A better tool for query optimization:

When evaluating the performance of a query strategy, one must often estimate the number of distinct values of an attribute in a randomly selected subset of a relation. Most query optimizers compute this estimate based on the assumption that prior to the selection, the attribute values are uniformly...

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Bibliographic Details
Main Authors: Bitton, Dina (Author), Vander Zanden, Bradley (Author)
Format: Book
Language:English
Published: Ithaca, NY 1985
Series:Cornell University <Ithaca, NY> / Dep. of Computer Science: Technical report 671.
Subjects:
Summary:When evaluating the performance of a query strategy, one must often estimate the number of distinct values of an attribute in a randomly selected subset of a relation. Most query optimizers compute this estimate based on the assumption that prior to the selection, the attribute values are uniformly distributed in the relation. In this paper we depart from this assumption and instead consider Zipf distributions that are known to accurately model text and name distributions. Given a relation of cardinality
Physical Description:16 S. graph. Darst.

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