White Papers

Statistical Learning Techniques for Costing XML Queries

Overview Developing cost models for query optimization is significantly harder for XML queries than for traditional relational queries. The reason is that XML query operators are much more complex than relational operators such as table scans and joins. This paper proposes a new approach, called Comet, to modeling the cost of XML operators; to the knowledge, Comet is the first method ever proposed for addressing the XML query costing problem. As in relational cost estimation, Comet exploits a set of system catalog statistics that summarizes the XML data; the set of "Simple path" statistics that one proposes is new, and is well suited to the XML setting.

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Publisher
University of Waterloo
File Format
PDF
Date Published
Dec 4, 2008
Format
White Papers
Topics
XML, Learning Management Systems, Programming Languages

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