UD(k,l)-Index: An Efficient Approximate Index for XML Data

  • Hongwei Wu
  • Qing Wang
  • Jeffrey Xu Yu
  • Aoying Zhou
  • Shuigeng Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2762)


XML has become the main standard of data presentation and exchange on the Internet. Processing path expressions plays a key role in XML queries evaluation. Path indices can speed up path expressions evaluation on XML data by restricting search only to the relevant portion. However, to answer all path expressions accurately, traditional path indices group data nodes according to the paths from the root of the data graph to the nodes in question, regardless of the paths fanning out from these nodes. This leads to large indices size and low efficiency of branching path expressions evaluation. In this paper, we present UD(k,l)-indices, a family of efficient approximate index structures in which data nodes are grouped according to their incoming paths of length up to k and outgoing paths of length up to l. UD(k,l)-indices fully exploit local similarity of XML data nodes on their upward and downward paths, so can be used for efficiently evaluating path expressions, especially branching path expressions. For small values of k and l, UD(k,l)-index is approximate, we use validation-based approach to find exact answers to the path expressions. Experiments show that with proper values of k and l, UD(k,l)-index can improve the performance of path expressions evaluation significantly with low space overhead.


Data Graph Primary Path Data Node Index Node Path Query 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abiteboul, S.: Quering semi-structured data. In: Afrati, F.N., Kolaitis, P.G. (eds.) ICDT 1997. LNCS, vol. 1186, pp. 1–18. Springer, Heidelberg (1997)Google Scholar
  2. 2.
    Buneman, P., Kaushik, R., Suciu, D.: A query language and algebra for semistructured data based on structural recursion. In: Proc. of Int’l Conf. on Very Large Databases (VLDB), vol. 9(1), pp. 76–110 (2000)Google Scholar
  3. 3.
    Chamberlin, D., et al.: XQuery 1.0: An XML Query Language. W3C Working Draft (June 2001),
  4. 4.
    Clark, J., DeRose, S.: XML Path Language (XPath). W3C Working Draft (November 1999),
  5. 5.
    Cooper, B., Sample, N., Franklin, M.J., Hjaltason, G.R., Shadmon, M.: A fast index for semistructured data. In: Proc. of Int’l Conf. on Very Large Databases (VLDB), pp. 341–350 (2001)Google Scholar
  6. 6.
    DeRose, S., Maler, E., Orchard, D.: The xlink standard (June 2001),
  7. 7.
    Deutsch, A., Fernandez, M., Florescu, D., Levy, A., Suciu, D.: A query language for XML. In: Proc. of Int’l World Wide Web Conf, WWW (1999)Google Scholar
  8. 8.
    Gionis, A., Garofalakis, M., Rastogi, R., Seshadri, S., Shim, K.: XTRACT: A system for extracting for document type descriptors from XML documents. In: Proc. of ACM SIGMOD Conf. on Management of Data, pp. 165–176 (2000)Google Scholar
  9. 9.
    Goldman, R., Widom, J.: Dataguides: Enabling query formulation and optimization in semistructured databases. In: Proc. of Int’l Conf. on Very Large Databases (VLDB), pp. 436–445 (1997)Google Scholar
  10. 10.
    Goldman, R., Widom, J.: Approximate dataguides. In: The WorkShop on Query Processing for Semistructured Data and Non-Standared Data Formats, Jerusalem, Israel (1999)Google Scholar
  11. 11.
    Kaushik, R., Shenoy, P., Bohannon, P., Gudes, E.: Exploiting local similarity for efficient indexing of paths in graph structured data. In: Proc. of IEEE Int’l Conf. on Data Engineering, ICDE (2002)Google Scholar
  12. 12.
    McHugh, J., Abiteboul, S., Goldman, R., Quass, D., Widom, J.: Lore: A database management system for semistructured data. SIGMOD Record 26(3) (1997)Google Scholar
  13. 13.
    Milo, D., Suciu, D.: Index structure for path expression. In: Proc. of Int’l Conf. on Database Theory (ICDT), pp. 277–295 (1999)Google Scholar
  14. 14.
    Nestorov, S., Abiteboul, S., Motwani, R.: Extracting schema from semistructured data. SIGMOD Record 27(2), 295–305 (1998)CrossRefGoogle Scholar
  15. 15.
    Nestorov, S., Ullman, J., Weiner, J., Chawathe, S.: Representative objects: Concise representations of semistructured, hierarchical data. In: Proc. of IEEE Int’l Conf. on Data Engineering (ICDE), pp. 79–90 (1999)Google Scholar
  16. 16.
    XMark. The XML benchmark project,

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Hongwei Wu
    • 1
  • Qing Wang
    • 1
  • Jeffrey Xu Yu
    • 2
  • Aoying Zhou
    • 1
  • Shuigeng Zhou
    • 1
  1. 1.Department of Computer Science and EngineeringFudan UniversityShanghaiChina
  2. 2.Department of Systems Engineering and Engineering ManagementThe Chinese University of Hong KongShatin, NT, Hong KongChina

Personalised recommendations