Cost-based query optimization via AI planning

Abstract

In this paper we revisit the problem of generating query plans using AI automated planning with a view to leveraging significant advances in state-of-the-art planning techniques. Our efforts focus on the specific problem of cost-based joinorder optimization for conjunctive relational queries, a critical component of production-quality query optimizers. We characterize the general query-planning problem as a deletefree planning problem, and query plan optimization as a context-sensitive cost-optimal planning problem. We propose algorithms that generate high-quality query plans, guaranteeing optimality under certain conditions. Our approach is general, supporting the use of a broad suite of domainindependent and domain-specific optimization criteria. Experimental results demonstrate the effectiveness of AI planning techniques for query plan generation and optimization. 'Most of this work was carried out at the University of Toronto. Show more