On-Line Analytical Processing (OLAP) refers to the technologies that allow users to efficiently retrieve data from the data warehouse for decision-support purposes. Data warehouses tend to be extremely large--it is quite possible for a data warehouse to be hundreds of gigabytes to terabytes in size [3]. Queries tend to be complex and ad hoc, often requiring computationally expensive operations such as joins and aggregation. Given this, we are interested in developing strategies for improving query processing in data warehouses by exploring the applicability of parallel processing techniques. In particular, we exploit the natural partitionability of a star schema and render it even more efficient by applying DataIndexes--a storage structure that serves both as an index as well as data and lends itself naturally to vertical partitioning of the data. Dataindexes are derived from the various special purpose access mechanisms currently supported in commercial OLAP products. Specifically, we...
Anindya Datta, Debra E. VanderMeer, Krithi Ramamri