You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/09/12 03:56:16 UTC
[GitHub] [spark] warrenzhu25 commented on a diff in pull request #37733: [SPARK-40267][DOC] Add description for ExecutorAllocationManager metrics
warrenzhu25 commented on code in PR #37733:
URL: https://github.com/apache/spark/pull/37733#discussion_r967965938
##########
docs/monitoring.md:
##########
@@ -1207,12 +1207,12 @@ This is the component with the largest amount of instrumented metrics
- namespace=ExecutorAllocationManager
- **note:** these metrics are only emitted when using dynamic allocation. Conditional to a configuration
parameter `spark.dynamicAllocation.enabled` (default is false)
- - executors.numberExecutorsToAdd
- - executors.numberExecutorsPendingToRemove
- - executors.numberAllExecutors
- - executors.numberTargetExecutors
- - executors.numberMaxNeededExecutors
- - executors.numberDecommissioningExecutors
+ - executors.numberExecutorsToAdd: Number of executors to add in the next round sync with cluster manager
+ - executors.numberExecutorsPendingToRemove: Number of executors to remove in the next round sync with cluster manager
+ - executors.numberAllExecutors: Number of all running executors including normal and decommissioning
+ - executors.numberTargetExecutors: Desired number of executors totally needed from cluster manager
+ - executors.numberMaxNeededExecutors: Maximum number of executors needed under the current load to satisfy all running and pending tasks, rounded up.
+ - executors.numberDecommissioningExecutors: Number of executors are decommissioning
Review Comment:
Yes, most metrics are self-explanation, but these metrics are not. Putting comments just after metrics name will be easier for users to understand. If you think there's better place, I'm happy to move it around.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org