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https://issues.apache.org/jira/browse/SPARK-10000?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14903995#comment-14903995
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Bowen Zhang commented on SPARK-10000:
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[~rxin], I am very interested in this new story. I am trying to understand the
story here. In addition to consolidate these two parts of memory into one
memory, are there other tricky things that can pose a challenge to this story
or other use case considerations that should be taken into account for this
story?
> Consolidate cache memory management and execution memory management
> -------------------------------------------------------------------
>
> Key: SPARK-10000
> URL: https://issues.apache.org/jira/browse/SPARK-10000
> Project: Spark
> Issue Type: Story
> Components: Block Manager, Spark Core
> Reporter: Reynold Xin
>
> As a Spark user, I want Spark to manage the memory more intelligently so I do
> not need to worry about how to statically partition the execution (shuffle)
> memory fraction and cache memory fraction.
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