An efficient selectivity estimation method for spatial query optimization with topological relationships

Many commercial database systems maintain histograms to summarize the contents of relations and permit the efficient estimation of query result sizes and the access plan cost. In spatial database systems, most spatial query predicates are consisted of topological relationships between spatial objects, and it is very important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multidimensional histogram and the transformation scheme. Proposed scheme applies twopartition strategy on transformed object space to generate spatial histogram and estimates the selectivity of topological predicates based on the topological characteristics of the transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in most spatial query optimizers.