[jira] [Commented] (CRUNCH-296) Support new distributed execution engines (e.g., Spark)

["Gabriel Reid (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/CRUNCH-296?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13825429#comment-13825429 ] 

Gabriel Reid commented on CRUNCH-296:
-------------------------------------

Looks and sounds very interesting -- I'm definitely looking forward to taking a closer look at this and playing around with it.

I think it's worth considering where we want to go with this (and/or where we don't want to go with it), as it _is_ straying away from the tagline of "Simple and Efficient MapReduce Pipelines". That being said, as long as this doesn't get in the way of working with MapReduce (assuming that's what the intention of Crunch will remain), then I'm all for it.



> Support new distributed execution engines (e.g., Spark)
> -------------------------------------------------------
>
>                 Key: CRUNCH-296
>                 URL: https://issues.apache.org/jira/browse/CRUNCH-296
>             Project: Crunch
>          Issue Type: Improvement
>          Components: Core
>            Reporter: Josh Wills
>            Assignee: Josh Wills
>         Attachments: CRUNCH-296.patch
>
>
> I've been working on this off-and-on for awhile, but it's currently in a state where I feel like it's worth sharing: I came up with an implementation of the Crunch APIs that runs on top of Apache Spark instead of MapReduce.
> My goal for this is pretty simple; I want to be able to change any instances of "new MRPipeline(...)" to "new SparkPipeline(...)", not change anything else at all, and have my pipelines run on Spark instead of as a series of MR jobs. Turns out that we can pretty much do exactly that. Not everything works yet, but lots of things do-- joins and cogroups work, the PageRank and TfIdf integration tests work. Some things that do not work that I'm aware of: in-memory joins and some of the more complex file output handling rules, but I believe that these things are fixable. Some thing that might work or might not: HBase inputs and outputs on top of Spark.
> This is just an idea I had, and I would understand if other people don't want to work on this or don't think it's the right direction for the project. My minimal request would be to include the refactoring of the core APIs necessary to support plugging in new execution frameworks so I can keep working on this stuff.



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