Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/16650#discussion_r97877918
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
---
@@ -148,6 +153,12 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, val rpcEnv: Rp
if (executorDataMap.contains(executorId)) {
executorRef.send(RegisterExecutorFailed("Duplicate executor ID:
" + executorId))
context.reply(true)
+ } else if (scheduler.nodeBlacklist != null &&
+ scheduler.nodeBlacklist.contains(executorId)) {
+ // Handle a race where the cluster manager finishes creating an
executor, just after
+ // the executor is blacklisted and just before it is possibly
killed.
+ executorRef.send(RegisterExecutorFailed("Executor is
blacklisted: " + executorId))
+ context.reply(true)
--- End diff --
can you change the comment to
If the cluster manager gives us an executor on a blacklisted node (because
it already started allocating those resources before we informed it of our
blacklist, or if it ignored our blacklist), then we reject that executor
immediately.
I'd also add a `logInfo` here about rejecting the executor b/c its on a
blacklisted node.
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