Looks like upgrading to Spark 2.0.1 fixed it! The thread count now when I
do cat /proc/pid/status is about 84 as opposed to a 1000 in the span of 2
mins in Spark 2.0.0
On Tue, Nov 1, 2016 at 11:40 AM, Shixiong(Ryan) Zhu wrote:
> Yes, try 2.0.1!
>
> On Tue, Nov 1, 2016
Yes, try 2.0.1!
On Tue, Nov 1, 2016 at 11:25 AM, kant kodali wrote:
> AH!!! Got it! Should I use 2.0.1 then ? I don't see 2.1.0
>
> On Tue, Nov 1, 2016 at 10:14 AM, Shixiong(Ryan) Zhu <
> shixi...@databricks.com> wrote:
>
>> Dstream "Window" uses "union" to combine multiple
AH!!! Got it! Should I use 2.0.1 then ? I don't see 2.1.0
On Tue, Nov 1, 2016 at 10:14 AM, Shixiong(Ryan) Zhu wrote:
> Dstream "Window" uses "union" to combine multiple RDDs in one window into
> a single RDD.
>
> On Tue, Nov 1, 2016 at 2:59 AM kant kodali
Dstream "Window" uses "union" to combine multiple RDDs in one window into a
single RDD.
On Tue, Nov 1, 2016 at 2:59 AM kant kodali wrote:
> @Sean It looks like this problem can happen with other RDD's as well. Not
> just unionRDD
>
> On Tue, Nov 1, 2016 at 2:52 AM, kant
@Sean It looks like this problem can happen with other RDD's as well. Not
just unionRDD
On Tue, Nov 1, 2016 at 2:52 AM, kant kodali wrote:
> Hi Sean,
>
> The comments seem very relevant although I am not sure if this pull
> request https://github.com/apache/spark/pull/14985
Hi Sean,
The comments seem very relevant although I am not sure if this pull request
https://github.com/apache/spark/pull/14985 would fix my issue? I am not
sure what unionRDD.scala has anything to do with my error (I don't know
much about spark code base). Do I ever use unionRDD.scala when I
Possibly https://issues.apache.org/jira/browse/SPARK-17396 ?
On Tue, Nov 1, 2016 at 2:11 AM kant kodali wrote:
> Hi Ryan,
>
> I think you are right. This may not be related to the Receiver. I have
> attached jstack dump here. I do a simple MapToPair and reduceByKey and I
>
This question looks very similar to mine but I don't see any answer.
http://markmail.org/message/kkxhi5jjtwyadzxt
On Mon, Oct 31, 2016 at 11:24 PM, kant kodali wrote:
> Here is a UI of my thread dump.
>
> http://fastthread.io/my-thread-report.jsp?p=c2hhcmVkLzIwMTYv
>
Here is a UI of my thread dump.
http://fastthread.io/my-thread-report.jsp?p=c2hhcmVkLzIwMTYvMTEvMS8tLWpzdG
Fja19kdW1wX3dpbmRvd19pbnRlcnZhbF8xbWluX2JhdGNoX2ludGVydmFsXz
FzLnR4dC0tNi0xNy00Ng==
On Mon, Oct 31, 2016 at 7:10 PM, kant kodali wrote:
> Hi Ryan,
>
> I think you are
If there is some leaking threads, I think you should be able to see the
number of threads is increasing. You can just dump threads after 1-2 hours.
On Mon, Oct 31, 2016 at 12:59 PM, kant kodali wrote:
> yes I can certainly use jstack but it requires 4 to 5 hours for me to
>
yes I can certainly use jstack but it requires 4 to 5 hours for me to
reproduce the error so I can get back as early as possible.
Thanks a lot!
On Mon, Oct 31, 2016 at 12:41 PM, Shixiong(Ryan) Zhu <
shixi...@databricks.com> wrote:
> Then it should not be a Receiver issue. Could you use `jstack`
Then it should not be a Receiver issue. Could you use `jstack` to find out
the name of leaking threads?
On Mon, Oct 31, 2016 at 12:35 PM, kant kodali wrote:
> Hi Ryan,
>
> It happens on the driver side and I am running on a client mode (not the
> cluster mode).
>
> Thanks!
>
Hi Ryan,
It happens on the driver side and I am running on a client mode (not the
cluster mode).
Thanks!
On Mon, Oct 31, 2016 at 12:32 PM, Shixiong(Ryan) Zhu <
shixi...@databricks.com> wrote:
> Sorry, there is a typo in my previous email: this may **not** be the root
> cause if the leak
Sorry, there is a typo in my previous email: this may **not** be the root
cause if the leak threads are in the driver side.
Does it happen in the driver or executors?
On Mon, Oct 31, 2016 at 12:20 PM, kant kodali wrote:
> Hi Ryan,
>
> Ahh My Receiver.onStop method is
This is more of a Java question. You don't 'clean up' threads but rather
rearchitect your app so that you don't create long running threads that
don't terminate. Consider also an Executor instead of manually creating
threads.
On Mon, Oct 31, 2016 at 7:20 PM kant kodali wrote:
Hi Ryan,
Ahh My Receiver.onStop method is currently empty.
1) I have a hard time seeing why the receiver would crash so many
times within a span of 4 to 5 hours but anyways I understand I should
still cleanup during OnStop.
2) How do I clean up those threads? The documentation here
So in your code, each Receiver will start a new thread. Did you stop the
receiver properly in `Receiver.onStop`? Otherwise, you may leak threads
after a receiver crashes and is restarted by Spark. However, this may be
the root cause since the leak threads are in the driver side. Could you use
I am also under the assumption that *onStart *function of the Receiver is
only called only once by Spark. please correct me if I am wrong.
On Mon, Oct 31, 2016 at 11:35 AM, kant kodali wrote:
> My driver program runs a spark streaming job. And it spawns a thread by
> itself
My driver program runs a spark streaming job. And it spawns a thread by
itself only in the *onStart()* function below Other than that it doesn't
spawn any other threads. It only calls MapToPair, ReduceByKey, forEachRDD,
Collect functions.
public class NSQReceiver extends Receiver {
private
> how do I tell my spark driver program to not create so many?
This may depend on your driver program. Do you spawn any threads in
it? Could you share some more information on the driver program, spark
version and your environment? It would greatly help others to help you
On Mon, Oct 31, 2016
The source of my problem is actually that I am running into the following
error. This error seems to happen after running my driver program for 4
hours.
"Exception in thread "ForkJoinPool-50-worker-11" Exception in thread
"dag-scheduler-event-loop" Exception in thread "ForkJoinPool-50-worker-13"
ps -L [pid] is what shows threads. I am not sure this is counting what you
think it does. My shell process has about a hundred threads, and I can't
imagine why one would have thousands unless your app spawned them.
On Mon, Oct 31, 2016 at 10:20 AM kant kodali wrote:
> when I
when I do
ps -elfT | grep "spark-driver-program.jar" | wc -l
The result is around 32K. why does it create so many threads how can I
limit this?
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