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From "Amit Sela (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (BEAM-198) Spark runner batch translator to work with Datasets instead of RDDs
Date Mon, 25 Jul 2016 17:32:20 GMT

    [ https://issues.apache.org/jira/browse/BEAM-198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15392346#comment-15392346
] 

Amit Sela commented on BEAM-198:
--------------------------------

See https://github.com/apache/incubator-beam/pull/495
Happy to get reviews/comments/testing/benchmarks. And of course you're most welcomed to help
with next steps - streaming "a la Beam" with Structured Streaming. 

We can chat about this in Beam's Slack channel. 

> Spark runner batch translator to work with Datasets instead of RDDs
> -------------------------------------------------------------------
>
>                 Key: BEAM-198
>                 URL: https://issues.apache.org/jira/browse/BEAM-198
>             Project: Beam
>          Issue Type: New Feature
>          Components: runner-spark
>            Reporter: Amit Sela
>            Assignee: Amit Sela
>
> Currently, the Spark runner translates batch pipelines into RDD code, meaning it doesn't
benefit from the optimizations DataFrames (which isn't type-safe) enjoys.
> With Datasets, batch pipelines will benefit the optimizations, adding to that that Datasets
are type-safe and encoder-based they seem like a much better fit for the Beam model.
> Looking ahead, Datasets is a good choice since it's the basis for the future of Spark
streaming as well  (Structured Streaming) so this will hopefully lay a solid foundation for
a native integration between Spark 2.0 and Beam.



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