Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/3868#discussion_r23702493
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
---
@@ -68,36 +69,60 @@ class JobScheduler(val ssc: StreamingContext) extends
Logging {
}
def stop(processAllReceivedData: Boolean): Unit = synchronized {
- if (eventActor == null) return // scheduler has already been stopped
- logDebug("Stopping JobScheduler")
+ val shutdownExecutor = Executors.newFixedThreadPool(1)
+ implicit val context =
ExecutionContext.fromExecutorService(shutdownExecutor)
- // First, stop receiving
- receiverTracker.stop()
+ val shutdown = Future {
+ if (eventActor == null) return // scheduler has already been stopped
+ logDebug("Stopping JobScheduler")
- // Second, stop generating jobs. If it has to process all received
data,
- // then this will wait for all the processing through JobScheduler to
be over.
- jobGenerator.stop(processAllReceivedData)
+ // First, stop receiving
+ receiverTracker.stop(processAllReceivedData)
- // Stop the executor for receiving new jobs
- logDebug("Stopping job executor")
- jobExecutor.shutdown()
+ // Second, stop generating jobs. If it has to process all received
data,
+ // then this will wait for all the processing through JobScheduler
to be over.
+ jobGenerator.stop(processAllReceivedData)
- // Wait for the queued jobs to complete if indicated
+ // Stop the executor for receiving new jobs
+ logDebug("Stopping job executor")
+ jobExecutor.shutdown()
+
+ // Wait for the queued jobs to complete if indicated
+ val terminated = if (processAllReceivedData) {
+ jobExecutor.awaitTermination(1, TimeUnit.HOURS) // just a very
large period of time
+ } else {
+ jobExecutor.awaitTermination(2, TimeUnit.SECONDS)
+ }
+ if (!terminated) {
+ jobExecutor.shutdownNow()
+ }
+ logDebug("Stopped job executor")
+
+ // Stop everything else
+ listenerBus.stop()
+ ssc.env.actorSystem.stop(eventActor)
+ eventActor = null
+ }
+
+ shutdownExecutor.shutdown()
+
+ // Wait for the JobScheduler shutdown sequence to finish
val terminated = if (processAllReceivedData) {
- jobExecutor.awaitTermination(1, TimeUnit.HOURS) // just a very
large period of time
+ val gracefulTimeout = ssc.conf.getLong(
+ "spark.streaming.gracefulStopTimeout",
+ 100 * ssc.graph.batchDuration.milliseconds
--- End diff --
This number 100 seems quite arbitrary. We would like to expose this
timeout, in which case there are two possibilities
- spark.streaming.gracefulStopTimeout - A fixed interval, say 10 seconds.
The system will wait approx that long.
- spark.streaming.gracefulStopTimeoutMultiplier - A constant, say M. The
system will wait for approx (M * batch-duration).
Each has its merits. The first is easier to understand for developers and
operational people, because it will not vary from app to app (different apps
can have different batch intervals). The second one is more logical as it makes
sense scale the timeout based on batch duration - an app with 1 minute batches
will obviously take longer to shutdown than another app with 2 second batches.
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