Our news journalists obtained a quote from the research, "Such queries are not only difficult to write but also challenging for a database engine to optimize, thus can result in costly evaluation. This paper proposes to augment SQL with set predicate, to bring out otherwise obscured set-level semantics. We studied two approaches to processing set predicates-an aggregate function-based approach and a bitmap index-based approach. Moreover, we designed a histogram-based probabilistic method of set predicate selectivity estimation, for optimizing queries with multiple predicates."
According to the news editors, the research concluded: "The experiments verified its accuracy and effectiveness in optimizing queries."
For more information on this research see: Set Predicates in SQL: Enabling Set-Level Comparisons for Dynamically Formed Groups. IEEE Transactions on Knowledge and Data Engineering, 2014;26(2):438-452. IEEE Transactions on Knowledge and Data Engineering can be contacted at: Ieee Computer Soc,
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