Parallel sorting on a shared-nothing architecture using probabilistic splitting

D. DeWitt, J. Naughton, Donovan A. Schneider
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引用次数: 167

Abstract

The authors consider the problem of external sorting in a shared-nothing multiprocessor. A critical step in the algorithms the authors consider is to determine the range of sort keys to be handled by each processor. They consider two techniques for determining these ranges of sort keys: exact splitting, using a parallel version of the algorithm proposed by Iyer, Ricard, and Varman; and probabilistic splitting, which uses sampling to estimate quantiles. They present analytic results showing that probabilistic splitting performs better than exact splitting. Finally, the authors present experimental results from an implementation of sorting probabilistic splitting in the Gamma parallel database machine.<>
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使用概率分裂的无共享架构上的并行排序
研究了无共享多处理器中的外部排序问题。作者认为算法中的一个关键步骤是确定每个处理器要处理的排序键的范围。他们考虑了确定这些排序键范围的两种技术:精确分割,使用Iyer, Ricard和Varman提出的算法的并行版本;概率分裂,用抽样来估计分位数。他们给出的分析结果表明,概率分裂比精确分裂性能更好。最后,作者给出了在Gamma并行数据库机上实现排序概率分裂的实验结果。
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High-quality and high-performance full-text document retrieval: the Parallel InfoGuide System Parallel sorting on a shared-nothing architecture using probabilistic splitting Marker-passing on a parallel knowledge processing testbed Achieving throughput and functionality in a common architecture: the Datacycle experiment Load balancing algorithms for parallel database processing on shared memory multiprocessors
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