Materialization of Fragmented Views in Multidimensional Databases

A multidimensional database can be seen as a collection of multidimensional cubes centered on facts of interest. In the context of multidimensional databases imple-mented on relational DBMSs, the most eective technique to enhance performances consists in materializing redundant aggregates called views. In the classical ap-proach to materialization, each view includes all and only the measures of the cube it aggregates. In this paper we investigate the benets of materializing views in vertical fragments, each possibly including measures from dierent cubes, aimed at minimizing the workload response time. In fact, the measures of a single cube are not necessarily always requested together in queries; on the other hand, drill-across queries involve measures taken from two or more cubes. We formalize the fragmentation problem as a 0-1 integer linear programming problem, which is then solved by means of a standard integer programming solver to determine the opti-mal fragmentation for a given workload. Finally, we demonstrate the usefulness of fragmentation by presenting a large set of experimental results based on the TPC-H benchmark