Data declustering and cluster ordering technique for spatial join scheduling

Authors:
Jitian Xiao;Yanchun Zhang;Xiaohua Jia;Xiaofang Zhou
Affiliations:
Univ. of Southern Queensland, Toowoomba, Qld., Australia;Univ. of Southern Queensland, Toowoomba, Qld., Australia;City Univ. of Hong Kong, Hong Kong;CSIRO Mathematical and Information Sciences, Canberra, Australia
Venue:
Information organization and databases
Year:
2000

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Abstract

The spatial join operations combine two sets of spatial data by their spatial relationships. They are the most expensive operations, yet among the most common operations in spatial databases. In this paper we investigate the optimization issue through data declustering. A graph model is developed to formalise the problem, and then a matrix-based data partitioning method is proposed for declustering the non-uniform spatial data. The clusters produced are also ordered with maximum-overlapping. When inputting the clusters in this order for spatial joins, the I/O cost can be reduced significantly. The experimental work has shown that 15 - 35% saving can be achieved when comparing with some existing methods.