[jira] [Commented] (SPARK-12133) Support dynamic allocation in Spark Streaming

2016-04-13 Thread WilliamZhu (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-12133?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15240453#comment-15240453
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WilliamZhu commented on SPARK-12133:


Here have a new Design:  http://www.jianshu.com/p/ae7fdd4746f6 

> Support dynamic allocation in Spark Streaming
> -
>
> Key: SPARK-12133
> URL: https://issues.apache.org/jira/browse/SPARK-12133
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core, Streaming
>Reporter: Andrew Or
>Assignee: Tathagata Das
> Attachments: dynamic-allocation-streaming-design.pdf
>
>
> Dynamic allocation is a feature that allows your cluster resources to scale 
> up and down based on the workload. Currently it doesn't work well with Spark 
> streaming because of several reasons:
> (1) Your executors may never be idle since they run something every N seconds
> (2) You should have at least one receiver running always
> (3) The existing heuristics don't take into account length of batch queue
> ...
> The goal of this JIRA is to provide better support for using dynamic 
> allocation in streaming. A design doc will be posted shortly.



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[jira] [Commented] (SPARK-12133) Support dynamic allocation in Spark Streaming

2016-04-04 Thread Apache Spark (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-12133?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15225057#comment-15225057
 ] 

Apache Spark commented on SPARK-12133:
--

User 'tdas' has created a pull request for this issue:
https://github.com/apache/spark/pull/12154

> Support dynamic allocation in Spark Streaming
> -
>
> Key: SPARK-12133
> URL: https://issues.apache.org/jira/browse/SPARK-12133
> Project: Spark
>  Issue Type: Bug
>  Components: Spark Core, Streaming
>Reporter: Andrew Or
>Assignee: Tathagata Das
> Attachments: dynamic-allocation-streaming-design.pdf
>
>
> Dynamic allocation is a feature that allows your cluster resources to scale 
> up and down based on the workload. Currently it doesn't work well with Spark 
> streaming because of several reasons:
> (1) Your executors may never be idle since they run something every N seconds
> (2) You should have at least one receiver running always
> (3) The existing heuristics don't take into account length of batch queue
> ...
> The goal of this JIRA is to provide better support for using dynamic 
> allocation in streaming. A design doc will be posted shortly.



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