In this paper, we focus on an approach to On-Line Analytical Processing (OLAP) that is based on a database operator and data structure called the datacube. The datacube is a relational operator that is used to construct all possible views of a given data set. Efficient algorithms for computing the entire datacube – both sequentially and in parallel – have recently been proposed. However, due to space and time constraints, the assumption that all 2d (where d = dimensions) views should be computed is often not valid in practice. As a result, algorithms for computing partial datacubes are required. In this paper, we describe a parallel algorithm for computing partial datacubes and provide preliminary experimental results based on an implementation in C and MPI.
CITATION STYLE
Dehne, F., Eavis, T., & Rau-Chaplin, A. (2001). Computing partial data cubes for parallel data warehousing applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2131, pp. 319–326). Springer Verlag. https://doi.org/10.1007/3-540-45417-9_44
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