2010 IEEE 26th International Conference on Data Engineering (ICDE 2010) (2010)
Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
Diego Arroyuelo , Yahoo! Research Latin America, Chile
Francisco Claude , David R. Cheriton School of Computer Science, University of Waterloo, Canada
Sebastian Maneth , NICTA, Australia
Veli Maakinen , Dept. of Computer Science, University of Helsinki, Finland
Gonzalo Navarro , Dept. of Computer Science, University of Chile, Chile
Kim Nguyen , NICTA, Australia
Jouni Siren , Dept. of Computer Science, University of Helsinki, Finland
Niko Valimaki , Dept. of Computer Science, University of Helsinki, Finland
A large fraction of an XML document typically consists of text data. The XPath query language allows text search via the equal, contains, and starts-with predicates. Such predicates can be efficiently implemented using a compressed self-index of the document's text nodes. Most queries, however, contain some parts querying the text of the document, plus some parts querying the tree structure. It is therefore a challenge to choose an appropriate evaluation order for a given query, which optimally leverages the execution speeds of the text and tree indexes. Here the SXSI system is introduced. It stores the tree structure of an XML document using a bit array of opening and closing brackets plus a sequence of labels, and stores the text nodes of the document using a global compressed self-index. On top of these indexes sits an XPath query engine that is based on tree automata. The engine uses fast counting queries of the text index in order to dynamically determine whether to evaluate top-down or bottom-up with respect to the tree structure. The resulting system has several advantages over existing systems: (1) on pure tree queries (without text search) such as the XPathMark queries, the SXSI system performs on par or better than the fastest known systems MonetDB and Qizx, (2) on queries that use text search, SXSI outperforms the existing systems by 1–3 orders of magnitude (depending on the size of the result set), and (3) with respect to memory consumption, SXSI outperforms all other systems for counting-only queries.
K. Nguyen et al., "Fast in-memory XPath search using compressed indexes," 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)(ICDE), Long Beach, CA, USA, 2010, pp. 417-428.