RMCC: A ROLAP data model of minimal condensed Cube

Data cubes facilitate online analytical processing (OLAP) systems greatly. Ever since the Cube-by operator was introduced by Jim Gray in 1997, techniques for computing, compressing and efficiently accessing data cubes have been substantially studied due to the enormous storage size as the number of dimensions and dimension cardinalities increase. Minimal condensed cube, one of these data cube compressing schemes, was proposed and shown to be very effective especially for the environment of RDBMSs. Although efforts on fast computation and incremental update algorithms of Minimal condensed cube has been made by researchers, a totally RDBMS based data storage model has not been investigated, which is a key issue in data cube implementation. In this paper, we proposed RMCC(relational Minimal condensed cube), a pure ROLAP-based data model for the storage structure of Minimal condensed cube. We model RMCC not only to further reduce the storage cost of Minimal condensed cube, but also that queries can be answered efficiently by mature relational database engines. We proposed a SQL framework for answering OLAP queries over RMCC by the stored procedure/function technique supported by SQL:2003.