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Implementing Data Cubes Efficiently.

Venky Harinarayan, Anand Rajaraman, Jeffrey D. Ullman: Implementing Data Cubes Efficiently. SIGMOD Conference 1996: 205-216
@inproceedings{DBLP:conf/sigmod/HarinarayanRU96,
  author    = {Venky Harinarayan and
               Anand Rajaraman and
               Jeffrey D. Ullman},
  editor    = {H. V. Jagadish and
               Inderpal Singh Mumick},
  title     = {Implementing Data Cubes Efficiently},
  booktitle = {Proceedings of the 1996 ACM SIGMOD International Conference on
               Management of Data, Montreal, Quebec, Canada, June 4-6, 1996},
  publisher = {ACM Press},
  year      = {1996},
  pages     = {205-216},
  ee        = {http://doi.acm.org/10.1145/233269.233333, db/conf/sigmod/HarinarayanRU96.html},
  crossref  = {DBLP:conf/sigmod/96},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the data as multidimensional data cube. Each cell of the data cube is a view consisting of an aggregation of interest, like total sales. The values of many of these cells are dependent on the values of other cells in the data cube. A common and powerful query optimization technique is to materialize some or all of these cells rather than compute them from raw data each time. Commercial systems differ mainly in their approach to materializing the data cube. In this paper, we investigate the issue of which cells (views) to materialize when it is too expensive to materialize all views. A lattice framework is used to express dependencies among views. We present greedy algorithms that work off this lattice and determine a good set of views to materialize. The greedy algorithm performs within a small constant factor of optimal under a variety of models. We then consider the most commoncase of the hypercube lattice and examine the choice of materialized views for hypercubes in detail, giving some good tradeoffs between the space used and the average time to answer a query.

Copyright © 1996 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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H. V. Jagadish, Inderpal Singh Mumick (Eds.): Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, Montreal, Quebec, Canada, June 4-6, 1996. ACM Press 1996 BibTeX , SIGMOD Record 25(2), June 1996
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References

[Arb]
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[CS94]
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[GHQ95]
Ashish Gupta, Venky Harinarayan, Dallan Quass: Aggregate-Query Processing in Data Warehousing Environments. VLDB 1995: 358-369 BibTeX
[GHRU96]
Himanshu Gupta, Venky Harinarayan, Anand Rajaraman, Jeffrey D. Ullman: Index Selection for OLAP. ICDE 1997: 208-219 BibTeX
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[STG]
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[Xen94]
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BibTeX
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