计算机科学 ›› 2017, Vol. 44 ›› Issue (4): 188-192.doi: 10.11896/j.issn.1002-137X.2017.04.041
王珍,韩忠明,李晋
WANG Zhen, HAN Zhong-ming and LI Jin
摘要： 随着社会网络数据规模的递增,结构洞节点计算涉及的计算量呈几何级增长,如何构建有效的并行化算法并缩短算法运行的时间成为当前研究的难点。针对大规模数据量下结构洞节点发现算法的不足,利用并行化思想设计实现了基于MapReduce的结构洞节点发现算法。该算法通过DBLP,YouTube和Califonia公路网这3组规模不同的数据集在Hadoop集群上运行的实验结果表明,增加DataNode机器节点的数量能够缩短算法运行的时间,提高运行效率且具有良好的并行加速比和扩展性能。
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