A Spatial Join Query Optimization Algorithm Based on Grid Index
Arming at the problem of spatial join query processing in cloud computing,an effective spatial join query processing optimization algorithm is proposed in this paper,which is based on the MapReduce framework. Data space is partitioned into many grid cells by using grid division approach,and each spatial object in one data set is distributed into a grid cell according to its central point position,this avoids the redundant duplication of the data object. According to the intersection relationship of data objects contained by these grid cells,a grid index is constructed to filter useless join objects. For another data set,we use the grid index to duplicate each data object only to the grid cells in which there exists one data object intersected with the data object,and thus filtering out the useless data objects,thereby greatly reducing the corresponding computational cost. Comparative experiments on synthetic data and real data sets show that the proposed spatial data join query processing optimization algorithm has obvious advantages and better performance than SJMR algorithm.