Computing Partial Data Cubes for Parallel Data Warehousing Applications.

F. Dehne, T. Eavis and A. Rau-Chaplin

Abstract: 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 an 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 \( 2^{d} \) (where $d$ = dimensions) views should be computed is often not valid in practice. As a result, algorithms for computing partial datacube are required. In this paper, we describe a parallel algorithm for computing partial datacubes and preliminary experimental results.