An efficient path index for querying semi-structured data

  • Authors:

  • Michael Barg;Raymond K. Wong;Franky Lam

  • Affiliations:

  • School of Computer Science and Engineering, University of New South Wales, Sydney, Australia;School of Computer Science and Engineering, University of New South Wales, Sydney, Australia;School of Computer Science and Engineering, University of New South Wales, Sydney, Australia

  • Venue:
  • APWeb'03 Proceedings of the 5th Asia-Pacific web conference on Web technologies and applications
  • Year:
  • 2003

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Abstract

The richness of semi-structured data allows data of varied and inconsistent structures to be stored in a single database. Such data can be represented as a graph, and queries can be constructed using path expressions, which describe traversals through the graph. Instead of providing optimal performance for a limited range of path expressions, we propose a mechanism which is shown to have consistent and high performance for path expressions of any complexity, including those with descendant operators (path wildcards). We further detail mechanisms which employ our index to perform more complex processing, such as evaluating both path expressions containing links and entire (sub) queries containing path based predicates. Performance is shown to be independent of the number of terms in the path expression(s), even where these expressions contain wildcards. Experiments show that our index is faster than conventional methods by up to two orders of magnitude for certain query types, is compact, and scales well.