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Analytical Synopses for Approximate Query Answering in OLAP Environments

  • Alfredo Cuzzocrea
  • Ugo Matrangolo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3180)

Abstract

In this paper we present a technique based on an analytical interpretation of multi-dimensional data and on the well-known Least Squares Approximation (LSA) method for supporting approximate aggregate query answering in OLAP environments, the most common application interfaces for a Data Warehouse Server (DWS). Our technique consists in building data synopses by interpreting the original data distribution as a set of discrete functions. These synopses, called Δ-Syn, are obtained by approximating data with a set of polynomial coefficients, and storing these coefficients instead of the original data. Queries are issued on the compressed representation, thus reducing the number of disk accesses needed to evaluate the answer. We also provide some experimental results on several kinds of synthetic OLAP data cubes.

Keywords

Range Query Data Cube Aggregate Query Approximate Answer Percentage Average Relative Error 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alfredo Cuzzocrea
    • 1
  • Ugo Matrangolo
    • 2
  1. 1.DEIS DeptUniversity of CalabriaRende, CosenzaItaly
  2. 2.ICAR InstCNRRende, CosenzaItaly

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