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https://issues.apache.org/jira/browse/HAMA-983?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15454239#comment-15454239
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Edward J. Yoon commented on HAMA-983:
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Just FYI, Apache Beam's basic example is wordcount. I guess, the batch mode can
be similar with org.apache.hama.examples.PiEstimator: (n - 1) tasks parses and
counts the words and 1 task aggregates the word counts and emits the final
result. The streaming mode is not sure, so you'll need to check how it handles
io.
> 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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