High performance distributed parallel query processing
The emerging between distributed and parallel technologies gives an enormous impact to database systems. In this paper, we present a 'Correction, Migration and Partition' approach for distributed parallel query processing. The correction process is to update query execution plan dynamically particularly when initial estimate is found to be wrong, whereas the migration process focuses on re-allocation of subquery from high load sites to low load sites to improve the performance of query processing. Further improvement may be achieved in the partitioning process in which parallel processing is applied to subquery when there are low load sites available after the migration process. This proposed approach seems to give benefits to database systems that are based on the distributed and parallel technologies.
parallel processing distributed parallel databases dynamic query optimization load balancing