Advertisement

QReduction: Synopsizing XPath Query Set Efficiently under Resource Constraint

  • Jun Gao
  • Xiuli Ma
  • Dongqing Yang
  • Tengjiao Wang
  • Shiwei Tang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3129)

Abstract

How to evaluate a massive XPath set over XML streams poses great challenges to database researchers. Current work chiefly focuses on evaluating efficiently massive XPath set to obtain precise results. The size of the input query set has a great impact on the resource requirement and the efficiency of evaluation. In this paper, we propose a novel method, QReduction, to obtain the synopsized XPath query set to represent the original query set, while at the same time to minimize the ’precision loss’ caused by query set synopsis. QReduction discovers frequent patterns among the massive input XPath tree patterns first, and select query set synopsis from them based on a dynamic benefit model under resource constraints. Since frequent patterns discovery takes high complexity in QReduction, we propose optimization methods by pushing the constraints of QReduction into the discovery process. We propose 3 criteria, namely recall, precision and intersection to determine a better synopsis. The experimental results demonstrate that our method can produce a query set synopsis with high precision, recall and intersection under given resource constraints.

Keywords

Frequent Pattern Tree Pattern Candidate Pattern XPath Query Query Containment 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amer-Yahia, S., Cho, S., Srivastava, D.: Tree Pattern Relaxation. In: Proceedings of 8th EDBT conference, pp. 496–513 (2002)Google Scholar
  2. 2.
    Yang, L.H., Lee, M.-L., Hsu, W.: Efficient Mining of XML Query Patterns for Caching. In: Proceedings of 29th VLDB conference, pp. 69–80 (2003)Google Scholar
  3. 3.
    Gupta, A.K., Suciu, D.: Stream Processing of XPath Queries with Predicates. In: Proceeding of SIGMOD conference, pp. 419–430 (2003)Google Scholar
  4. 4.
    Diao, Y., Fischer, P., Franklin, M., Raymond: YFilter: efficient and scalable filtering of XML documents. In: Proceeding of ICDE conference, pp. 341–345 (2002)Google Scholar
  5. 5.
    Clark, J.: XML Path language(XPath) (1999), available from the W3C, http://www.w3.org/TR/XPath
  6. 6.
    Garofalakis, M., Chan, C.Y., fan, W., Felber, P., Rastogi, R.: Tree pattern aggregation for scalable XML data dissemination. In: Proceedings of 28th VLDB conference (2002)Google Scholar
  7. 7.
    Miklau, G., suciu, D.: Containment and equivalence for an XPath fragment. In: Proceedings of 21th PODS, pp. 65–76 (2002)Google Scholar
  8. 8.
    C.Chan, P.Felber, M.Garofalakis and R.Rastogi. Efficient filtering of XML document with XPath expressions. In proceedings of 18th ICDE conference, 2002, pages 235-244. Google Scholar
  9. 9.
    Garofalakis, M.N., Gibbon, P.B.: Approximate Query Processing: Taming the TeraBytes. In: Proceedings of 27th VLDB Conference (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jun Gao
    • 1
  • Xiuli Ma
    • 1
  • Dongqing Yang
    • 1
  • Tengjiao Wang
    • 1
  • Shiwei Tang
    • 1
  1. 1.The school of electronic engineering and computer sciencePeking UniversityBeijingChina

Personalised recommendations