Fan Jing Meng, Ying Huang, et al.
ICEBE 2007
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.
Fan Jing Meng, Ying Huang, et al.
ICEBE 2007
Yun Mao, Hani Jamjoom, et al.
CoNEXT 2006
Thomas M. Cover
IEEE Trans. Inf. Theory
Joel L. Wolf, Mark S. Squillante, et al.
IEEE Transactions on Knowledge and Data Engineering