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The Dynamic Data Cube

  • Steven Geffner
  • Divakant Agrawal
  • Amr El Abbadi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1777)

Abstract

Range sum queries on data cubes are a powerful tool for analysis. A range sum query applies an aggregation operation (e.g., SUM, AVERAGE) over all selected cells in a data cube, where the selection is specified by providing ranges of values for numeric dimensions. We present the Dynamic Data Cube, a new approach to range sum queries which provides efficient performance for both queries and updates, which handles clustered and sparse data gracefully, and which allows for the dynamic expansion of the data cube in any direction.

Keywords

Range Query Data Cube Sublinear Performance Left Subtree Partition Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    J. Gray, A. Bosworth, A. Layman, H. Pirahesh. Data Cube: A relational aggregation operator generalizing group-by, cross-tabs and sub-totals. In Proc. of the 12th Int’l Conference on Data Engineering, pages 152–159, 1996.Google Scholar
  2. [2]
    S. Agarwal, R. Agrawal, P. M. Deshpande, A. Gupta, J. F. Naughton, R. Ramakrishnan, S. Sarawagi. On the computation of multidimensional aggregates. In Proc. of the 22nd Int’l Conference on Very Large Databases, pages 506–521, Mumbai (Bombay), India, September 1996.Google Scholar
  3. [3]
    V. Harinarayan, A. Rajaraman, J. D. Ullman. Implementing data cubes efficiently. In Proc. of the ACM SIGMOD Conference on the Management of Data, June 1996.Google Scholar
  4. [4]
    H. Gupta, V. Harinarayan, A. Rajaraman, J. Ullman. Index selection for OLAP. In Proc. of. the 13th Int’l Conference on Data Engineering, Birmingham, U. K. April 1997.Google Scholar
  5. [5]
    A. Shukla, P. M. Deshpande, J. F. Naughton, K. Ramasamy. Storage estimation for multidimensional aggregates in the presence of hierarchies. In Proc. of the 22nd Int’l Conference on Very Large Databases, pages 522–531, Mumbai (Bombay), India, September 1996.Google Scholar
  6. [6]
    B. Salzberg, A. Reuter. Indexing for aggregation, 1996. Working Paper.Google Scholar
  7. [7]
    T. Johnson, D. Shasha. Hierarchically split cube forests for decision support: description and tuned design, 1996. Working Paper.Google Scholar
  8. [8]
    C. Ho, R. Agrawal, N. Megiddo, R. Srikant. Range Queries in OLAP Data Cubes. In Proc. of the ACM SIGMOD Conference on the Management of Data, pages 73–88, 1997.Google Scholar
  9. [9]
    S. Geffner, D. Agrawal, A. El Abbadi, T. Smith. Relative Prefix Sums: An Efficient Approach for Querying Dynamic OLAP Data Cubes. In Proc. of the 15th International Conference on Data Engineering, Sydney, Australia, March 1999.Google Scholar
  10. [10]
    S. Geffner, D. Agrawal, A. El Abbadi. Performance Characteristics of the Dynamic Data Cube. University of California, Santa Barbara, Computer Science Technical Report TRCS99-38, available at http://www.cs.ucsb.edu.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Steven Geffner
    • 1
  • Divakant Agrawal
    • 1
  • Amr El Abbadi
    • 1
  1. 1.Department of Computer ScienceUniversity of CaliforniaSanta Barbara

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