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Pre-computing Approximate Hierarchical Range Queries in a Tree-Like Histogram

  • Francesco Buccafurri
  • Gianluca Lax
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2737)

Abstract

Histograms are a lossy compression technique widely applied in various application contexts, like query optimization, statistical and temporal databases, OLAP applications, and so on. This paper presents a new histogram based on a hierarchical decomposition of the original data distribution kept in a complete binary tree. This tree, thus containing a set of pre-computed hierarchical queries, is encoded in a compressed form using bit saving in representing integer numbers. The approach, extending a recently proposed technique based on the application of such a decomposition to the buckets of a pre-existing histogram, is shown by several experiments to improve the accuracy of the state-of-the-art histograms.

Keywords

Compression Ratio Parent Node Range Query Average Relative Error Query Optimization 
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 2003

Authors and Affiliations

  • Francesco Buccafurri
    • 1
  • Gianluca Lax
    • 1
  1. 1.DIMETUniversità degli Studi Mediterranea di Reggio CalabriaReggio CalabriaItaly

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