AAAI Publications, Twenty-Eighth AAAI Conference on Artificial Intelligence

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Cost-Based Query Optimization via AI Planning
Nathan Robinson, Sheila McIlraith, David Toman

Last modified: 2014-06-21

Abstract


In this paper we revisit the problem of generating query plans using AI automated planning with a view to leveraging significant recent advances in state-of-the-art planning techniques. Our efforts focus on the specific problem of cost-based join-order optimization for conjunctive relational queries, a critical component of production-quality query optimizers. We characterize the general query-planning problem as a delete-free 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 domain-independent and domain-specific optimization criteria. Experimental results demonstrate the effectiveness of AI planning techniques for query plan generation and optimization.

Keywords


Planning; Query optimization; Join-order Selection

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