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<p><it>Abstract</it>—Shared nothing multiprocessor architecture is known to be more scalable to support very large databases. Compared to other join strategies, a hash-based join algorithm is particularly efficient and easily parallelized for this computation model. However, this hardware structure is very sensitive to the skew in tuple distribution. Unless the parallel hash join algorithm includes some dynamic load balancing mechanism, the skew effect can severely deteriorate the system performance. In this paper, we investigate this issue. In particular, three parallel hash join algorithms are presented. We implement a simulator to study the effectiveness of these schemes. The simulation model is validated by comparing the simulation results to those produced by the actual implementation of the algorithms running on a multiprocessor system. Our performance study indicates that a naive approach is not able to provide tangible savings. However, the carefully designed strategies can offer substantial improvement over conventional techniques for a wide range of skew conditions.</p>
Database machine, load balancing, parallel join algorithm, query processing, relational database.

C. M. Hua, K. A. Hua and C. Lee, "Dynamic Load Balancing in Multicomputer Database Systems Using Partition Tuning," in IEEE Transactions on Knowledge & Data Engineering, vol. 7, no. , pp. 968-983, 1995.
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