Benchmarking holistic approaches to XML tree pattern query processing
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
Extending XQuery with a pattern matching facility
XSym'10 Proceedings of the 7th international XML database conference on Database and XML technologies
Adding logical operators to tree pattern queries on graph-structured data
Proceedings of the VLDB Endowment
Multidimensional implementation of stream ADT
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
CIS-X: A compacted indexing scheme for efficient query evaluation of XML documents
Information Sciences: an International Journal
The VLDB Journal — The International Journal on Very Large Data Bases
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As business and enterprises generate and exchange XML data more often, there is an increasing need for efficient processing of queries on XML data. Searching for the occurrences of a tree pattern query in an XML database is a core operation in XML query processing. Prior works demonstrate that holistic twig pattern matching algorithm is an efficient technique to answer an XML tree pattern with parent-child (P-C) and ancestor-descendant (A-D) relationships, as it can effectively control the size of intermediate results during query processing. However, XML query languages (e.g., XPath and XQuery) define more axes and functions such as negation function, order-based axis, and wildcards. In this paper, we research a large set of XML tree pattern, called extended XML tree pattern, which may include P-C, A-D relationships, negation functions, wildcards, and order restriction. We establish a theoretical framework about “matching cross” which demonstrates the intrinsic reason in the proof of optimality on holistic algorithms. Based on our theorems, we propose a set of novel algorithms to efficiently process three categories of extended XML tree patterns. A set of experimental results on both real-life and synthetic data sets demonstrate the effectiveness and efficiency of our proposed theories and algorithms.