A New Structure for Accelerating XPath Location Steps

  • Yaokai Feng
  • Akifumi Makinouchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4016)


Multidimensional indices have been successfully introduced to the field of querying on XML data. Using R*-tree, T. Grust proposed an interesting method to support all XPath axes. In that method, each node of an XML document is labeled with a five-dimensional descriptor. All the nodes of the XML document are mapped to a point set in a five-dimensional space. T. Grust made it clear that each of the XPath axes can be implemented by a range query in the above five-dimensional space. Thus, R*-tree can be used to improve the query performance for XPath axes. However, according to our investigations, most of the range queries for the XPath axes are partially-dimensional range queries. That is, the number of query dimensions in each of the range queries is less than five, although the R*-tree is built in the five-dimensional space. If the existing multidimensional indices are used for such range queries, then a great deal of information that is irrelevant to the queries also has to be read from disk. Based on this observation, a new multidimensional index structure (called Adaptive R*-tree) is proposed in this paper to support the XPath axes more efficiently.


Index Structure Range Query Query Performance XPath Expression Multidimensional Index 
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.
    Grust, T.: Accelerating XPath Location Steps. In: Proc. ACM SIGMOD International Conference, pp. 109–120 (2002)Google Scholar
  2. 2.
    Berglund, A., Boag, S., Chamberlin, D., Fernandez, M.F., et al.: XML Path Language (XPath) 2.0. Technical Report W3C Working Draft, Version 2.0, World Wide Web Consortium (December 2001),
  3. 3.
    Boag, S., Chamberlin, D., Fernandez, M.F., et al.: XQuery 1.0: An XML query language. In: W3C Working Draft, August 16 (2002),
  4. 4.
    Cooper, B.F., Sample, N., Franklin, M.J., Hjaltason, G.R., Shadmon, M.: A Fast Index for Semistructured Data. In: Proc. the 27th International Conference on Very Large Data Bases (VLDB), pp. 341–360 (2001)Google Scholar
  5. 5.
    Li, Q., Moon, B.: Indexing and Querying XML Data for Regular Path Expressions. In: Proc. the 27th International Conference on Very Large Data Bases (VLDB), pp. 361–370 (2001)Google Scholar
  6. 6.
    Suciu, D., Milo, T.: Index structures for path expressions. In: Beeri, C., Bruneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 277–295. Springer, Heidelberg (1999)Google Scholar
  7. 7.
    Goldman, R., Widom, J.: DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases. In: Proc. the 23rd International Conference on Very Large Databases (VLDB), pp. 436–445 (1997)Google Scholar
  8. 8.
    Zhang, C., Naughton, J., DeWitt, D., Luo, Q., Lohman, G.: On Supporting Containment Queries in Relational Database Management Systems. In: Proc. ACM SIGMOD International Conference on Management of Data, pp. 425–436 (2001)Google Scholar
  9. 9.
    Kriegel, H.P., Potke, M., Seidl, T.: Managing Intervals efficiently in Object- Relational Databases. In: Proc. the 26th International Conference on Very Large Databases, VLDB, pp. 407–418 (2000)Google Scholar
  10. 10.
    Kriegel, H.P., otke, M.P., Seidl, T.: Managing Intervals Efficiently in Object- Relational Databases. In: Proc. the 26th International Conference on Very Large Databases (VLDB), pp. 407–418 (2000)Google Scholar
  11. 11.
    Dietz, P.F., Sleator, D.D.: Two Algorithms for Maintaining Order in a List. In: Proc. the 19th Annual ACM Symposium on Theory of Computing (STOC), pp. 365–372. ACM Press, New York (1987)Google Scholar
  12. 12.
    Beckmann, N., Kriegel, H.: The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. In: Proc. ACM SIGMOD Intl. Conf., pp. 322–331 (1990)Google Scholar
  13. 13.
    Hjaltason, G.R.l., Samet, H.: Distance Browsing in Spatial Database. ACM Transactions on Database Systems 24(2), 265–318 (1999)CrossRefGoogle Scholar
  14. 14.
    Schmidt, A.R., Waas, F., Kersten, M.L., Florescu, D., Manolescu, I., Carey, M.J., Busse, R.: The XML Benchmark Project. Technical Report INSR0103, CWI, Amsterdam, The Netherlands (April 2001)Google Scholar
  15. 15.
  16. 16.
    Jiang, H., Lu, H., Wang, W., Ooi, B.C.: XR-Tree: Indexing XML Data for Efficient Structural Joins. In: Proc. International Conference on Data Engineering (ICDE), pp. 253–263 (2003)Google Scholar
  17. 17.

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yaokai Feng
    • 1
  • Akifumi Makinouchi
    • 1
  1. 1.Graduate School of Information Science and Electrical EngineeringKyushu UniversityFukuoka CityJapan

Personalised recommendations