complexity analysis. Based on the data partition results, a distribution algorithm is also proposed for scheduling parallel spatial join processing

Published in:

Algorithms and Architectures for Parallel Processing, 1997. ICAPP 97., 1997 3rd International Conference on

Date of Conference:

10-12 Dec 1997