abellina commented on a change in pull request #24035: [SPARK-27112] : Spark
Scheduler encounters two independent Deadlocks …
URL: https://github.com/apache/spark/pull/24035#discussion_r264700561
##########
File path:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
##########
@@ -622,67 +633,107 @@ class CoarseGrainedSchedulerBackend(scheduler:
TaskSchedulerImpl, val rpcEnv: Rp
* @param countFailures if there are tasks running on the executors when
they are killed, whether
* those failures be counted to task failure limits?
* @param force whether to force kill busy executors, default false
+ * @param blacklistingOnTaskCompletion whether the executors are being
killed due to
+ * blacklisting triggered by the task
completion event
* @return the ids of the executors acknowledged by the cluster manager to
be removed.
*/
final override def killExecutors(
executorIds: Seq[String],
adjustTargetNumExecutors: Boolean,
countFailures: Boolean,
- force: Boolean): Seq[String] = {
+ force: Boolean,
+ blacklistingOnTaskCompletion: Boolean): Seq[String] = {
logInfo(s"Requesting to kill executor(s) ${executorIds.mkString(", ")}")
- val response = synchronized {
- val (knownExecutors, unknownExecutors) =
executorIds.partition(executorDataMap.contains)
- unknownExecutors.foreach { id =>
- logWarning(s"Executor to kill $id does not exist!")
- }
-
- // If an executor is already pending to be removed, do not kill it again
(SPARK-9795)
- // If this executor is busy, do not kill it unless we are told to force
kill it (SPARK-9552)
- val executorsToKill = knownExecutors
- .filter { id => !executorsPendingToRemove.contains(id) }
- .filter { id => force || !scheduler.isExecutorBusy(id) }
- executorsToKill.foreach { id => executorsPendingToRemove(id) =
!countFailures }
-
- logInfo(s"Actual list of executor(s) to be killed is
${executorsToKill.mkString(", ")}")
-
- // If we do not wish to replace the executors we kill, sync the target
number of executors
- // with the cluster manager to avoid allocating new ones. When computing
the new target,
- // take into account executors that are pending to be added or removed.
- val adjustTotalExecutors =
- if (adjustTargetNumExecutors) {
- requestedTotalExecutors = math.max(requestedTotalExecutors -
executorsToKill.size, 0)
- if (requestedTotalExecutors !=
- (numExistingExecutors + numPendingExecutors -
executorsPendingToRemove.size)) {
- logDebug(
- s"""killExecutors($executorIds, $adjustTargetNumExecutors,
$countFailures, $force):
- |Executor counts do not match:
- |requestedTotalExecutors = $requestedTotalExecutors
- |numExistingExecutors = $numExistingExecutors
- |numPendingExecutors = $numPendingExecutors
- |executorsPendingToRemove =
${executorsPendingToRemove.size}""".stripMargin)
- }
- doRequestTotalExecutors(requestedTotalExecutors)
- } else {
- numPendingExecutors += executorsToKill.size
- Future.successful(true)
+ var response: Future[Seq[String]] = null
+ val idleExecutorIds = executorIds.filter { id =>
!scheduler.isExecutorBusy(id) }
+ if (!blacklistingOnTaskCompletion) {
Review comment:
We could but, the values of the `executorIdToRunningTaskIds` map (`HashSet`)
are not protected or thread safe. We leave the protection of the concurrent
trie map after the `.get(execId)`, then there are race conditions on the
`.exists` that happens against this hash set. We could make the `HashSet` a
concurrent trie also.
This could result in `isExecutorBusy` telling you an executor was idle when
it wasn't, or the other way around. Leading to some of the same things that
were fixed in https://issues.apache.org/jira/browse/SPARK-19757 coming back.
The locking as it is in the PR is keeping the
https://issues.apache.org/jira/browse/SPARK-19757 fix, as far as I can tell.
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