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https://issues.apache.org/jira/browse/MAHOUT-56?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12616527#action_12616527
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Deneche A. Hakim commented on MAHOUT-56:
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The whole point of the CDGA example is to show how to use Mahout to run a
Genetic Algorithm on a very large dataset, cause this is what Map-Reduce is
about : large and distributed data.
Now, it wont harm my program to be able to work with in-memory datasets, and
I'll be more than happy to implement (a) as soon as there is a "stable"
solution for (b) and (c).
I have one question about in-memory datasets : how to pass them to the mappers
? we can't use the job input if the dataset is in-memory ? so I assume it is
passed as a job parameter, is it ?
> Watchmaker Integration
> ----------------------
>
> Key: MAHOUT-56
> URL: https://issues.apache.org/jira/browse/MAHOUT-56
> Project: Mahout
> Issue Type: Task
> Components: Genetic Algorithms
> Reporter: Deneche A. Hakim
> Assignee: Grant Ingersoll
> Priority: Minor
> Fix For: 0.1
>
> Attachments: libs.zip, libs.zip, libs.zip, tsp-screenshot-1.jpg,
> watchmaker-tsp.patch, watchmaker-tsp.patch, watchmaker-tsp.patch,
> watchmaker-tsp.patch, watchmaker-tsp.patch, watchmaker-tsp.patch,
> watchmaker-tsp.patch, watchmaker-tsp.patch, watchmaker-tsp.patch,
> watchmaker-tsp.patch, watchmaker-tsp.patch, watchmaker-tsp.patch,
> watchmaker-tsp.patch
>
>
> The goal of this task is to allow watchmaker definded problems be solved in
> Mahout.
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