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Posted to hdfs-dev@hadoop.apache.org by "Ravi Phulari (JIRA)" <ji...@apache.org> on 2009/07/10 20:21:14 UTC
[jira] Resolved: (HDFS-486) error : too many fetch failures
[ https://issues.apache.org/jira/browse/HDFS-486?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Ravi Phulari resolved HDFS-486.
-------------------------------
Resolution: Invalid
Closing as invalid because this error is not due to HDFS.
The fetch is over HTTP, so it has nothing to do with HDFS . and this could be anything from network congestion to a bad disk. The issue is invalid, since the framework- failing to obtain the map output- reexecuted the map and completed the job successfully.
If you have any issues with Map Reduce please write email to mapreduce-user at hadoop.apache.org
> 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
> Original Estimate: 48h
> Remaining Estimate: 48h
>
> 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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