Seeking efficient database query processing? This paper explores optimization techniques for SQL-like nested queries, a common feature in relational databases. It focuses on the challenges presented by the nesting of query blocks to arbitrary depths and identifies five basic types of nesting within SQL queries. The research addresses four types of nesting that are often poorly understood and inefficiently executed. Algorithms are developed to transform these queries into semantically equivalent forms, making them more suitable for processing by existing query-processing subsystems. This transformation enhances the efficiency of query execution. These algorithms are integrated into a coherent strategy designed to process complex, general nested queries, offering a practical approach to improving database performance and query optimization. This approach is relevant for databases and computer science.
Appearing in ACM Transactions on Database Systems, a leading journal in the field, this paper aligns with the journal’s focus on database technology and management. The research contributes to the ongoing efforts to optimize database performance and improve the efficiency of query processing, a critical aspect of database system design and implementation. It relates to topics of computer science and software engineering.