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Query Performance Optimization in XML Data Warehouses

Query Performance Optimization in XML Data Warehouses

Hadj Mahboubi, Jérôme Darmont
Copyright: © 2011 |Pages: 22
ISBN13: 9781616920166|ISBN10: 1616920165|ISBN13 Softcover: 9781616923785|EISBN13: 9781616920173
DOI: 10.4018/978-1-61692-016-6.ch014
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MLA

Mahboubi, Hadj, and Jérôme Darmont. "Query Performance Optimization in XML Data Warehouses." E-Strategies for Resource Management Systems: Planning and Implementation, edited by Eshaa Alkhalifa, IGI Global, 2011, pp. 232-253. https://doi.org/10.4018/978-1-61692-016-6.ch014

APA

Mahboubi, H. & Darmont, J. (2011). Query Performance Optimization in XML Data Warehouses. In E. Alkhalifa (Ed.), E-Strategies for Resource Management Systems: Planning and Implementation (pp. 232-253). IGI Global. https://doi.org/10.4018/978-1-61692-016-6.ch014

Chicago

Mahboubi, Hadj, and Jérôme Darmont. "Query Performance Optimization in XML Data Warehouses." In E-Strategies for Resource Management Systems: Planning and Implementation, edited by Eshaa Alkhalifa, 232-253. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-61692-016-6.ch014

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Abstract

XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native-XML database management systems (DBMSs) currently bear limited performances and it is necessary to research for ways to optimize them. In this chapter, the authors present two such techniques. First, they propose an XML join index that is specifically adapted to the multidimensional architecture of XML warehouses. It eliminates join operations while preserving the information contained in the original warehouse. Second, the authors present a strategy for selecting XML materialized views by clustering the query workload. To validate these proposals, the authors measure the response time of a set of decision-support XQueries over an XML data warehouse, with and without using their optimization techniques. The authors’ experimental results demonstrate their efficiency, even when queries are complex and data are voluminous.

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