Cubing Algorithms, Storage Estimation, and Storage and Processing Alternatives for OLAP.
Prasad Deshpande, Jeffrey F. Naughton, Karthikeyan Ramasamy, Amit Shukla, Kristin Tufte, Yihong Zhao:
Cubing Algorithms, Storage Estimation, and Storage and Processing Alternatives for OLAP.
IEEE Data Eng. Bull. 20(1): 3-11(1997)@article{DBLP:journals/debu/DeshpandeNRSTZ97,
author = {Prasad Deshpande and
Jeffrey F. Naughton and
Karthikeyan Ramasamy and
Amit Shukla and
Kristin Tufte and
Yihong Zhao},
title = {Cubing Algorithms, Storage Estimation, and Storage and Processing
Alternatives for OLAP},
journal = {IEEE Data Eng. Bull.},
volume = {20},
number = {1},
year = {1997},
pages = {3-11},
ee = {db/journals/debu/DeshpandeNRSTZ97.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
"OLAP" or multi-dimensional analysis workloads present a number of interesting challenges and opportunities for database developers and researchers.
While the OLAP goal of extremely fast response times is hard to meet in general, the structure of the underlying multidimensional model (whether implemented by arrays or by tables) provides a framework that can be used to approach this performance goal for this class of queries.
In this note we give an overview of our research into these problems.
Copyright © 1997 by The Institute of
Electrical and Electronic Engineers, Inc. (IEEE).
Abstract used with permission.
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Data Engineering Bulletin March 1997:
Supporting On-line Analytical Processing (Daniel Barbara, ed.)
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Copyright © Fri Mar 12 17:26:38 2010
by Michael Ley (ley@uni-trier.de)