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https://issues.apache.org/jira/browse/SPARK-21270?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin closed SPARK-21270.
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Resolution: Won't Fix
While I absolutely would love to see this feature, I don't think this is
realistic to enforce, since there is no way to dynamically grow or shrink
memory used by the JVM heap at runtime. Sorry. I'm going to close this.
> Improvement for memory config.
> ------------------------------
>
> Key: SPARK-21270
> URL: https://issues.apache.org/jira/browse/SPARK-21270
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 2.1.1
> Reporter: jin xing
>
> 1. For executor memory, we have {{spark.executor.memory}} for heap size, and
> {{spark.memory.offHeap.size}} for off-heap size, and these 2 together is the
> total memory consumption for each executor process.
> From the user side, what they always care is the total memory consumption, no
> matter it is on-heap or off-heap. It seems that it is more friendly to have
> only one memory config for the user.
> Can we merge the two configs to be one, and hide the complexity within
> internal system?
> 2. {{spark.memory.offHeap.size}} is originally designed for
> {{MemoryManager}}, which is to manage off-heap memory explicitly allocated by
> Spark itself when creating its own buffers / pages or caching blocks, not to
> account for off-heap memory used by lower-level code or third-party
> libraries, for example Netty. But {{spark.memory.offHeap.size}} and
> {{spark.memory.offHeap.enable}} are more or less confusing. Sometimes user
> can ask -- "I've already set {{spark.memory.offHeap.enable}} to be false, but
> why Netty is reading remote blocks to off-heap?". Also I think we need to
> document more about
> {{spark.memory.offHeap.size}} and {{spark.memory.offHeap.enable}} on
> http://spark.apache.org/docs/latest/configuration.html
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