[SPARK-39987][K8S] Support PEAK_JVM_(ON|OFF)HEAP_MEMORY executor rolling policy
#37418
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
dongjoon-hyun
changed the title
PEAK_JVM_(ON|OFF)HEAP_MEMORY executor rolling policy
Member
Author
|
Could you review this when you have some time, @viirya ? |
Member
Author
|
Thank you, @viirya ! Merged to master. |
sunchao
pushed a commit
to sunchao/spark
that referenced
this pull request
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>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
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.