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From "Chris Douglas (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-6423) MapOutput Sampler
Date Fri, 21 Aug 2015 20:51:48 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-6423?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14707436#comment-14707436

Chris Douglas commented on MAPREDUCE-6423:

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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