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Lossless Reduction of Datacubes

  • Conference paper
Database and Expert Systems Applications (DEXA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4080))

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Abstract

Datacubes are specially useful for answering efficiently queries on data warehouses. Nevertheless the amount of generated aggregated data is incomparably more voluminous than the initial data which is itself very large. Recently, research work has addressed the issue of a concise representation of datacubes in order to reduce their size. The approach presented in this paper fits in a similar trend. We propose a concise representation, called Partition Cube, based on the concept of partition and define an algorithm to compute it. Various experiments are performed in order to compare our approach with methods fitting in the same trend. This comparison relates to the efficiency of algorithms computing the representations, the main memory requirements, and the storage space which is necessary.

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Casali, A., Cicchetti, R., Lakhal, L., Novelli, N. (2006). Lossless Reduction of Datacubes. In: Bressan, S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2006. Lecture Notes in Computer Science, vol 4080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11827405_40

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  • DOI: https://doi.org/10.1007/11827405_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37871-6

  • Online ISBN: 978-3-540-37872-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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