Query Optimization in the Presence of Limited Access Patterns
Abstract
We consider the problem of query optimization in the presence of limitations on access patterns to the data (i.e., when one must provide v alues for one of theattributes of a relation in order to obtain tuples). We show that in the presence of limited access patterns we must search a space of {annotated query plans}, where the annotations describe the inputs that must be given to the plan. We describe a theoretical and exp erimental analysis of the resulting search space. Based on the conclusion s of this analysis, we describe a novel query optimization algorithm that is designed to perform well under the different conditions that may aris e. The algorithm searches the set of annotated query plans, pruning inval id and non-viable plans as early as possible in the search space. The alg orithm also uses a best-first search strategy in order to produce a first complete plan early in the search. We describe experiments to illustrate the performance of our algorithm.