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APEX: an adaptive path index for XML data


Chin-Wan Chung, Jun-Ki Min, and Kyuseok Shim

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Abstract

The emergence of the Web has increased interests in XML data. XML query languages such as XQuery and XPath use label paths to traverse the irregularly structured data. Without a structural summary and efficient indexes, query processing can be quite inefficient due to an exhaustive traversal on XML data. To overcome the inefficiency, several path indexes have been proposed in the research community. Traditional indexes generally record all label paths from the root element in XML data. Such path indexes may result in performance degradation due to large sizes and exhaustive navigations for partial matching path queries start with the self-or-descendent axis("//").In this paper, we propose APEX, an adaptive path index for XML data. APEX does not keep all paths starting from the root and utilizes frequently used paths to improve the query performance. APEX also has a nice property that it can be updated incrementally according to the changes of query workloads. Experimental results with synthetic and real-life data sets clearly confirm that APEX improves query processing cost typically 2 to 54 times better than the existing indexes, with the performance gap increasing with the irregularity of XML data.


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