guixiaowen opened a new pull request, #46496:
URL: https://github.com/apache/spark/pull/46496
…ing is enabled in the “ Stage Level Scheduling Overview”
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### What changes were proposed in this pull request?
“ Stage Level Scheduling Overview ” in running-on-yarn and
running-on-kubernetes
The description of dynamic partitioning is inconsistent with the code
implementation verification.
In running-on-yarn
'
When dynamic allocation is disabled: It allows users to specify different
task resource requirements at the stage level and will use the same executors
requested at startup.
'
But the implementation is：
Class：ResourceProfileManager
Fuc：isSupported
private[spark] def isSupported(rp: ResourceProfile): Boolean = {
assert(master != null)
if (rp.isInstanceOf[TaskResourceProfile] && !dynamicEnabled) {
if ((notRunningUnitTests || testExceptionThrown) &&
!(isStandaloneOrLocalCluster || isYarn || isK8s))
{ throw new SparkException("TaskResourceProfiles are only supported for
Standalone, " + "Yarn and Kubernetes cluster for now when dynamic allocation is
disabled.") }
}
The judgment of this code is that it does not support TaskResourceProfile in
Yarn and k8s when dynamic partitioning is closed.
The description in the document does not match, so the document needs to be
modified.
### Why are the changes needed?
This description is a bit misleading for users.
### Does this PR introduce _any_ user-facing change?
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