Github user markhamstra commented on a diff in the pull request:
https://github.com/apache/spark/pull/186#discussion_r11101486
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -116,21 +119,30 @@ class DAGScheduler(
private val metadataCleaner =
new MetadataCleaner(MetadataCleanerType.DAG_SCHEDULER, this.cleanup,
env.conf)
- taskScheduler.setDAGScheduler(this)
-
/**
- * Starts the event processing actor. The actor has two
responsibilities:
- *
- * 1. Waits for events like job submission, task finished, task failure
etc., and calls
- * [[org.apache.spark.scheduler.DAGScheduler.processEvent()]] to
process them.
- * 2. Schedules a periodical task to resubmit failed stages.
- *
- * NOTE: the actor cannot be started in the constructor, because the
periodical task references
- * some internal states of the enclosing
[[org.apache.spark.scheduler.DAGScheduler]] object, thus
- * cannot be scheduled until the
[[org.apache.spark.scheduler.DAGScheduler]] is fully constructed.
+ * Starts the event processing actor within the supervisor. The
eventProcessingActor
+ * waits for events like job submission, task finished, task failure
etc., and calls
+ * [[org.apache.spark.scheduler.DAGScheduler.processEvent()]] to process
them.
*/
- def start() {
- eventProcessActor = env.actorSystem.actorOf(Props(new Actor {
+ env.actorSystem.actorOf(Props(new Actor {
+
+ override val supervisorStrategy =
+ OneForOneStrategy() {
+ case x: Exception => {
+ logError("eventProcesserActor failed due to the error %s;
shutting down SparkContext"
+ .format(x.getMessage))
+ doCancelAllJobs()
+ sc.stop()
+ Stop
--- End diff --
Right, which may be enough as long as all we are trying to accomplish is a
clean shutdown of the whole system, not restarting all or part of it while
retaining state and partial results from running jobs. TaskManager's messages
won't go anywhere but the /deadLetters synthetic actor, but I think that's fine
as long as we avoid throwing uncaught exceptions etc. while trying to shutdown.
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