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https://issues.apache.org/jira/browse/HBASE-13992?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14639471#comment-14639471
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Sean Busbey commented on HBASE-13992:
-------------------------------------

I agree that test handling around failures will be necessary for this to be 
robust and usable for downstream folks.

Steve, do you think we need those tests in place to land on master? Would you 
be fine with making those additions part of the gate for getting this 
backported to branch-1? The expectation is that backporting to branch-1 will 
mark when users end up interacting with this code. Similar to needing failure 
handling we'll definitely need to have user-facing docs before that happens, 
but those docs are part of the follow on work after this first jira.

I think right now the expectation is that master won't have a release before 
the end of the year and these changes in branch-1 would correspond to 1.3. 
Given that we're trying to get 1.2 out now, that would give us at least  3-4 
months for the follow on tickets.

> Integrate SparkOnHBase into HBase
> ---------------------------------
>
>                 Key: HBASE-13992
>                 URL: https://issues.apache.org/jira/browse/HBASE-13992
>             Project: HBase
>          Issue Type: New Feature
>          Components: spark
>            Reporter: Ted Malaska
>            Assignee: Ted Malaska
>             Fix For: 2.0.0
>
>         Attachments: HBASE-13992.5.patch, HBASE-13992.6.patch, 
> HBASE-13992.7.patch, HBASE-13992.8.patch, HBASE-13992.9.patch, 
> HBASE-13992.patch, HBASE-13992.patch.3, HBASE-13992.patch.4, 
> HBASE-13992.patch.5
>
>
> This Jira is to ask if SparkOnHBase can find a home in side HBase core.
> Here is the github: 
> https://github.com/cloudera-labs/SparkOnHBase
> I am the core author of this project and the license is Apache 2.0
> A blog explaining this project is here
> http://blog.cloudera.com/blog/2014/12/new-in-cloudera-labs-sparkonhbase/
> A spark Streaming example is here
> http://blog.cloudera.com/blog/2014/11/how-to-do-near-real-time-sessionization-with-spark-streaming-and-apache-hadoop/
> A real customer using this in produce is blogged here
> http://blog.cloudera.com/blog/2015/03/how-edmunds-com-used-spark-streaming-to-build-a-near-real-time-dashboard/
> Please debate and let me know what I can do to make this happen.



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