A Case for Parallelism in Data Warehousing and OLAP

In recent years the database community has experienced a tremendous increase in the availability of new technologies to support eecient storage and retrieval of large volumes of data, namely data warehousing and On-Line Analytical Processing (OLAP) products. Ef-cient query processing is critical in such an environment , yet achieving quick response times with OLAP queries is still largely an open issue. In this paper we propose a solution approach to this problem by applying parallel processing techniques to a warehouse environment. We suggest an eecient partitioning strategy based on the relational representation of a data warehouse (i.e., star schema). Furthermore, we incorporate a particular indexing strategy, DataIndexes, to further improve query processing times and parallel resource utilization, and propose a preliminary parallel star-join strategy.