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Graph partitioning for massive scale graphs

机译:大规模比例图的图分区

摘要

Graph partitioning for massive scale graphs is described, such as for graphs having vertices representing people and edges representing connections between people in a social networking system; or for graphs where the vertices represent other items and the edges represent relationships between the items. In various embodiments a graph data allocator receives a graph vertex and its edges and allocates the vertex to one of a plurality of clusters each associated with one or more computing devices. In various embodiments the allocation is made by optimizing an objective function which takes into account both a cost of edges between clusters and a cost related to sizes of the clusters. In some examples the cost related to sizes of the clusters comprises a convex function applied to each of the cluster sizes. In examples, computations on the graph data are carried out with reduced runtimes and communications cost.
机译:描述了用于大规模图形的图形划分,诸如用于在社交网络系统中具有表示人的顶点和表示人之间的连接的边的图;等等。或用于图形,其中顶点表示其他项目,而边线表示项目之间的关系。在各个实施例中,图数据分配器接收图顶点及其边缘,并将该顶点分配给每个与一个或多个计算设备相关联的多个集群之一。在各种实施例中,通过优化目标函数来进行分配,该目标函数考虑了集群之间的边缘成本和与集群大小相关的成本。在一些示例中,与群集的大小有关的成本包括应用于每个群集大小的凸函数。在示例中,以减少的运行时间和通信成本来执行对图形数据的计算。

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