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https://issues.apache.org/jira/browse/HADOOP-153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12610897#action_12610897
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Sharad Agarwal commented on HADOOP-153:
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Had an offline discussion with Eric and Devaraj, and we came up with following:
- Let this issue handle the case of crashes and hangups. For the case of 
catching the exception for Java tasks, filed another Jira -> Hadoop-3700
- Design gets impacted based on the assumption of how frequent the failures 
would be. At this point of time, design for INFREQUENT failures. This would 
simplify the design. Also, bad records can be maintained by the Jobtracker (as 
pointed out by Enis), as no of bad records are expected to be quite low.
- Failing Fast the bad jobs is very crucial to avoid wasting Grid resources. 
Thresholds should be define in such a way that we identify bad jobs early 
enough, say maximum of 10% of the maps can fail. Also, we need to make sure 
that we execute failed task VERY FAST.
- Apart from bad data, Task crashes could be due to bad user code (like Out of 
memory) or bad nodes. To isolate these cases, on failure, reexecute on another 
node as now.  If it fails AGAIN, then reexecute a third time, this time in the 
special mode where we report every record completion to the Task tracker.
- For the case of Streaming, streaming would have to write the processed record 
count to the stderr as a framework counter, to take advantage of this feature.






> skip records that throw exceptions
> ----------------------------------
>
>                 Key: HADOOP-153
>                 URL: https://issues.apache.org/jira/browse/HADOOP-153
>             Project: Hadoop Core
>          Issue Type: New Feature
>          Components: mapred
>    Affects Versions: 0.2.0
>            Reporter: Doug Cutting
>            Assignee: Sharad Agarwal
>         Attachments: skipRecords_wip1.patch
>
>
> MapReduce should skip records that throw exceptions.
> If the exception is thrown under RecordReader.next() then RecordReader 
> implementations should automatically skip to the start of a subsequent record.
> Exceptions in map and reduce implementations can simply be logged, unless 
> they happen under RecordWriter.write().  Cancelling partial output could be 
> hard.  So such output errors will still result in task failure.
> This behaviour should be optional, but enabled by default.  A count of errors 
> per task and job should be maintained and displayed in the web ui.  Perhaps 
> if some percentage of records (>50%?) result in exceptions then the task 
> should fail.  This would stop jobs early that are misconfigured or have buggy 
> code.
> Thoughts?

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