[jira] [Commented] (HAMA-983) Hama runner for DataFlow

["Edward J. Yoon (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HAMA-983?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16009911#comment-16009911 ] 

Edward J. Yoon commented on HAMA-983:
-------------------------------------

{code}
# create a new branch inside your directory 'current'
git checkout -b HAMA-983
# ... do some changes to the files ...
# store changes in the branch
git push origin HAMA-983
# commit changes to the branch
git commit -a -m '[HAMA-983] Hama runner for DataFlow'
Then go to your GitHub HAMA page and do a Pull Request. 
{code}

Hi JongYoon, you can create new branch like above.

> Hama runner for DataFlow
> ------------------------
>
>                 Key: HAMA-983
>                 URL: https://issues.apache.org/jira/browse/HAMA-983
>             Project: Hama
>          Issue Type: Bug
>            Reporter: Edward J. Yoon
>              Labels: gsoc2016
>
> As you already know, Apache Beam provides unified programming model for both batch and streaming inputs.
> The APIs are generally associated with data filtering and transforming. So we'll need to implement some data processing runner like https://github.com/dapurv5/MapReduce-BSP-Adapter/blob/master/src/main/java/org/apache/hama/mapreduce/examples/WordCount.java
> Also, implementing similarity join can be funny. According to http://www.ruizhang.info/publications/TPDS2015-Heads_Join.pdf, Apache Hama is clearly winner among Apache Hadoop and Apache Spark.
> Since it consists of transformation, aggregation, and partition computations, I think it's possible to implement using Apache Beam APIs.



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