Type-based XML projection

  • Véronique Benzaken
  • , Giuseppe Castagna
  • , Dario Colazzo
  • , Kim Nguyên

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

XML data projection (or pruning) is one of the main optimization techniques recently adopted in the context of main-memory XML query-engines. The underlying idea is quite simple: given a query Q over a document D, the subtrees of D not necessary to evaluate Q are pruned, thus obtaining a smaller document D′. Then Q is executed over D′, hence avoiding to allocate and process nodes that will never be reached by navigational specifications in Q. In this article, we propose a new approach, based on types, that greatly improves current solutions. Besides providing comparable or greater precision and far lesser pruning overhead our solution, unlike current approaches, takes into account backward axes, predicates, and can be applied to multiple queries rather than just to single ones. A side contribution is a new type system for XPath able to handle backward axes, which we devise in order to apply our solution. The soundness of our approach is formally proved. Furthermore, we prove that the approach is also complete (i.e., yields the best possible type-driven pruning) for a relevant class of queries and DTDs, which include nearly all the queries used in the XMark and XPathMark benchmarks. These benchmarks are also used to test our implementation and show and gauge the practical benefits of our solution.

Original languageEnglish
Title of host publicationVLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases
PublisherAssociation for Computing Machinery
Pages271-282
Number of pages12
ISBN (Print)1595933859, 9781595933850
Publication statusPublished - 1 Jan 2006
Externally publishedYes
Event32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: 12 Sept 200615 Sept 2006

Publication series

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

Conference

Conference32nd International Conference on Very Large Data Bases, VLDB 2006
Country/TerritoryKorea, Republic of
CitySeoul
Period12/09/0615/09/06

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