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  1. Proceedings of the 8th annual ACM international workshop on Web information and data management (WIDM '06)
  2. Efficient evaluation of n-ary conjunctive queries over trees and graphs
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Efficient evaluation of n-ary conjunctive queries over trees and graphs

Content Provider ACM Digital Library
Author Furche, Tim Schroeder, Andreas Bry, François Linse, Benedikt
Abstract N-ary conjunctive queries, i.e., queries with any number of answer variables, are the formal core of many Web query languages including XSLT, XQuery, SPARQL, and Xcerpt. Despite a considerable body of research on the optimization of such queries over tree-shaped XML data, little attention has been paid so far to efficient access to graph-shaped XML, RDF, or Topic Maps. We propose the first evaluation technique for n-ary conjunctive queries that applies to both tree- and graph-shaped data and retains the same complexity as the best known approaches that are restricted to tree-shaped data only. Furthermore, the approach treats tree and graph-shaped queries uniformly without sacrificing evaluation complexity on the restricted query class. The core of the evaluation technique is based on dynamic programming using a memoization data structure, called "memoization matrix". It can be populated and consumed in different ways. For each of population and consumption, we propose two resp. three algorithms each having their own advantages. The complexity of the algorithms is compared analytically and experimentally.
Starting Page 11
Ending Page 18
Page Count 8
File Format PDF
ISBN 1595935258
DOI 10.1145/1183550.1183555
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2006-11-10
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Semi-structured data Rdf Query evaluation and optimization Xml Memoization Conjunctive queries
Content Type Text
Resource Type Article
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