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https://issues.apache.org/jira/browse/MAPREDUCE-6423?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14707436#comment-14707436
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Chris Douglas commented on MAPREDUCE-6423:
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Thanks for taking a look at this. That the sampler only works on input data was
always a weakness for jobs requiring their output be totally ordered.
Could you generate a patch? The contribution wiki is
[here|http://wiki.apache.org/hadoop/HowToContribute].
It might be easier for others to use if the Mapper was integrated with the
InputSampler, but a separate tool is still an improvement.
> MapOutput Sampler
> -----------------
>
> Key: MAPREDUCE-6423
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6423
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Reporter: Ram Manohar Bheemana
> Assignee: Ram Manohar Bheemana
> Priority: Minor
> Attachments: MapOutputSampler.java
>
>
> Need a sampler based on the MapOutput Keys. Current InputSampler
> implementation has a major drawback which is input and output of a mapper
> should be same, generally this isn't the case.
> approach:
> 1. Create a Sampler which samples the data based on the input.
> 2. Run a small map reduce in uber task mode using the original job mapper and
> identity reducer to generate required MapOutputSample keys
> 3. Optionally, we can input the input file to be sample. For example inputs
> files A, B; we should be able to specify to use only file A for sampling.
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