拓扑感知并行连接

Xiao Hu, Paraschos Koutris
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引用次数: 0

摘要

我们在拓扑感知计算模型中研究并行连接算法的设计和分析。在该模型中,网络被建模为有向图,每条边都与成本函数相关联,而成本函数取决于两个端点之间传输的数据和链路带宽。计算以同步轮进行,每一轮的成本以网络中所有边的最大成本来衡量。我们的主要成果是对称树拓扑上的渐进最优连接算法。该算法将先前针对集合相交和卡特积的拓扑感知协议推广到任意输入分布上的二进制连接,并可能存在数据倾斜。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topology-aware Parallel Joins
We study the design and analysis of parallel join algorithms in a topology-aware computational model. In this model, the network is modeled as a directed graph, where each edge is associated with a cost function that depends on the data transferred between the two endpoints and the link bandwidth. The computation proceeds in synchronous rounds and the cost of each round is measured as the maximum cost over all the edges in the network. Our main result is an asymptotically optimal join algorithm over symmetric tree topologies. The algorithm generalizes prior topology-aware protocols for set intersection and cartesian product to a binary join over an arbitrary input distribution with possible data skew.
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