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https://issues.apache.org/jira/browse/SPARK-3561?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14148010#comment-14148010
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Mayank Bansal commented on SPARK-3561:
--------------------------------------

HI Guys,

we at ebay are having some issues in cluster utilization while running 
spark-on-yarn with batch workloads of Hadoop. I think this would be nice to try 
out and see if we overcome this issue. We would be intrested in trying this out.

Thanks,
Mayank

> Native Hadoop/YARN integration for batch/ETL workloads
> ------------------------------------------------------
>
>                 Key: SPARK-3561
>                 URL: https://issues.apache.org/jira/browse/SPARK-3561
>             Project: Spark
>          Issue Type: New Feature
>          Components: Spark Core
>    Affects Versions: 1.1.0
>            Reporter: Oleg Zhurakousky
>              Labels: features
>             Fix For: 1.2.0
>
>         Attachments: SPARK-3561.pdf
>
>
> Currently Spark provides integration with external resource-managers such as 
> Apache Hadoop YARN, Mesos etc. Specifically in the context of YARN, the 
> current architecture of Spark-on-YARN can be enhanced to provide 
> significantly better utilization of cluster resources for large scale, batch 
> and/or ETL applications when run alongside other applications (Spark and 
> others) and services in YARN. 
> Proposal:
> The proposed approach would introduce a pluggable JobExecutionContext (trait) 
> - a gateway and a delegate to Hadoop execution environment - as a non-public 
> api (@DeveloperAPI) not exposed to end users of Spark.
> The trait will define 4 only operations:
> * hadoopFile
> * newAPIHadoopFile
> * broadcast
> * runJob
> Each method directly maps to the corresponding methods in current version of 
> SparkContext. JobExecutionContext implementation will be accessed by 
> SparkContext via master URL as 
> "execution-context:foo.bar.MyJobExecutionContext" with default implementation 
> containing the existing code from SparkContext, thus allowing current 
> (corresponding) methods of SparkContext to delegate to such implementation. 
> An integrator will now have an option to provide custom implementation of 
> DefaultExecutionContext by either implementing it from scratch or extending 
> form DefaultExecutionContext.
> Please see the attached design doc for more details.
> Pull Request will be posted shortly as well



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