Spatial Query Optimization Utilizingearly Separated Filter and Refinement

| Due to the high complexity and large volume of spatial data, a spatial query has been processed in two steps, called the lter step and the reenement step. However, the two-step processing of the spatial query has been considered locally in one spatial predicate evaluation at the query execution level. This paper presents query optimization strategies which exploit the two-step processing of a spatial query at the query optimization level. The rst strategy involves the separation of lter and reenement steps not in the query execution phase but in the query optimization phase. As the second strategy, several reenement operations can be combined in processing a complex query if they were already separated, and as the third strategy several lter operations can also be combined. We call the optimization technique utilizing these strategies the Early Separated Filter And Reenement (ESFAR). This paper also presents an algebra, which is called the Intermediate Spatial Object Algebra (ISOA), and optimization rules for ESFAR. Through experiments using real data, we compare the ESFAR optimization technique with a traditional optimization technique which does not separate lter and reenement steps from the query optimization phase. The experimental results show that the ESFAR optimization technique generates more eecient query execution plans than the traditional one in many cases. c