[SPARK-27112][CORE] : Create a resource ordering between threads to r…

…esolve the deadlocks encountered when trying to kill executors either due to dynamic allocation or blacklisting

Closes apache#24072 from pgandhi999/SPARK-27112-2.

Authored-by: pgandhi <pgandhiverizonmedia.com>
Signed-off-by: Imran Rashid <irashidcloudera.com>

## What changes were proposed in this pull request?

There are two deadlocks as a result of the interplay between three different threads:

**task-result-getter thread**

**spark-dynamic-executor-allocation thread**

**dispatcher-event-loop thread(makeOffers())**

The fix ensures ordering synchronization constraint by acquiring lock on `TaskSchedulerImpl` before acquiring lock on `CoarseGrainedSchedulerBackend` in `makeOffers()` as well as killExecutors() method. This ensures resource ordering between the threads and thus, fixes the deadlocks.

## How was this patch tested?

Manual Tests

Closes apache#24134 from pgandhi999/branch-2.4-SPARK-27112.

Authored-by: pgandhi <pgandhi@verizonmedia.com>
Signed-off-by: Imran Rashid <irashid@cloudera.com>

core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala

@@ -237,7 +237,7 @@ 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 {
+      val taskDescs = withLock {
         // Filter out executors under killing
         val activeExecutors = executorDataMap.filterKeys(executorIsAlive)
         val workOffers = activeExecutors.map {
@@ -263,7 +263,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
     // Make fake resource offers on just one executor
     private def makeOffers(executorId: String) {
       // Make sure no executor is killed while some task is launching on it
-      val taskDescs = CoarseGrainedSchedulerBackend.this.synchronized {
+      val taskDescs = withLock {
         // Filter out executors under killing
         if (executorIsAlive(executorId)) {
           val executorData = executorDataMap(executorId)
@@ -607,7 +607,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
       force: Boolean): Seq[String] = {
     logInfo(s"Requesting to kill executor(s) ${executorIds.mkString(", ")}")
 
-    val response = synchronized {
+    val response = withLock {
       val (knownExecutors, unknownExecutors) = executorIds.partition(executorDataMap.contains)
       unknownExecutors.foreach { id =>
         logWarning(s"Executor to kill $id does not exist!")
@@ -685,6 +685,13 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
   }
 
   protected def fetchHadoopDelegationTokens(): Option[Array[Byte]] = { None }
+
+  // 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
+  private def withLock[T](fn: => T): T = scheduler.synchronized {
+    CoarseGrainedSchedulerBackend.this.synchronized { fn }
+  }
 }
 
 private[spark] object CoarseGrainedSchedulerBackend {