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https://issues.apache.org/jira/browse/SPARK-3561?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14137378#comment-14137378
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Oleg Zhurakousky commented on SPARK-3561:
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Patrick, sorry as I feel like I missed the core emphasis of what we are trying
to accomplish with this.
Our main goal is to expose Spark to native Hadoop features (i.e., stateless
YARN shuffle, Tez etc.), thus increasing the existing capabilities of Spark
such as interactive, in-memory and streaming to batch and ETL in a shared,
multi-tenant environments, thus benefiting Spark community considerably by
allowing Spark to be applied for all use-cases and capabilties on and in Hadoop.
> 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: 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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