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Data Cube: A Relational Aggregation
Operator Generalizing Group-By, CrossTab, and Sub-Totals
February 1, 1995
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Authors

Adam Bosworth

Jim Gray

Andrew Layman

Hamid Pirahesh
Publication Type
TechReport
Pages
21
Number
MSR-TR-95-22
Publisher
Institute of Electrical and Electronics Engineers, Inc.
© 1997 IEEE. Personal use of this material is permitted. However, permission to
reprint/republish this material for advertising or promotional purposes or for creating new
collective works for resale or redistribution to servers or lists, or to reuse any copyrighted
component of this work in other works must be obtained from the IEEE.
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Abstract
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Related Info
Abstract
Data analysis applications typically aggregate data across many dimensions looking for unusual
patterns. The SQL aggregate functions and the GROUP BY operator produce zero-dimensional
or 1-dimensional answers. Applications need the N-dimensional generalization of these
operators. This paper defines that operator, called the data cube, or simply cube. The cube
operator generalizes the histogram, cross-tabulation, drill-down, and sub-total constructs found
in most report writers. The cube treats each of the N aggregation attributes as a dimension of Nspace. The aggregate of a particular set of attribute values is a point in this space. The set of
points form an N-dimensional cube. Super-aggregates are computed by aggregating the N-cube
to lower dimensional spaces. Aggregation points are represented by an “infinite value”, ALL.
For example, the point would represent the global sum of all items. Each ALL value actually
represents the set of values contributing to that aggregation.
Related Info
Related Files
 tr-95-22.doc
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 Data visualization, analytics, and platform
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