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Hadoop的slowtaskthreshold是否有助于解决竞争状况?

[英]Will Hadoop's slowtaskthreshold help to resolve race condition?

I had a question about mapreduce.job.speculative.slowtaskthreshold . 我有一个关于mapreduce.job.speculative.slowtaskthreshold的问题。

The docs say: 文档说:

The number of standard deviations by which a task's ave progress-rates must be lower than the average of all running tasks' for the task to be considered too slow. 任务的平均进度必须低于所有正在运行的任务的平均值的标准偏差数,才能使该任务太慢。

I'm curious what happens when a process is considered "too slow". 我很好奇当一个进程被认为“太慢”时会发生什么。 Does it kill and restart it? 它会杀死并重新启动它吗? Just kill? 只是杀了? I'm curious because I think I've possibly encountered a race condition and would like to tune the parameters to minimize the issue. 我很好奇,因为我认为我可能已经遇到了竞争状况,并且想调整参数以最大程度地减少问题。

Source: http://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-core/mapred-default.xml 来源: http : //hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-core/mapred-default.xml

With speculative execution, when the framework decides that a task is "too slow", it will speculatively execute the same task on a different node. 通过推测执行,当框架确定任务“太慢”时,它将推测地在不同节点上执行同一任务。 Once one of the two tasks finishes successfully, the other task is killed. 一旦两个任务之一成功完成,另一个任务就被杀死。

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