Efficient parallel spatial join processing method in a shared-nothing database cluster system

Spatial database cluster consisted of several single nodes on highspeed network to offer high-performance is raised. But, research about spatial join operation that can reduce the performance of whole system in case process at single node is not achieved. Therefore, we propose efficient parallel spatial join processing method in a spatial database cluster system that uses data partitions and replications method that considers the characteristics of spatial data. Since proposed method does not need the creation step and the assignment step of tasks, and additional message transmission between cluster nodes that appear in existent parallel spatial join method, it shows performance improvement of 23% than the conventional parallel R-tree spatial join for a shared-nothing architecture about expensive spatial join queries.