Can logic make databases smarter? This paper introduces a logic-based method for semantic query optimization, leveraging semantic knowledge such as integrity constraints to transform queries for more efficient answering. Semantic query optimization aims to enhance database performance by using semantic knowledge to convert a query into an equivalent form that can be processed more effectively. The method, designed for deductive databases grounded in first-order logic, is presented with an emphasis on its techniques and applicability for optimizing relational queries. The authors demonstrate that this approach not only subsumes but also generalizes previous work in the field, providing a comprehensive framework for query optimization. Furthermore, the paper explores the potential extension of these semantic query optimization techniques to databases supporting recursion and integrity constraints, including disjunction, negation, and recursion. This research contributes to the advancement of database technology, offering valuable tools and insights for improving query processing and database efficiency. Future work may focus on refining and expanding these techniques to address the complexities of modern database systems.
Published in ACM Transactions on Database Systems, this paper aligns perfectly with the journal's focus on advancements in database technology and management. By addressing semantic query optimization, a crucial aspect of database performance, the study contributes directly to the journal's core topics. The rigorous logic-based approach and the potential for extending the techniques to handle recursion further enhance the paper's relevance and significance within the field.