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ABSTRACT
Decision support applications are growing in popularity as more business data is kept on-line. Such applications typically include complex SQL queries that can test a query optimizer's ability to produce an efficient access plan. Many access plan strategies exploit the physical ordering of data provided by indexes or sorting. Sorting is an expensive operation, however. Therefore, it is imperative that sorting is optimized in some way or avoided all together. Toward that goal, this paper describes novel optimization techniques for pushing down sorts in joins, minimizing the number of sorting columns, and detecting when sorting can be avoided because of predicates, keys, or indexes. A set of fundamental operations is described that provide the foundation for implementing such techniques. The operations exploit data properties that arise from predicate application, uniqueness, and functional dependencies. These operations and techniques have been implemented in IBM's DB2/CS.
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[doi> 10.1145/582095.582099]
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CITED BY 22
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Ihab F. Ilyas , Jun Rao , Guy Lohman , Dengfeng Gao , Eileen Lin, Estimating compilation time of a query optimizer, Proceedings of the 2003 ACM SIGMOD international conference on Management of data, June 09-12, 2003, San Diego, California
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Peter Boncz , Torsten Grust , Maurice van Keulen , Stefan Manegold , Jan Rittinger , Jens Teubner, MonetDB/XQuery: a fast XQuery processor powered by a relational engine, Proceedings of the 2006 ACM SIGMOD international conference on Management of data, June 27-29, 2006, Chicago, IL, USA
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