[SPARK-39987][K8S] Support PEAK_JVM_(ON|OFF)HEAP_MEMORY executor rolling policy
#37418
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PEAK_JVM_(ON|OFF)HEAP_MEMORY executor rolling policy
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Could you review this when you have some time, @viirya ? |
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Thank you, @viirya ! Merged to master. |
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Jun 2, 2023
…lling policy (apache#1484) ### What changes were proposed in this pull request? This PR aims to support two new executor rolling policies. - `PEAK_JVM_ONHEAP_MEMORY` policy chooses an executor with the biggest peak JVM on-heap memory. - `PEAK_JVM_OFFHEAP_MEMORY` policy chooses an executor with the biggest peak JVM off-heap memory. ### Why are the changes needed? Although peak memory is a kind of historic value, these two new policies add a capability to maintain the memory usage of Spark jobs minimally as much as possible. ### Does this PR introduce _any_ user-facing change? Yes, but this is a new feature. ### How was this patch tested? Pass the CIs. Closes apache#37418 from dongjoon-hyun/SPARK-39987. Authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> (cherry picked from commit 3df7124) Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> (cherry picked from commit 84cd907) Signed-off-by: Dongjoon Hyun <dongjoon@apache.org> Co-authored-by: Dongjoon Hyun <dongjoon@apache.org>
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What changes were proposed in this pull request?
This PR aims to support two new executor rolling policies.
PEAK_JVM_ONHEAP_MEMORYpolicy chooses an executor with the biggest peak JVM on-heap memory.PEAK_JVM_OFFHEAP_MEMORYpolicy chooses an executor with the biggest peak JVM off-heap memory.Why are the changes needed?
Although peak memory is a kind of historic value, these two new policies add a capability to maintain the memory usage of Spark jobs minimally as much as possible.
Does this PR introduce any user-facing change?
Yes, but this is a new feature.
How was this patch tested?
Pass the CIs.