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The combination of spatial data sets based on spatial relationships between objects is a common operation in geographical databases. This operation is called spatial join operation. The spatial join o...peration, as with all join operations of relational databases has high computing time cost. It is natural to apply parallelism to the spatial join operation. In this paper, we focus on the parallel processing of spatial join when a geographical database is partitioned by round-robin algorithm. We propose two algorithms of the Filter Step in parallel join processing based on a round-robin algorithm. One of the algorithm uses a R*-tree of all data sets, the other uses a set of the R*-tree each partition owns. We implement proposed algorithm on Query10 of Extended Sequoia 2000 benchmark and compare the Filter Step performance of two algorithms.続きを見る
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