Would the following change work for you ?
diff --git
a/core/src/main/scala/org/apache/spark/util/AsynchronousListenerBus.scala
b/core/src/main/scala/org/apache/spark/util/AsynchronousListenerBus.scala
index 61b5a4c..c330d25 100644
---
a/core/src/main/scala/org/apache/spark/util/AsynchronousListenerBus.scala
+++
b/core/src/main/scala/org/apache/spark/util/AsynchronousListenerBus.scala
@@ -66,6 +66,7 @@ private[spark] abstract class AsynchronousListenerBus[L
<: AnyRef, E](name: Stri
self.synchronized {
processingEvent = true
}
+ if (stopped.get()) return
try {
val event = eventQueue.poll
if (event == null) {
On Sat, Nov 7, 2015 at 12:17 PM, vonnagy <i...@vadio.com> wrote:
> If I have a streaming job (Spark 1.5.1) and attempt to stop the stream
> after
> the first batch, the system locks up and never completes. The pseudo code
> below shows that after the batch complete notification is called the stream
> is stopped. I have traced the lockup to the call `listener.stop()`in
> JobScheduler (line 114) which attempts to join the thread in
> AsynchronousListenerBus. That thread never ends because it is still getting
> messages `SparkListenerExecutorMetricsUpdate` from the DAGScheduler. The
> thread never ends because the events continue to come in.
>
> Any thoughts/ideas on how I can effectively stop the stream after the first
> batch would greatly appreciated.
>
> Psuedo Example:
>
> class SomeJob {
>
> val ssc = createStreamingContext()
> val listener = new MyListener(ssc)
> ssc.addStreamingListener(listener)
>
> val stream = getStream
>
> stream.foreachRDD { rdd =>
> // Do something with the data
> }
> }
>
> class MyListener(ctx: StreamingContext) extends StreamingListener {
> override def onBatchCompleted(batchCompleted:
> StreamingListenerBatchCompleted) = synchronized {
> ctx.stop(false, false)
> // NOTE: I get the same results with ctx.stop(), ctx.stop(true),
> ctx.stop(true, true), or ctx.stop(false, false)
> }
> }
>
>
>
> --
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