Parallel R-tree spatial join for a shared-nothing architecture

The growing importance of spatial data has made it imperative that spatial operations be executed efficiently. The most expensive operation is the join for spatial databases. We propose a replicated parallel packed R-tree and its use in performing the parallel R-tree join. We examine its performance using the Digital Chart of the World Data on a shared nothing machine. Our experimental results show that the proposed tree and heuristics for load balancing improve parallel R-tree join