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https://issues.apache.org/jira/browse/HAMA-983?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15451100#comment-15451100
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Edward J. Yoon commented on HAMA-983:
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Hi, I didn't look at dataflow (apache beam) closely, but:
>> Do you mean that each superstep can be executed in data pipeline as a
>> pcollection?
I guess yes, or single job can be executed as the case may be.
If you're interested in working on this, you can refer
https://github.com/dataArtisans/flink-dataflow/blob/master/runner/src/main/java/com/dataartisans/flink/dataflow/FlinkPipelineRunner.java
And, before we do this, HAMA-940 and data processing BSP maybe the first I
guess. Please feel free to drop your opinion and contribute the patches. :-)
If you have any questions, let me know.
> 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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