Effective skew handling for parallel sorting in multiprocessor database systems

A consensus on a parallel architecture for very large database management has emerged. This architecture is based on a shared-nothing hardware organization. The computation model is very sensitive to skew in tuple distribution, however. The sorting operation is frequently used for database processing. For example sorting may be requested by users through the use of Distinct, Order By and Group By clauses in SQL. Although load balancing incurs processing costs, and therefore can have a profound influence on the optimized execution plan of a query, only few of the existing parallel sorting executions consider this factor. We present two parallel sorting algorithms using the dynamic load balancing technique to address the data skew problem. Our performance study indicates that the proposed parallel sorting techniques can provide very impressive performance improvement over conventional approaches.