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Automated Verification of Query Equivalence Using Satisfiability Modulo Theories

Qi Zhou,Joy Arulraj,S. Navathe,William R. Harris,Dong Xu

Published 2019 in Proceedings of the VLDB Endowment

ABSTRACT

Database-as-a-service offerings enable users to quickly create and deploy complex data processing pipelines. In practice, these pipelines often exhibit significant overlap of computation due to redundant execution of certain sub-queries. It is challenging for developers and database administrators to manually detect overlap across queries since they may be distributed across teams, organization roles, and geographic locations. Thus, we require automated cloud-scale tools for identifying equivalent queries to minimize computation overlap. State-of-the-art algebraic approaches to automated verification of query equivalence suffer from two limitations. First, they are unable to model the semantics of widely-used SQL features, such as complex query predicates and three-valued logic. Second, they have a computationally intensive verification procedure. These limitations restrict their efficacy and efficiency in cloud-scale database-as-a-service offerings. This paper makes the case for an alternate approach to determining query equivalence based on symbolic representation. The key idea is to effectively transform a wide range of SQL queries into first order logic formulae and then use satisfiability modulo theories to efficiently verify their equivalence. We have implemented this symbolic representation-based approach in EQUITAS. Our evaluation shows that EQUITAS proves the semantic equivalence of a larger set of query pairs compared to algebraic approaches and reduces the verification time by 27X. We also demonstrate that on a set of 17,461 real-world SQL queries, it automatically identifies redundant execution across 11% of the queries. Our symbolic-representation based technique is currently deployed on Alibaba's MaxCompute database-as-a-service platform.

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