vinodkc commented on code in PR #41746:
URL: https://github.com/apache/spark/pull/41746#discussion_r1250119121
##########
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala:
##########
@@ -311,13 +311,24 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, val rpcEnv: Rp
decommissionExecutors(Array((executorId, v._1)), v._2, v._3)
unknownExecutorsPendingDecommission.invalidate(executorId)
})
+ // propagate current log level to new executor only if flag is true
+ if (conf.get(EXECUTOR_ALLOW_SYNC_LOG_LEVEL)) {
+ data.executorEndpoint.send(RefreshExecutor(Map("logLevel" ->
Utils.getLogLevel)))
+ }
Review Comment:
@mridulm , Done, when executors are initialized, applied the log level of
the driver in the executor.
@grundprinzip , If the user turns on the "sync", it will override the
executor log configuration only if `spark.log.level` is applied on
`SparkContext` or `sc.setLogLevel()` explicitly called with a different log
level than default log level configured on log4j2 , hence there won't be a side
effect in that scenario.
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