Abstract
Many parallel join algorithms have been proposed for parallel relational database systems. Among them, the parallel hash-based join algorithm has been found to be superior to other ones for the uniform distribution of data. This paper proposes an efficient algorithm, called skew resolution join algorithm (SRJA), for parallel join algorithms with skewed data. We propose a methodology for partitioning relations evenly across all processors in a parallel database system. We performed simulation experiments under the Zipf-like distribution of hashed values for join attributes.
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