有谁有使用MapReduce解决网络流量问题的经验
MapReduce 已被证明能够以并行/分布式方式强大地解决大型数据集问题。
已知一些组合优化问题能够扩展到非常大的规模，例如最大网络流、最小成本网络流、多商品最小成本流或最短距离路径/路径对问题。
有人有应用 MapReduce 处理此类问题的成功/失败经验吗？您能否分享一下您的意见，用 MapReduce 来解决此类问题是好是坏？
MapReduce has been shown to be powerful solve problem with large data sets in a parallel/distributed way.
Some combinational optimization problem such as maximum network flow, minimum cost network flow, multi commodity minimum cost flows, or shortest distance path/path-pair problems are known to be able to scale to very large size.
Does anyone has successful/failure experience to apply MapReduce to handle these types of problem? Could you please share your opinion whether it is a good fit or bad idea to resolve to MapReduce to solve such type of problems?
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Felix Halim 等人于 2011 年发表了一篇论文，讨论了他们如何解决最大流量问题使用地图减少。他们“能够在合理的时间内使用 21 台机器计算具有 4.11 亿个顶点和 310 亿条边的图上的最大流”！
Felix Halim and others published a paper in 2011 that discusses how they solve max flow problem using map reduce. They "are able to compute max-flow on graph with 411 million vertices and 31 billion edges using 21 machines in reasonable time"!