You are viewing a plain text version of this content. The canonical link for it is here.
Posted to mapreduce-issues@hadoop.apache.org by "YunFan Zhou (JIRA)" <ji...@apache.org> on 2017/08/18 09:40:02 UTC
[jira] [Commented] (MAPREDUCE-6485) MR job hanged forever because
all resources are taken up by reducers and the last map attempt never get
resource to run
[ https://issues.apache.org/jira/browse/MAPREDUCE-6485?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16131973#comment-16131973 ]
YunFan Zhou commented on MAPREDUCE-6485:
----------------------------------------
[~varun_impala_149e] [~rohithsharma] Hi, Rohith Sharma K S,Karthik Kambatla.
Could you please help me with my problems?
The job I ran was hanged, but it was different from the scenario you encountered. What I've observed is that there are 15564 maps in total, and only one map is Pending. All reduce is pending because the map is not finished. But the resources for clustering and queues are very idle. The job was pending about 12 hours until I used the MR Cli to actively fail the map, and the job was finished normally.
To view AM's log, the following info has been reported:
{noformat}
2017-08-17 07:58:44,401 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Ramping down all scheduled reduces:0
2017-08-17 07:58:44,401 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Going to preempt 1 due to lack of space for maps
2017-08-17 07:58:44,401 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Recalculating schedule, headroom=<memory:814012, vCores:-1>
2017-08-17 07:58:44,401 INFO [RMCommunicator Allocator] org.apache.hadoop.mapreduce.v2.app.rm.RMContainerAllocator: Reduce slow start threshold not met. completedMapsForReduceSlowstart 15564
{noformat}
> MR job hanged forever because all resources are taken up by reducers and the last map attempt never get resource to run
> -----------------------------------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-6485
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6485
> Project: Hadoop Map/Reduce
> Issue Type: Bug
> Components: applicationmaster
> Affects Versions: 2.4.1, 2.6.0, 2.7.1, 3.0.0-alpha1
> Reporter: Bob.zhao
> Assignee: Xianyin Xin
> Priority: Critical
> Fix For: 2.8.0, 3.0.0-alpha1
>
> Attachments: MAPREDUCE-6485.001.patch, MAPREDUCE-6485.004.patch, MAPREDUCE-6485.005.patch, MAPREDUCE-6485.006.patch, MAPREDUCE-6845.002.patch, MAPREDUCE-6845.003.patch
>
>
> The scenarios is like this:
> With configuring mapreduce.job.reduce.slowstart.completedmaps=0.8, reduces will take resource and start to run when all the map have not finished.
> But It could happened that when all the resources are taken up by running reduces, there is still one map not finished.
> Under this condition , the last map have two task attempts .
> As for the first attempt was killed due to timeout(mapreduce.task.timeout), and its state transitioned from RUNNING to FAIL_CONTAINER_CLEANUP then to FAILED, but failed map attempt would not be restarted for there is still one speculate map attempt in progressing.
> As for the second attempt which was started due to having enable map task speculative is pending at UNASSINGED state because of no resource available. But the second map attempt request have lower priority than reduces, so preemption would not happened.
> As a result all reduces would not finished because of there is one map left. and the last map hanged there because of no resource available. so, the job would never finish.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: mapreduce-issues-unsubscribe@hadoop.apache.org
For additional commands, e-mail: mapreduce-issues-help@hadoop.apache.org