...
首页> 外文期刊>IEICE transactions on information and systems >An Efficient Parallel Triangle Enumeration on the MapReduce Framework
【24h】

An Efficient Parallel Triangle Enumeration on the MapReduce Framework

机译:MapReduce框架上的高效并行三角枚举

获取原文

摘要

A triangle enumerating problem is one of fundamental problems of graph data. Although several triangle enumerating algorithms based on MapReduce have been proposed, they still suffer from generating a lot of intermediate data. In this paper, we propose the efficient MapReduce algorithms to enumerate every triangle in the massive graph based on a vertex partition. Since a triangle is composed of an edge and a wedge, our algorithms check the existence of an edge connecting the end-nodes of each wedge. To generate every triangle from a graph in parallel, we first split a graph into several vertex partitions and group the edges and wedges in the graph for each pair of vertex partitions. Then, we form the triangles appearing in each group. Furthermore, to enhance the performance of our algorithm, we remove the duplicated wedges existing in several groups. Our experimental evaluation shows the performance of our proposed algorithm is better than that of the state-of-the-art algorithm in diverse environments.
机译:三角形枚举问题是图形数据的基本问题之一。尽管已经提出了几种基于MapReduce的三角枚举算法,但是它们仍然会产生大量中间数据。在本文中,我们提出了有效的MapReduce算法,以基于顶点分区枚举体图中的每个三角形。由于三角形由边和楔形组成,因此我们的算法检查是否存在连接每个楔形末端节点的边。为了从图上并行生成每个三角形,我们首先将一个图分成几个顶点分区,并为每对顶点分区将图中的边和楔形分组。然后,我们形成出现在每个组中的三角形。此外,为了提高算法的性能,我们删除了多个组中存在的重复楔形。我们的实验评估表明,在各种环境下,我们提出的算法的性能都优于最新算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号