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Implementing data cubes efficiently
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Volume 25 ,  Issue 2  (June 1996) table of contents
Pages: 205 - 216  
Year of Publication: 1996
ISSN:0163-5808
Also published in ...
Authors
Venky Harinarayan  Stanford University
Anand Rajaraman  Stanford University
Jeffrey D. Ullman  Stanford University
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 30,   Downloads (12 Months): 278,   Citation Count: 263
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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 cubes. 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 common case 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.


REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.2 Types of Systems
          Subjects: Decision support (e.g., MIS)

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.4 Systems
          Subjects: Query processing


General Terms:
Theory

Collaborative Colleagues:
Venky Harinarayan: colleagues
Anand Rajaraman: colleagues
Jeffrey D. Ullman: colleagues
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