Twig2Stack: Bottom-up processing of Generalized-Tree-Pattern queries over XML documents

Songting Chen, Hua Gang Li, Junichi Tatemura, Wang Pin Hsiung, Divyakant Agrawal, K. Selçuk Candan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

160 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationVLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases
PublisherAssociation for Computing Machinery
Pages283-294
Number of pages12
ISBN (Print)1595933859, 9781595933850
StatePublished - 2006
Externally publishedYes
Event32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: Sep 12 2006Sep 15 2006

Publication series

NameVLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases

Other

Other32nd International Conference on Very Large Data Bases, VLDB 2006
Country/TerritoryKorea, Republic of
CitySeoul
Period9/12/069/15/06

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems
  • Software
  • Information Systems and Management

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