Cubes convexes

Sebastien Nedjar (1) , Alain Casali (1) , Rosine Cicchetti (1) , Lotfi Lakhal (1)

1 LIF - Laboratoire d'informatique Fondamentale de Marseille - UMR 6166

In various approaches, data cubes are pre-computed in order to answer efficiently OLAP queries. The notion of data cube has been declined in various ways: iceberg cubes, range cubes or differential cubes. In this paper, we introduce the concept of convex cube which captures all the tuples of a datacube satisfying a constraint combination. It can be represented in a very compact way in order to optimize both computation time and required storage space. The convex cube is not an additional structure appended to the list of cube variants but we propose it as a unifying structure that we use to characterize, in a simple, sound and homogeneous way, the other quoted types of cubes. Finally, we introduce the concept of emerging cube which captures the significant trend inversions. characterizations.

Domaines: Base de données [cs.DB]

Sebastien Nedjar, Alain Casali, Rosine Cicchetti, Lotfi Lakhal. Cubes convexes. Revue des Sciences et Technologies de l'Information - Série ISI : Ingénierie des Systèmes d'Information, 2006, 11 (6), pp.11-31. ⟨10.3166/isi.11.6.11-31⟩. ⟨hal-00464232⟩