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Simultaneous Optimization and Evaluation of Multiple Dimensional Queries |
Full Paper (PDF)
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Database researchers have made significant progress on several research issues related to multidimensional data analysis, including the development of fast cubing algorithms, efficient schemes for creating and maintaining pre-computed group-bys, and the design of efficient storage structures for multidimensional data. However, to date there has been little or no work multidimensional query optimization. Recently, Microsoft has proposed "OLE DB for OLAP" as a standard multidimensional interface for databases. OLE DB for OLAP defines Multi-dimensional Expressions (MDX), which has the interesting and challenging feature of allowing clients to ask several related dimensional queries in a single MDX expression. In this paper we present three algorithms to optimize multiple related dimensional queries. Two of algorithms focus on how to generate a global plan from several related local plans. The third algorithm focuses on generating a good global plan without first generating local plans. We also present three new query evaluation primitives that allow related query plans to share portions of their evaluation. In our performance study, we compare the three algorithms. |
References, where available, link to the DBLP on the World Wide Web.
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@inproceedings{DBLP:conf/sigmod/ZhaoDNS98,
author = {Yihong Zhao and
Prasad Deshpande and
Jeffrey F. Naughton and
Amit Shukla},
editor = {Laura M. Haas and
Ashutosh Tiwary},
title = {Simultaneous Optimization and Evaluation of Multiple Dimensional
Queries},
booktitle = {SIGMOD 1998, Proceedings ACM SIGMOD International Conference
on Management of Data, June 2-4, 1998, Seattle, Washington, USA},
publisher = {ACM Press},
year = {1998},
isbn = {0-89791-955-5},
pages = {271-282},
crossref = {DBLP:conf/sigmod/98},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
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DBLP: Copyright ©1999 by Michael Ley (ley@uni-trier.de).
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