OLAP Dimension Constraints

In multidimensional data models intended for online analytic processing (OLAP), data are viewed as points in a multidimensional space. Each dimension has structure, described by a directed graph of categories, a set of members for each category, and a child/parent relation between members. An important application of this structure is to use it to infer summarizability, that is, whether an aggregate view defined for some category can be correctly derived from a set of precomputed views defined for other categories. A dimension is called heterogeneous if two members in a given category are allowed to have ancestors in different categories. In previous work, we studied the problem of inferring summarizability in a particular class of heterogeneous dimensions. In this paper, we propose a class of integrity constraints and schemas that allow us to reason about summarizability in general heterogeneous dimensions. We introduce the notion of frozen dimensions, which are minimal homogeneous d...

• Type: Conference
• Year: 2002
• Where: PODS
• Authors: Carlos A. Hurtado, Alberto O. Mendelzon
• Keywords: Database, Dimension Constraints, Heterogeneous Dimension, Heterogeneous Dimensions, PODS 2002