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https://issues.apache.org/jira/browse/HADOOP-5985?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12717401#action_12717401
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Aaron Kimball commented on HADOOP-5985:
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I was under the impression that if a map task died before delivering output to
all of the reducers, then after the map task is re-executed elsewhere, all
reducers roll back and re-pull from the newer version of the mapper. I could be
mistaken though?
Because if that's the case, then we just need to run another round of
speculative execution during the final shufflings, even if the map tasks
themselves were marked as "complete," and modify the reducers to try to pull
from a list of eligible mappers instead of just a single node.
> A single slow (but not dead) map TaskTracker impedes MapReduce progress
> -----------------------------------------------------------------------
>
> Key: HADOOP-5985
> URL: https://issues.apache.org/jira/browse/HADOOP-5985
> Project: Hadoop Core
> Issue Type: Bug
> Affects Versions: 0.18.3
> Reporter: Aaron Kimball
>
> We see cases where there may be a large number of mapper nodes running many
> tasks (e.g., a thousand). The reducers will pull 980 of the map task
> intermediate files down, but will be unable to retrieve the final
> intermediate shards from the last node. The TaskTracker on that node returns
> data to reducers either slowly or not at all, but its heartbeat messages make
> it back to the JobTracker -- so the JobTracker doesn't mark the tasks as
> failed. Manually stopping the offending TaskTracker works to migrate the
> tasks to other nodes, where the shuffling process finishes very quickly. Left
> on its own, it can take hours to unjam itself otherwise.
> We need a mechanism for reducers to provide feedback to the JobTracker that
> one of the mapper nodes should be regarded as lost.
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