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https://issues.apache.org/jira/browse/MAPREDUCE-7148?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16645034#comment-16645034
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Jason Lowe commented on MAPREDUCE-7148:
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Unrecoverable works as long as the reader understands the "recovery" part is
referring to tasks and not the error on the filesystem being reported. Maybe
ClusterStorageCapacityExceededException? I'm terrible with names -- as long as
everyone's on the same page as to what it really means I'm OK with it. Or as
you suggest, a boolean predicate like isNodeLocal() can work too. The key is
having someone who implements a new FileSystem easily knowing when it's
appropriate to throw an exception of this type and when it's not.
> Fast fail jobs when exceeds dfs quota limitation
> ------------------------------------------------
>
> Key: MAPREDUCE-7148
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-7148
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: task
> Affects Versions: 2.7.0, 2.8.0, 2.9.0
> Environment: hadoop 2.7.3
> Reporter: Wang Yan
> Assignee: Wang Yan
> Priority: Major
> Attachments: MAPREDUCE-7148.001.patch, MAPREDUCE-7148.002.patch,
> MAPREDUCE-7148.003.patch, MAPREDUCE-7148.004.patch
>
>
> We are running hive jobs with a DFS quota limitation per job(3TB). If a job
> hits DFS quota limitation, the task that hit it will fail and there will be a
> few task reties before the job actually fails. The retry is not very helpful
> because the job will always fail anyway. In some worse cases, we have a job
> which has a single reduce task writing more than 3TB to HDFS over 20 hours,
> the reduce task exceeds the quota limitation and retries 4 times until the
> job fails in the end thus consuming a lot of unnecessary resource. This
> ticket aims at providing the feature to let a job fail fast when it writes
> too much data to the DFS and exceeds the DFS quota limitation. The fast fail
> feature is introduced in MAPREDUCE-7022 and MAPREDUCE-6489 .
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