Twig2Stack: bottom-up processing of generalized-tree-pattern queries over XML documents

  • Authors:
  • Songting Chen;Hua-Gang Li;Junichi Tatemura;Wang-Pin Hsiung;Divyakant Agrawal;K. Selçuk Candan

  • Affiliations:
  • NEC Laboratories America, Cupertino, CA;Department of Computer Science, University of California, Santa Barbara, CA and NEC Laboratories America;NEC Laboratories America, Cupertino, CA;NEC Laboratories America, Cupertino, CA;NEC Laboratories America, Cupertino, CA;NEC Laboratories America, Cupertino, CA

  • Venue:
  • VLDB '06 Proceedings of the 32nd international conference on Very large data bases
  • Year:
  • 2006

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Abstract

Tree pattern matching is one of the most fundamental tasks for XML query processing. Holistic twig query processing techniques [4, 16] have been developed to minimize the intermediate results, namely, those root-to-leaf path matches that are not in the final twig results. However, useless path matches cannot be completely avoided, especially when there is a parent-child relationship in the twig query. Furthermore, existing approaches do not consider the fact that in practice, in order to process XPath or XQuery statements, a more powerful form of twig queries, namely, Generalized-Tree-Pattern (GTP) [8] queries, is required. Most existing works on processing GTP queries generally calls for costly post-processing for eliminating redundant data and/or grouping of the matching results.In this paper, we first propose a novel hierarchical stack encoding scheme to compactly represent the twig results. We introduce Twig2Stack, a bottom-up algorithm for processing twig queries based on this encoding scheme. Then we show how to efficiently enumerate the query results from the encodings for a given GTP query. To our knowledge, this is the first GTP matching solution that avoids any post path-join, sort, duplicate elimination and grouping operations. Extensive performance studies on various data sets and queries show that the proposed Twig2Stack algorithm not only has better twig query processing performance than state-of-the-art algorithms, but is also capable of efficiently processing the more complex GTP queries.