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XSelMark: A Micro-benchmark for Selectivity Estimation Approaches of XML Queries

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Database and Expert Systems Applications (DEXA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5181))

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Abstract

Estimating the sizes of query results and intermediate results is a crucial part of any effective query optimization process. Due to several reasons, the selectivity estimation problem in the XML domain is more complicated than that in the relational domain. Several research efforts have proposed selectivity estimation approaches in the XML domain. Lacking of a suitable benchmark was one of the main reasons which prevented a real assessment and comparison between the approaches to be conducted. In this paper we propose a selectivity estimation benchmark for XML queries, XSelMark. It consists of a set of 25 queries organized into seven groups and covers the main aspects of selectivity estimation of XML queries. These queries have been designed with respect to an XML document instance of a popular benchmark for XML data management, XMark. In addition, we suggest some criteria of assessing the capability and quality of XML queries selectivity estimation approaches. Finally, we use the proposed benchmark to assess the capabilities of the-state-of-the-art of the selectivity estimation approaches.

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References

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Authors and Affiliations

  1. National ICT Australia (NICTA), Sydney, Australia

    Sherif Sakr

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  1. Sherif Sakr
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Sourav S. Bhowmick Josef Küng Roland Wagner

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© 2008 Springer-Verlag Berlin Heidelberg

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Sakr, S. (2008). XSelMark: A Micro-benchmark for Selectivity Estimation Approaches of XML Queries. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2008. Lecture Notes in Computer Science, vol 5181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85654-2_65

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  • DOI: https://doi.org/10.1007/978-3-540-85654-2_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85653-5

  • Online ISBN: 978-3-540-85654-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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