Physical and virtual partitioning in OLAP database clusters - Furtado, C.; Lima, A. A. B.; Pacitti, E.; Valduriez, P.; Mattoso, M. (Anais do International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD); 2005: Anais do XVII International Symposium on Computer Architecture and High Performance Computing, 2005)
On-line analytical processing (OLAP) applications require high performance database support to achieve good response time (crucial for decision making). Database clusters provide a cost-effective alternative to parallel database systems. For OLAP applications, that typically use heavy weight queries, intra-query parallelism yields better performance as it reduces the execution time of individual queries. Intra-query parallelism is based on processing the same query on different subsets of the query table. Combining physical and virtual partitioning to define table subsets provides flexibility in intra-query parallelism while optimizing disk space usage and data availability. Experiments with our partitioning technique using TPC-H benchmark queries on a 32-dual node cluster gave linear and super-linear speedup, thereby reducing significantly the time of typical OLAP heavy weight queries.