Query optimizers in current database management systems (DBMS) often face problems such as intolerably long optimization time and/or poor optimization results when optimizing complex queries. To tackle this challenge, we present a new similarity-based optimization technique in this paper. The key idea is to identify groups of similar subqueries that often appear in a complex query and share the optimization result within each group in the query. An efficient algorithm to identify similar queries in a given query and optimize the query based on ' similarity is presented. Our experimental results demonstrate that the proposed technique is quite promising in optimizing complex queries in a DBMS. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Tao, Y., Zhu, Q., & Zuzarte, C. (2003). Exploiting similarity of subqueries for complex query optimization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2736, 747–759. https://doi.org/10.1007/978-3-540-45227-0_73
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