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From "vijayan.B (JIRA)" <j...@apache.org>
Subject [jira] Created: (HDFS-486) error : too many fetch failures
Date Fri, 10 Jul 2009 10:13:14 GMT
error : too many fetch failures
-------------------------------

                 Key: HDFS-486
                 URL: https://issues.apache.org/jira/browse/HDFS-486
             Project: Hadoop HDFS
          Issue Type: Bug
         Environment: operating system : fedora-8
virtual environment : using xen
hadoop-0.18.3
            Reporter: vijayan.B


i configured the hadoop cluster environment with one physical mahine as data node and 7(2physical
and 5 virtual machines) as namenode
when i submitted the sort job(from hadoop-core-example)
it finished with following error, can you explain why this is happening and how to solve this?


output from terminal ************************************************************

[root@hadoop1 hadoop-0.18.3]# bin/hadoop jar hadoop-0.18.3-examples.jar sort input13 output1
Running on 7 nodes to sort from hdfs://hadoop1:8022/user/root/input13 into hdfs://hadoop1:8022/user/root/output1
with 12 reduces.
Job started: Fri Jul 10 14:00:19 IST 2009
09/07/10 14:00:19 INFO mapred.FileInputFormat: Total input paths to process : 1
09/07/10 14:00:19 INFO mapred.FileInputFormat: Total input paths to process : 1
09/07/10 14:00:19 INFO mapred.JobClient: Running job: job_200907101344_0002
09/07/10 14:00:20 INFO mapred.JobClient:  map 0% reduce 0%
09/07/10 14:00:24 INFO mapred.JobClient:  map 6% reduce 0%
09/07/10 14:00:25 INFO mapred.JobClient:  map 12% reduce 0%
09/07/10 14:00:28 INFO mapred.JobClient:  map 31% reduce 0%
09/07/10 14:00:29 INFO mapred.JobClient:  map 50% reduce 0%
09/07/10 14:00:33 INFO mapred.JobClient:  map 66% reduce 0%
09/07/10 14:00:34 INFO mapred.JobClient:  map 72% reduce 0%
09/07/10 14:00:35 INFO mapred.JobClient:  map 75% reduce 0%
09/07/10 14:00:37 INFO mapred.JobClient:  map 75% reduce 1%
09/07/10 14:00:38 INFO mapred.JobClient:  map 78% reduce 5%
09/07/10 14:00:39 INFO mapred.JobClient:  map 89% reduce 10%
09/07/10 14:00:40 INFO mapred.JobClient:  map 89% reduce 11%
09/07/10 14:00:41 INFO mapred.JobClient:  map 90% reduce 11%
09/07/10 14:00:42 INFO mapred.JobClient:  map 99% reduce 14%
09/07/10 14:00:43 INFO mapred.JobClient:  map 99% reduce 16%
09/07/10 14:00:44 INFO mapred.JobClient:  map 99% reduce 18%
09/07/10 14:00:45 INFO mapred.JobClient:  map 99% reduce 19%
09/07/10 14:00:47 INFO mapred.JobClient:  map 99% reduce 22%
09/07/10 14:00:48 INFO mapred.JobClient:  map 100% reduce 22%
09/07/10 14:00:50 INFO mapred.JobClient:  map 100% reduce 24%
09/07/10 14:00:52 INFO mapred.JobClient:  map 100% reduce 25%
09/07/10 14:00:53 INFO mapred.JobClient:  map 100% reduce 26%
09/07/10 14:00:54 INFO mapred.JobClient:  map 100% reduce 27%
09/07/10 14:00:58 INFO mapred.JobClient:  map 100% reduce 33%
09/07/10 14:01:00 INFO mapred.JobClient:  map 100% reduce 34%
09/07/10 14:01:03 INFO mapred.JobClient:  map 100% reduce 39%
09/07/10 14:03:29 INFO mapred.JobClient:  map 100% reduce 40%
09/07/10 14:03:42 INFO mapred.JobClient:  map 100% reduce 41%
09/07/10 14:03:50 INFO mapred.JobClient:  map 100% reduce 47%
09/07/10 14:03:51 INFO mapred.JobClient:  map 100% reduce 50%
09/07/10 14:03:52 INFO mapred.JobClient:  map 100% reduce 56%
09/07/10 14:03:57 INFO mapred.JobClient:  map 100% reduce 57%
09/07/10 14:04:00 INFO mapred.JobClient:  map 100% reduce 58%
09/07/10 14:04:05 INFO mapred.JobClient:  map 100% reduce 59%
09/07/10 14:04:07 INFO mapred.JobClient:  map 100% reduce 60%
09/07/10 14:04:09 INFO mapred.JobClient:  map 100% reduce 66%
09/07/10 14:04:10 INFO mapred.JobClient:  map 100% reduce 67%
09/07/10 14:04:12 INFO mapred.JobClient:  map 100% reduce 68%
09/07/10 14:04:13 INFO mapred.JobClient:  map 100% reduce 69%
09/07/10 14:04:14 INFO mapred.JobClient:  map 100% reduce 70%
09/07/10 14:04:20 INFO mapred.JobClient:  map 100% reduce 79%
09/07/10 14:04:21 INFO mapred.JobClient:  map 100% reduce 80%
09/07/10 14:04:22 INFO mapred.JobClient:  map 100% reduce 81%
09/07/10 14:04:23 INFO mapred.JobClient:  map 100% reduce 82%
09/07/10 14:04:33 INFO mapred.JobClient:  map 100% reduce 87%
09/07/10 14:04:42 INFO mapred.JobClient: Task Id : attempt_200907101344_0002_m_000013_0, Status
: FAILED
Too many fetch-failures
09/07/10 14:04:44 INFO mapred.JobClient:  map 93% reduce 87%
09/07/10 14:04:50 INFO mapred.JobClient:  map 100% reduce 87%
09/07/10 14:05:06 INFO mapred.JobClient:  map 100% reduce 93%
09/07/10 14:05:36 INFO mapred.JobClient:  map 100% reduce 94%
09/07/10 14:06:17 INFO mapred.JobClient: Job complete: job_200907101344_0002
09/07/10 14:06:17 INFO mapred.JobClient: Counters: 17
09/07/10 14:06:17 INFO mapred.JobClient:   File Systems
09/07/10 14:06:17 INFO mapred.JobClient:     HDFS bytes read=1077612760
09/07/10 14:06:17 INFO mapred.JobClient:     HDFS bytes written=1077285377
09/07/10 14:06:17 INFO mapred.JobClient:     Local bytes read=1083539214
09/07/10 14:06:17 INFO mapred.JobClient:     Local bytes written=2167083496
09/07/10 14:06:17 INFO mapred.JobClient:   Job Counters 
09/07/10 14:06:17 INFO mapred.JobClient:     Launched reduce tasks=18
09/07/10 14:06:17 INFO mapred.JobClient:     Rack-local map tasks=2
09/07/10 14:06:17 INFO mapred.JobClient:     Launched map tasks=18
09/07/10 14:06:17 INFO mapred.JobClient:     Data-local map tasks=15
09/07/10 14:06:17 INFO mapred.JobClient:   Map-Reduce Framework
09/07/10 14:06:17 INFO mapred.JobClient:     Reduce input groups=102341
09/07/10 14:06:17 INFO mapred.JobClient:     Combine output records=0
09/07/10 14:06:17 INFO mapred.JobClient:     Map input records=102341
09/07/10 14:06:17 INFO mapred.JobClient:     Reduce output records=102341
09/07/10 14:06:17 INFO mapred.JobClient:     Map output bytes=1074564177
09/07/10 14:06:17 INFO mapred.JobClient:     Map input bytes=1077284885
09/07/10 14:06:17 INFO mapred.JobClient:     Combine input records=0
09/07/10 14:06:17 INFO mapred.JobClient:     Map output records=102341
09/07/10 14:06:17 INFO mapred.JobClient:     Reduce input records=102341
Job ended: Fri Jul 10 14:06:17 IST 2009
The job took 357 seconds.



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