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Pre-computing Approximate Hierarchical Range Queries in a Tree-Like Histogram

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Data Warehousing and Knowledge Discovery (DaWaK 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2737))

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Abstract

Histograms are a lossy compression technique widely applied in various application contexts, like query optimization, statistical and temporal databases, OLAP applications, and so on. This paper presents a new histogram based on a hierarchical decomposition of the original data distribution kept in a complete binary tree. This tree, thus containing a set of pre-computed hierarchical queries, is encoded in a compressed form using bit saving in representing integer numbers. The approach, extending a recently proposed technique based on the application of such a decomposition to the buckets of a pre-existing histogram, is shown by several experiments to improve the accuracy of the state-of-the-art histograms.

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Buccafurri, F., Lax, G. (2003). Pre-computing Approximate Hierarchical Range Queries in a Tree-Like Histogram. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2003. Lecture Notes in Computer Science, vol 2737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45228-7_35

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  • DOI: https://doi.org/10.1007/978-3-540-45228-7_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40807-9

  • Online ISBN: 978-3-540-45228-7

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