hadoop 之 FAILED Too many fetch-failures 错误

  今天在执行job时发现如下错误：

11/08/12 15:19:33 INFO mapred.JobClient:  map 99% reduce 32%
11/08/12 15:20:59 INFO mapred.JobClient:  map 99% reduce 33%
11/08/12 15:21:10 INFO mapred.JobClient:  map 100% reduce 33%
11/08/12 15:21:34 INFO mapred.JobClient: Task Id : attempt_201108021504_30459_m_000368_0, Status : FAILED
Too many fetch-failures
11/08/12 15:22:35 WARN mapred.JobClient: Error reading task outputRead timed out
11/08/12 15:22:36 INFO mapred.JobClient:  map 100% reduce 34%
11/08/12 15:24:44 INFO mapred.JobClient: Task Id : attempt_201108021504_30459_m_000392_0, Status : FAILED
Too many fetch-failures
11/08/12 15:25:44 WARN mapred.JobClient: Error reading task outputRead timed out
11/08/12 15:25:45 INFO mapred.JobClient:  map 100% reduce 67%
11/08/12 15:25:56 INFO mapred.JobClient: Job complete: job_201108021504_30459
11/08/12 15:25:56 INFO mapred.JobClient: Counters: 26
11/08/12 15:25:56 INFO mapred.JobClient:   Job Counters
11/08/12 15:25:56 INFO mapred.JobClient:     Launched reduce tasks=303
11/08/12 15:25:56 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=8591016

经过查找， 原因解释如下： http://blog.csdn.net/liangliyin/article/details/6455713
        Reduce task启动后第一个阶段是shuffle，即向map端fetch数据。每次fetch都可能因为connect超时，read超时，checksum错误等原因而失败。Reduce task为每个map设置了一个计数器，用以记录fetch该map输出时失败的次数。当失败次数达到一定阈值时，会通知JobTracker fetch该map输出操作失败次数太多了，并打印如下log：
Failed to fetch map-output from attempt_201105261254_102769_m_001802_0 even after MAX_FETCH_RETRIES_PER_MAP retries... reporting to the JobTracker
其中阈值计算方式为：
max(MIN_FETCH_RETRIES_PER_MAP,
getClosestPowerOf2((this.maxBackoff * 1000 / BACKOFF_INIT) + 1));
默认情况下MIN_FETCH_RETRIES_PER_MAP=2 maxBackoff=300 BACKOFF_INIT=4000，因此默认阈值为6，可通过修改mapred.reduce.copy.backoff参数来调整。当达到阈值后，Reduce task通过umbilical协议告诉TaskTracker，TaskTracker在下一次heartbeat时，通知JobTracker。当JobTracker发现超过50%的Reduce汇报fetch某个map的输出多次失败后，JobTracker会failed掉该map并重新调度，打印如下log：
"Too many fetch-failures for output of task: attempt_201105261254_102769_m_001802_0 ... killing it"