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SF-Tree: An Efficient and Flexible Structure for Estimating Selectivity of Simple Path Expressions with Statistical Accuracy Guarantee

  • Wai-Shing Ho
  • Ben Kao
  • David W. Cheung
  • YIP Chi Lap
  • Eric Lo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2973)

Abstract

Estimating the selectivity of a simple path expression (SPE) is essential for selecting the most efficient evaluation plans for XML queries. To estimate selectivity, we need an efficient and flexible structure to store a summary of the path expressions that are present in an XML document collection. In this paper we propose a new structure called SF-Treeto address the selectivity estimation problem. SF-Tree provides a flexible way for the users to choose among accuracy, space requirement and selectivity retrieval speed. It makes use of signature files to store the SPEs in a tree form to increase the selectivity retrieval speed and the accuracy of the retrieved selectivity. Our analysis shows that the probability that a selectivity estimation error occurs decreases exponentially with respect to the error size.

Keywords

SF-Tree query processing selectivity estimation XML path expressions 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Wai-Shing Ho
    • 1
  • Ben Kao
    • 1
  • David W. Cheung
    • 1
  • YIP Chi Lap
    • 1
  • Eric Lo
    • 1
  1. 1.Department of Computer Science and Information SystemsThe University of Hong KongHong Kong

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