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How does fault tolerance work in mapreduce?


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    In a mapreduce job the master pings each worker periodically. In case a worker does not respond to that system then the system is marked as failed. Even completed tasks are rescheduled because the output was stored in a in a local disk of a worker which failed. Hence mapreduce is able to handle large-scale failures easily by simply restarting a task. The master node always saves itself at checkpoints and in case of any failure it simply restarts from that checkpoint.

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