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• W3197267923 abstract "Data analysis often involves comparing subsets of data across many dimensions for finding unusual trends and patterns. While the comparison between subsets of data can be expressed using SQL, they tend to be complex to write, and suffer from poor performance over large and high-dimensional datasets. In this paper, we propose a new logical operator COMPARE for relational databases that concisely captures the enumeration and comparison between subsets of data and greatly simplifies the expressing of a large class of comparative queries. We extend the database engine with optimization techniques that exploit the semantics of COMPARE to significantly improve the performance of such queries. We have implemented these extensions inside Microsoft SQL Server, a commercial DBMS engine. Our extensive evaluation on synthetic and real-world datasets shows that COMPARE results in a significant speedup over existing approaches, including physical plans generated by today's database systems, user-defined functions (UDFs), as well as middleware solutions that compare subsets outside the databases." @default.
• W3197267923 created "2021-09-13" @default.
• W3197267923 creator A5038037154 @default.
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• W3197267923 date "2021-07-01" @default.
• W3197267923 modified "2023-09-24" @default.
• W3197267923 title "COMPARE" @default.
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• W3197267923 doi "https://doi.org/10.14778/3476249.3476291" @default.
• W3197267923 hasPublicationYear "2021" @default.
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