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https://issues.apache.org/jira/browse/SPARK-17397?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15466898#comment-15466898
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Sean Owen edited comment on SPARK-17397 at 10/2/16 4:22 PM:
------------------------------------------------------------
I think it's reasonable to show the
{code}
try { awaitTermination() } finally { stop() }
{code}
pattern as a good practice. That much could certainly be reflected in examples
and docs.
It could be worth another note about potentially recovering from
awaitTermination exceptions, but I'm not sure what can be promised. Some
exceptions would indicate a fatal problem, some wouldn't. I might stop short of
that, to be conservative. Or, at best mention it to about that level.
was (Author: srowen):
I think it's reasonable to show the try { awaitTermination() } finally { stop()
} pattern as a good practice. That much could certainly be reflected in
examples and docs.
It could be worth another note about potentially recovering from
awaitTermination exceptions, but I'm not sure what can be promised. Some
exceptions would indicate a fatal problem, some wouldn't. I might stop short of
that, to be conservative. Or, at best mention it to about that level.
> Show example of what to do when awaitTermination() throws an Exception
> ----------------------------------------------------------------------
>
> Key: SPARK-17397
> URL: https://issues.apache.org/jira/browse/SPARK-17397
> Project: Spark
> Issue Type: Improvement
> Components: Documentation, Streaming
> Affects Versions: 2.0.0
> Environment: Linux, Scala but probably general
> Reporter: Spiro Michaylov
> Priority: Minor
>
> When awaitTermination propagates an exception that was thrown in processing a
> batch, the StreamingContext keeps running. Perhaps this is by design, but I
> don't see any mention of it in the API docs or the streaming programming
> guide. It's not clear what idiom should be used to block the thread until the
> context HAS been stopped in a situation where stream processing is throwing
> lots of exceptions.
> For example, in the following, streaming takes the full 30 seconds to
> terminate. My hope in asking this is to improve my own understanding and
> perhaps inspire documentation improvements. I'm not filing a bug because it's
> not clear to me whether this is working as intended.
> {code}
> val conf = new
> SparkConf().setAppName("ExceptionPropagation").setMaster("local[4]")
> val sc = new SparkContext(conf)
> // streams will produce data every second
> val ssc = new StreamingContext(sc, Seconds(1))
> val qm = new QueueMaker(sc, ssc)
> // create the stream
> val stream = // create some stream
> // register for data
> stream
> .map(x => { throw new SomeException("something"); x} )
> .foreachRDD(r => println("*** count = " + r.count()))
> // start streaming
> ssc.start()
> new Thread("Delayed Termination") {
> override def run() {
> Thread.sleep(30000)
> ssc.stop()
> }
> }.start()
> println("*** producing data")
> // start producing data
> qm.populateQueue()
> try {
> ssc.awaitTermination()
> println("*** streaming terminated")
> } catch {
> case e: Exception => {
> println("*** streaming exception caught in monitor thread")
> }
> }
> // if the above goes down the exception path, there seems no
> // good way to block here until the streaming context is stopped
> println("*** done")
> {code}
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