Dynamic Query Scheduling in Parallel Data Warehouses

Data warehouse queries pose challenging performance problems that often necessitate the use of parallel database systems (PDBS). Although dynamic load balancing is of key importance in PDBS, to our knowledge it has not yet been investigated thoroughly for parallel data warehouses. In this study, we propose a scheduling strategy that simultaneously considers both processors and disks while utilizing the load balancing potential of a Shared Disk architecture. We compare the performance of this new method to several other approaches in a comprehensive simulation study, incorporating skew aspects and typical data warehouse features such as star schemas.