vanzin commented on a change in pull request #24072: [SPARK-27112] : Create a
resource ordering between threads to resolve the deadlocks encountered …
URL: https://github.com/apache/spark/pull/24072#discussion_r265779141
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File path:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
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@@ -258,15 +258,20 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, val rpcEnv: Rp
// Make fake resource offers on all executors
private def makeOffers() {
// Make sure no executor is killed while some task is launching on it
- val taskDescs = CoarseGrainedSchedulerBackend.this.synchronized {
- // Filter out executors under killing
- val activeExecutors = executorDataMap.filterKeys(executorIsAlive)
- val workOffers = activeExecutors.map {
- case (id, executorData) =>
- new WorkerOffer(id, executorData.executorHost,
executorData.freeCores,
- Some(executorData.executorAddress.hostPort))
- }.toIndexedSeq
- scheduler.resourceOffers(workOffers)
+ // SPARK-27112: We need to ensure that there is ordering of lock
acquisition
+ // between TaskSchedulerImpl and CoarseGrainedSchedulerBackend objects
in order to fix
+ // the deadlock issue exposed in SPARK-27112
+ val taskDescs = scheduler.synchronized {
Review comment:
Ok, I think that's fine. I checked and all modifications happen on the
endpoint thread, so reading the map from that thread without a lock should be
fine. The data being modified (`freeCores`) is also only used in the endpoint
thread, so that looks safe too.
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