Spatial query optimization should be the focus of attention in spatial area. Since relational optimizer is unsuitable for dealing with spatial data
spatial systems should have their own cost model and optimizer. In this paper
a spatial query optimization system—FQPro was presented. After the overview of general phrases of spatial query optimization
we put the emphasis on cost model
calculation of predicate costs and plan costs. In particular
we give a detailed introduction of the cost model based on R-tree. Similar to relational systems
FQPro defines a set of formula for predicate costs and predicate selectivity respectively. They are used in G/SQL. On top of these formulas
the idea and algorithm for forming the optimum execution plan is defined. Concluding this paper are some issues that should be the concerns of research on spatial optimization
primarily the cost model and the extensible system architecture. Also
this paper summarizes the challenges and opportunites facing spatial query processing in the end.