Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
Enterprises have been storing multidimensional data, using a star or snowflake schema, in relational databases for many years. Over time, relational database vendors have added optimizations that enhance query performance on these schemas. During the 1990s many special-purpose databases were developed that could handle added calculational complexity and that generally performed better than relational engines. DB2® has added a number of features that make it more competitive with these special-purpose databases. In this paper, we define meta-data extensions that allow designers of multidimensional schemas to describe the structure of those schemas to multidimensional query and analysis tools. The SQL (Structured Query Language) extensions include a "cube" object that returns row sets that are "slices" of the cube. We also describe Web services for OLAP (online analytical processing) that provide meta-data for multidimensional data, as well as XML (Extensible Markup Language) query results.
Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
Alessandro Morari, Roberto Gioiosa, et al.
IPDPS 2011
Rajiv Ramaswami, Kumar N. Sivarajan
IEEE/ACM Transactions on Networking
Corneliu Constantinescu
SPIE Optical Engineering + Applications 2009