Edinburgh Research Explorer

Tree Pattern Aggregation for Scalable XML Data Dissemination

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

  • Chee Yong Chan
  • Wenfei Fan
  • Pascal Felber
  • Minos N. Garofalakis
  • Rajeev Rastogi

Related Edinburgh Organisations

Original languageEnglish
Title of host publicationVLDB 2002, Proceedings of 28th International Conference on Very Large Data Bases, August 20-23, 2002, Hong Kong, China
Number of pages12
Publication statusPublished - 2002


With the rapid growth of XML-document traffic on the Internet, scalable content-based dissemination of XML documents to a large, dynamic group of consumers has become an important research challenge. To indicate the type of content that they are interested in, data consumers typically specify their subscriptions using some XML pattern specification language (e.g., XPath).
Given the large volume of subscribers, system scalability and efficiency mandate the ability to aggregate the set of consumer subscriptions to a smaller set of content specifications, so as to both reduce their storage space requirements as well as speed up the document subscription matching process. In this paper, we provide the first systematic study of subscription aggregation where subscriptions are specified with tree patterns (an important subclass of XPath expressions). The main challenge is to aggregate an input set of tree patterns
into a smaller set of generalized tree patterns such that: (1) a given space constraint on the total size of the subscriptions is met, and (2) the loss in precision (due to aggregation) during document filtering is minimized. We propose an efficient tree-pattern aggregation algorithm that makes effective use of document-distribution statistics in order to compute a precise set of aggregate
tree patterns within the allotted space budget. As part of our solution, we also develop several novel algorithms for tree-pattern containment and minimization,
as well as “least-upper-bound” computation for a set of tree patterns. These results are of interest in their own right, and can prove useful in other domains, such as XML query optimization. Extensive results from a prototype implementation validate our approach.

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