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Data partition and parallel evaluation of Datalog programs

机译:数据分区和Datalog程序的并行评估

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Parallel bottom-up evaluation provides an alternative for the efficient evaluation of logic programs. Existing parallel evaluation strategies are neither effective nor efficient in determining the data to be transmitted among processors. In this paper, we propose re different strategy, for general Datalog programs, that is based on the partitioning of data rather than that of rule instantiations. The partition and processing schemes defined in this paper are more general than those in existing strategies. A parallel evaluation algorithm is given based on the semi-naive bottom-up evaluation. A notion of potential usefulness is recognized as a data transmission criterion to reduce, both effectively and efficiently, the amount of data transmitted. Heuristics and algorithms are proposed for designing the partition and processing schemes for a given program. Results from an experiment show that the strategy proposed in this paper has many promising features.
机译:并行的自下而上的评估为逻辑程序的有效评估提供了一种选择。现有的并行评估策略在确定要在处理器之间传输的数据时既无效也不高效。在本文中,对于一般的Datalog程序,我们提出了另一种策略,该策略基于数据分区而不是规则实例化。与现有策略相比,本文定义的分区和处理方案更为通用。基于半幼稚自下而上的评估给出了并行评估算法。潜在有用性的概念被认为是一种数据传输标准,可以有效而高效地减少传输的数据量。提出了启发式算法和算法,用于设计给定程序的分区和处理方案。实验结果表明,本文提出的策略具有许多有前途的特征。

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