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项目已死还是作者已死？
有没有考虑过先实现一下Apache Spark里的RDD，在此基础上实现分布式机器学习算法?
我用Spark写过两个机器学习算法，Naive Bayes classifier, Random forest, Apache Spark 的 RDD 是一个比Map-reduce和MPI更好用的分布式框架，表达力也很强。
看样子你目前是想直接使用golang 的 channel 实现分布式机器学习算法？这样的话，跟直接用MPI差不多，太底层，写的代码会很罗嗦。
方便程度：Spark > Hadoop > MPI， 代码简洁度：Spark > Hadoop > MPI，限制程度：MapReduce > Spark > MPI，MPI是最自由的，写起来也是最麻烦的，所以任何分布式计算框架，都似乎是在抽象和性能之间进行折中。
只有用更高层的抽象工具，写机器学习算法才会更简洁。
对了，Apache Tez，也是一个DAG计算框架（跟Spark很类似，本质上都是DAG），你也可以看看。还有MSRA的 Dryad，等等。我个人觉得Spark的RDD平衡的更好，也有非常成熟的实现，就是Spark本身。
关于用 golang 实现 Spark的RDD，有一个项目在此 Gopark，不过不太活跃，但是可以联系作者，一起做形成合力，照目前这种活跃度，项目完工遥遥无期。。。。
项目已死？
最后没成型吗？
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