Fast in-memory XPath search using compressed indexes

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Arroyuelo , D , Claude , F , Maneth , S , Mäkinen , V , Navarro , G , Nguyen , K , Sirén , J & Välimäki , N 2010 , Fast in-memory XPath search using compressed indexes . in ICDE 2010 : 26th IEEE International Conference on Data Engineering . IEEE Computer Society , pp. 417-428 , International Conference on Data Engineering , Long Beach, California , United States , 01/03/2010 .

Title: Fast in-memory XPath search using compressed indexes
Author: Arroyuelo, Diego; Claude, Francisco; Maneth, Sebastian; Mäkinen, Veli; Navarro, Gonzalo; Nguyen, Kim; Sirén, Jouni; Välimäki, Niko
Contributor organization: Department of Computer Science
Helsinki Graduate School in Computer Science and Engineering (Hecse)
Genome-scale Algorithmics research group / Veli Mäkinen
Publisher: IEEE Computer Society
Date: 2010
Language: eng
Number of pages: 12
Belongs to series: ICDE 2010
ISBN: 978-1-4244-5446-4
Abstract: 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.
Subject: 113 Computer and information sciences
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: acceptedVersion

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