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Research on partitioning algorithm based on RDF graph

机译:基于RDF图的分区算法研究

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With the increasing size of the RDF dataset, the application of parallel computing frameworks is applying more and more widely in big data. In order to realize the parallel query of data, an edge partitioning algorithm is proposed based on RDF sentence graph. Firstly, the algorithm transforms the RDF graph into an RDF sentence graph using coarsening and partitioning. Secondly, the minimum degree vertex partitioning algorithm is put forward to partition the RDF sentence graph. Finally, according to the equivalence thought between edge segmentation of RDF sentence and vertex segmentation of RDF graph, the intersection between RDF subgraphs is the vertex cut set of RDF graph to achieve parallel query of RDF data. The experimental results show that the algorithm's partitioning time and efficiency are better than the traditional algorithms.
机译:随着RDF数据集的越来越大,并行计算框架的应用程序在大数据中越来越广泛地应用。为了实现数据的并行查询,基于RDF句子图提出了边缘划分算法。首先,该算法使用粗化和分区将RDF图转换为RDF句子图。其次,提出了最小程度的顶点分区算法来分区RDF句子图。最后,根据RDF句子的边缘分割与RDF图的顶点分割的等价思想,RDF子图之间的交叉点是RDF图的顶点切割集,以实现RDF数据的并行查询。实验结果表明,算法的分区时间和效率优于传统算法。

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