Re: No executors allocated on yarn with latest master branch

2015-03-09 Thread Sandy Ryza
You would have needed to configure it by
setting yarn.scheduler.capacity.resource-calculator to something ending in
DominantResourceCalculator.  If you haven't configured it, there's a high
probability that the recently committed
https://issues.apache.org/jira/browse/SPARK-6050 will fix your problem.

On Wed, Feb 25, 2015 at 1:36 AM, Anders Arpteg arp...@spotify.com wrote:

 We're using the capacity scheduler, to the best of my knowledge. Unsure if
 multi resource scheduling is used, but if you know of an easy way to figure
 that out, then let me know.

 Thanks,
 Anders

 On Sat, Feb 21, 2015 at 12:05 AM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 Are you using the capacity scheduler or fifo scheduler without multi
 resource scheduling by any chance?

 On Thu, Feb 12, 2015 at 1:51 PM, Anders Arpteg arp...@spotify.com
 wrote:

 The nm logs only seems to contain similar to the following. Nothing else
 in the same time range. Any help?

 2015-02-12 20:47:31,245 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_02
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_12
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_22
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_32
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_42
 2015-02-12 21:24:30,515 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: FINISH_APPLICATION sent to absent application
 application_1422406067005_0053

 On Thu, Feb 12, 2015 at 10:38 PM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 It seems unlikely to me that it would be a 2.2 issue, though not
 entirely impossible.  Are you able to find any of the container logs?  Is
 the NodeManager launching containers and reporting some exit code?

 -Sandy

 On Thu, Feb 12, 2015 at 1:21 PM, Anders Arpteg arp...@spotify.com
 wrote:

 No, not submitting from windows, from a debian distribution. Had a
 quick look at the rm logs, and it seems some containers are allocated but
 then released again for some reason. Not easy to make sense of the logs,
 but here is a snippet from the logs (from a test in our small test 
 cluster)
 if you'd like to have a closer look: http://pastebin.com/8WU9ivqC

 Sandy, sounds like it could possible be a 2.2 issue then, or what do
 you think?

 Thanks,
 Anders

 On Thu, Feb 12, 2015 at 3:11 PM, Aniket Bhatnagar 
 aniket.bhatna...@gmail.com wrote:

 This is tricky to debug. Check logs of node and resource manager of
 YARN to see if you can trace the error. In the past I have to closely 
 look
 at arguments getting passed to YARN container (they get logged before
 attempting to launch containers). If I still don't get a clue, I had to
 check the script generated by YARN to execute the container and even run
 manually to trace at what line the error has occurred.

 BTW are you submitting the job from windows?

 On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com
 wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as
 well? No strange log message during startup, and can't see any other log
 messages since no executer gets launched. Does not seems to work in
 yarn-client mode either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at
 org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at
 com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native
 Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 

Re: No executors allocated on yarn with latest master branch

2015-02-25 Thread Anders Arpteg
We're using the capacity scheduler, to the best of my knowledge. Unsure if
multi resource scheduling is used, but if you know of an easy way to figure
that out, then let me know.

Thanks,
Anders

On Sat, Feb 21, 2015 at 12:05 AM, Sandy Ryza sandy.r...@cloudera.com
wrote:

 Are you using the capacity scheduler or fifo scheduler without multi
 resource scheduling by any chance?

 On Thu, Feb 12, 2015 at 1:51 PM, Anders Arpteg arp...@spotify.com wrote:

 The nm logs only seems to contain similar to the following. Nothing else
 in the same time range. Any help?

 2015-02-12 20:47:31,245 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_02
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_12
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_22
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_32
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_42
 2015-02-12 21:24:30,515 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: FINISH_APPLICATION sent to absent application
 application_1422406067005_0053

 On Thu, Feb 12, 2015 at 10:38 PM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 It seems unlikely to me that it would be a 2.2 issue, though not
 entirely impossible.  Are you able to find any of the container logs?  Is
 the NodeManager launching containers and reporting some exit code?

 -Sandy

 On Thu, Feb 12, 2015 at 1:21 PM, Anders Arpteg arp...@spotify.com
 wrote:

 No, not submitting from windows, from a debian distribution. Had a
 quick look at the rm logs, and it seems some containers are allocated but
 then released again for some reason. Not easy to make sense of the logs,
 but here is a snippet from the logs (from a test in our small test cluster)
 if you'd like to have a closer look: http://pastebin.com/8WU9ivqC

 Sandy, sounds like it could possible be a 2.2 issue then, or what do
 you think?

 Thanks,
 Anders

 On Thu, Feb 12, 2015 at 3:11 PM, Aniket Bhatnagar 
 aniket.bhatna...@gmail.com wrote:

 This is tricky to debug. Check logs of node and resource manager of
 YARN to see if you can trace the error. In the past I have to closely look
 at arguments getting passed to YARN container (they get logged before
 attempting to launch containers). If I still don't get a clue, I had to
 check the script generated by YARN to execute the container and even run
 manually to trace at what line the error has occurred.

 BTW are you submitting the job from windows?

 On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com
 wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as
 well? No strange log message during startup, and can't see any other log
 messages since no executer gets launched. Does not seems to work in
 yarn-client mode either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at
 org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at
 com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
 at java.lang.reflect.Method.invoke(Method.java:597)
 at
 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
 at
 org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
 at
 org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
 at
 

Re: No executors allocated on yarn with latest master branch

2015-02-20 Thread Sandy Ryza
Are you using the capacity scheduler or fifo scheduler without multi
resource scheduling by any chance?

On Thu, Feb 12, 2015 at 1:51 PM, Anders Arpteg arp...@spotify.com wrote:

 The nm logs only seems to contain similar to the following. Nothing else
 in the same time range. Any help?

 2015-02-12 20:47:31,245 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_02
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_12
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_22
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_32
 2015-02-12 20:47:31,246 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: KILL_CONTAINER sent to absent container
 container_1422406067005_0053_01_42
 2015-02-12 21:24:30,515 WARN
 org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
 Event EventType: FINISH_APPLICATION sent to absent application
 application_1422406067005_0053

 On Thu, Feb 12, 2015 at 10:38 PM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 It seems unlikely to me that it would be a 2.2 issue, though not entirely
 impossible.  Are you able to find any of the container logs?  Is the
 NodeManager launching containers and reporting some exit code?

 -Sandy

 On Thu, Feb 12, 2015 at 1:21 PM, Anders Arpteg arp...@spotify.com
 wrote:

 No, not submitting from windows, from a debian distribution. Had a quick
 look at the rm logs, and it seems some containers are allocated but then
 released again for some reason. Not easy to make sense of the logs, but
 here is a snippet from the logs (from a test in our small test cluster) if
 you'd like to have a closer look: http://pastebin.com/8WU9ivqC

 Sandy, sounds like it could possible be a 2.2 issue then, or what do you
 think?

 Thanks,
 Anders

 On Thu, Feb 12, 2015 at 3:11 PM, Aniket Bhatnagar 
 aniket.bhatna...@gmail.com wrote:

 This is tricky to debug. Check logs of node and resource manager of
 YARN to see if you can trace the error. In the past I have to closely look
 at arguments getting passed to YARN container (they get logged before
 attempting to launch containers). If I still don't get a clue, I had to
 check the script generated by YARN to execute the container and even run
 manually to trace at what line the error has occurred.

 BTW are you submitting the job from windows?

 On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as
 well? No strange log message during startup, and can't see any other log
 messages since no executer gets launched. Does not seems to work in
 yarn-client mode either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at
 com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
 at java.lang.reflect.Method.invoke(Method.java:597)
 at
 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
 at
 org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
 at
 org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
 at
 org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:99)
 at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

 /Anders


 On Thu, Feb 12, 2015 at 1:33 AM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 Hi Anders,

 I just tried this out and was able to 

Re: No executors allocated on yarn with latest master branch

2015-02-12 Thread Anders Arpteg
The nm logs only seems to contain similar to the following. Nothing else in
the same time range. Any help?

2015-02-12 20:47:31,245 WARN
org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
Event EventType: KILL_CONTAINER sent to absent container
container_1422406067005_0053_01_02
2015-02-12 20:47:31,246 WARN
org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
Event EventType: KILL_CONTAINER sent to absent container
container_1422406067005_0053_01_12
2015-02-12 20:47:31,246 WARN
org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
Event EventType: KILL_CONTAINER sent to absent container
container_1422406067005_0053_01_22
2015-02-12 20:47:31,246 WARN
org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
Event EventType: KILL_CONTAINER sent to absent container
container_1422406067005_0053_01_32
2015-02-12 20:47:31,246 WARN
org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
Event EventType: KILL_CONTAINER sent to absent container
container_1422406067005_0053_01_42
2015-02-12 21:24:30,515 WARN
org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl:
Event EventType: FINISH_APPLICATION sent to absent application
application_1422406067005_0053

On Thu, Feb 12, 2015 at 10:38 PM, Sandy Ryza sandy.r...@cloudera.com
wrote:

 It seems unlikely to me that it would be a 2.2 issue, though not entirely
 impossible.  Are you able to find any of the container logs?  Is the
 NodeManager launching containers and reporting some exit code?

 -Sandy

 On Thu, Feb 12, 2015 at 1:21 PM, Anders Arpteg arp...@spotify.com wrote:

 No, not submitting from windows, from a debian distribution. Had a quick
 look at the rm logs, and it seems some containers are allocated but then
 released again for some reason. Not easy to make sense of the logs, but
 here is a snippet from the logs (from a test in our small test cluster) if
 you'd like to have a closer look: http://pastebin.com/8WU9ivqC

 Sandy, sounds like it could possible be a 2.2 issue then, or what do you
 think?

 Thanks,
 Anders

 On Thu, Feb 12, 2015 at 3:11 PM, Aniket Bhatnagar 
 aniket.bhatna...@gmail.com wrote:

 This is tricky to debug. Check logs of node and resource manager of YARN
 to see if you can trace the error. In the past I have to closely look at
 arguments getting passed to YARN container (they get logged before
 attempting to launch containers). If I still don't get a clue, I had to
 check the script generated by YARN to execute the container and even run
 manually to trace at what line the error has occurred.

 BTW are you submitting the job from windows?

 On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as
 well? No strange log message during startup, and can't see any other log
 messages since no executer gets launched. Does not seems to work in
 yarn-client mode either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
 at java.lang.reflect.Method.invoke(Method.java:597)
 at
 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
 at
 org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
 at
 org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
 at
 org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:99)
 at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

 /Anders


 On Thu, Feb 12, 2015 at 1:33 AM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 Hi Anders,

 I just tried this out and was able to successfully acquire executors.
 Any strange log messages or additional color you can provide on your
 setup?  Does yarn-client mode work?

 -Sandy

 On Wed, Feb 11, 2015 at 1:28 PM, Anders Arpteg 

Re: No executors allocated on yarn with latest master branch

2015-02-12 Thread Sandy Ryza
It seems unlikely to me that it would be a 2.2 issue, though not entirely
impossible.  Are you able to find any of the container logs?  Is the
NodeManager launching containers and reporting some exit code?

-Sandy

On Thu, Feb 12, 2015 at 1:21 PM, Anders Arpteg arp...@spotify.com wrote:

 No, not submitting from windows, from a debian distribution. Had a quick
 look at the rm logs, and it seems some containers are allocated but then
 released again for some reason. Not easy to make sense of the logs, but
 here is a snippet from the logs (from a test in our small test cluster) if
 you'd like to have a closer look: http://pastebin.com/8WU9ivqC

 Sandy, sounds like it could possible be a 2.2 issue then, or what do you
 think?

 Thanks,
 Anders

 On Thu, Feb 12, 2015 at 3:11 PM, Aniket Bhatnagar 
 aniket.bhatna...@gmail.com wrote:

 This is tricky to debug. Check logs of node and resource manager of YARN
 to see if you can trace the error. In the past I have to closely look at
 arguments getting passed to YARN container (they get logged before
 attempting to launch containers). If I still don't get a clue, I had to
 check the script generated by YARN to execute the container and even run
 manually to trace at what line the error has occurred.

 BTW are you submitting the job from windows?

 On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as
 well? No strange log message during startup, and can't see any other log
 messages since no executer gets launched. Does not seems to work in
 yarn-client mode either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
 at java.lang.reflect.Method.invoke(Method.java:597)
 at
 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
 at
 org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
 at
 org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
 at
 org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:99)
 at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

 /Anders


 On Thu, Feb 12, 2015 at 1:33 AM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 Hi Anders,

 I just tried this out and was able to successfully acquire executors.
 Any strange log messages or additional color you can provide on your
 setup?  Does yarn-client mode work?

 -Sandy

 On Wed, Feb 11, 2015 at 1:28 PM, Anders Arpteg arp...@spotify.com
 wrote:

 Hi,

 Compiled the latest master of Spark yesterday (2015-02-10) for Hadoop
 2.2 and failed executing jobs in yarn-cluster mode for that build. Works
 successfully with spark 1.2 (and also master from 2015-01-16), so 
 something
 has changed since then that prevents the job from receiving any executors
 on the cluster.

 Basic symptoms are that the jobs fires up the AM, but after examining
 the executors page in the web ui, only the driver is listed, no
 executors are ever received, and the driver keep waiting forever. Has
 anyone seemed similar problems?

 Thanks for any insights,
 Anders







Re: No executors allocated on yarn with latest master branch

2015-02-12 Thread Anders Arpteg
Interesting to hear that it works for you. Are you using Yarn 2.2 as well?
No strange log message during startup, and can't see any other log messages
since no executer gets launched. Does not seems to work in yarn-client mode
either, failing with the exception below.

Exception in thread main org.apache.spark.SparkException: Yarn
application has already ended! It might have been killed or unable to
launch application master.
at
org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
at
org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
at
org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
at org.apache.spark.SparkContext.init(SparkContext.scala:370)
at
com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
at com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
at com.spotify.analytics.DataSampler.main(DataSampler.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at
org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
at
org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
at
org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:99)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

/Anders


On Thu, Feb 12, 2015 at 1:33 AM, Sandy Ryza sandy.r...@cloudera.com wrote:

 Hi Anders,

 I just tried this out and was able to successfully acquire executors.  Any
 strange log messages or additional color you can provide on your setup?
 Does yarn-client mode work?

 -Sandy

 On Wed, Feb 11, 2015 at 1:28 PM, Anders Arpteg arp...@spotify.com wrote:

 Hi,

 Compiled the latest master of Spark yesterday (2015-02-10) for Hadoop
 2.2 and failed executing jobs in yarn-cluster mode for that build. Works
 successfully with spark 1.2 (and also master from 2015-01-16), so something
 has changed since then that prevents the job from receiving any executors
 on the cluster.

 Basic symptoms are that the jobs fires up the AM, but after examining the
 executors page in the web ui, only the driver is listed, no executors
 are ever received, and the driver keep waiting forever. Has anyone seemed
 similar problems?

 Thanks for any insights,
 Anders





Re: No executors allocated on yarn with latest master branch

2015-02-12 Thread Anders Arpteg
No, not submitting from windows, from a debian distribution. Had a quick
look at the rm logs, and it seems some containers are allocated but then
released again for some reason. Not easy to make sense of the logs, but
here is a snippet from the logs (from a test in our small test cluster) if
you'd like to have a closer look: http://pastebin.com/8WU9ivqC

Sandy, sounds like it could possible be a 2.2 issue then, or what do you
think?

Thanks,
Anders

On Thu, Feb 12, 2015 at 3:11 PM, Aniket Bhatnagar 
aniket.bhatna...@gmail.com wrote:

 This is tricky to debug. Check logs of node and resource manager of YARN
 to see if you can trace the error. In the past I have to closely look at
 arguments getting passed to YARN container (they get logged before
 attempting to launch containers). If I still don't get a clue, I had to
 check the script generated by YARN to execute the container and even run
 manually to trace at what line the error has occurred.

 BTW are you submitting the job from windows?

 On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as
 well? No strange log message during startup, and can't see any other log
 messages since no executer gets launched. Does not seems to work in
 yarn-client mode either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
 at java.lang.reflect.Method.invoke(Method.java:597)
 at
 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
 at
 org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
 at
 org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
 at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:99)
 at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

 /Anders


 On Thu, Feb 12, 2015 at 1:33 AM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 Hi Anders,

 I just tried this out and was able to successfully acquire executors.
 Any strange log messages or additional color you can provide on your
 setup?  Does yarn-client mode work?

 -Sandy

 On Wed, Feb 11, 2015 at 1:28 PM, Anders Arpteg arp...@spotify.com
 wrote:

 Hi,

 Compiled the latest master of Spark yesterday (2015-02-10) for Hadoop
 2.2 and failed executing jobs in yarn-cluster mode for that build. Works
 successfully with spark 1.2 (and also master from 2015-01-16), so something
 has changed since then that prevents the job from receiving any executors
 on the cluster.

 Basic symptoms are that the jobs fires up the AM, but after examining
 the executors page in the web ui, only the driver is listed, no
 executors are ever received, and the driver keep waiting forever. Has
 anyone seemed similar problems?

 Thanks for any insights,
 Anders






Re: No executors allocated on yarn with latest master branch

2015-02-12 Thread Aniket Bhatnagar
This is tricky to debug. Check logs of node and resource manager of YARN to
see if you can trace the error. In the past I have to closely look at
arguments getting passed to YARN container (they get logged before
attempting to launch containers). If I still don't get a clue, I had to
check the script generated by YARN to execute the container and even run
manually to trace at what line the error has occurred.

BTW are you submitting the job from windows?

On Thu, Feb 12, 2015, 3:34 PM Anders Arpteg arp...@spotify.com wrote:

 Interesting to hear that it works for you. Are you using Yarn 2.2 as well?
 No strange log message during startup, and can't see any other log messages
 since no executer gets launched. Does not seems to work in yarn-client mode
 either, failing with the exception below.

 Exception in thread main org.apache.spark.SparkException: Yarn
 application has already ended! It might have been killed or unable to
 launch application master.
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:119)
 at
 org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
 at
 org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
 at org.apache.spark.SparkContext.init(SparkContext.scala:370)
 at
 com.spotify.analytics.AnalyticsSparkContext.init(AnalyticsSparkContext.scala:8)
 at com.spotify.analytics.DataSampler$.main(DataSampler.scala:42)
 at com.spotify.analytics.DataSampler.main(DataSampler.scala)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
 at java.lang.reflect.Method.invoke(Method.java:597)
 at
 org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:551)
 at
 org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:155)
 at
 org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:178)
 at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:99)
 at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

 /Anders


 On Thu, Feb 12, 2015 at 1:33 AM, Sandy Ryza sandy.r...@cloudera.com
 wrote:

 Hi Anders,

 I just tried this out and was able to successfully acquire executors.
 Any strange log messages or additional color you can provide on your
 setup?  Does yarn-client mode work?

 -Sandy

 On Wed, Feb 11, 2015 at 1:28 PM, Anders Arpteg arp...@spotify.com
 wrote:

 Hi,

 Compiled the latest master of Spark yesterday (2015-02-10) for Hadoop
 2.2 and failed executing jobs in yarn-cluster mode for that build. Works
 successfully with spark 1.2 (and also master from 2015-01-16), so something
 has changed since then that prevents the job from receiving any executors
 on the cluster.

 Basic symptoms are that the jobs fires up the AM, but after examining
 the executors page in the web ui, only the driver is listed, no
 executors are ever received, and the driver keep waiting forever. Has
 anyone seemed similar problems?

 Thanks for any insights,
 Anders






No executors allocated on yarn with latest master branch

2015-02-11 Thread Anders Arpteg
Hi,

Compiled the latest master of Spark yesterday (2015-02-10) for Hadoop 2.2
and failed executing jobs in yarn-cluster mode for that build. Works
successfully with spark 1.2 (and also master from 2015-01-16), so something
has changed since then that prevents the job from receiving any executors
on the cluster.

Basic symptoms are that the jobs fires up the AM, but after examining the
executors page in the web ui, only the driver is listed, no executors are
ever received, and the driver keep waiting forever. Has anyone seemed
similar problems?

Thanks for any insights,
Anders


Re: No executors allocated on yarn with latest master branch

2015-02-11 Thread Sandy Ryza
Hi Anders,

I just tried this out and was able to successfully acquire executors.  Any
strange log messages or additional color you can provide on your setup?
Does yarn-client mode work?

-Sandy

On Wed, Feb 11, 2015 at 1:28 PM, Anders Arpteg arp...@spotify.com wrote:

 Hi,

 Compiled the latest master of Spark yesterday (2015-02-10) for Hadoop 2.2
 and failed executing jobs in yarn-cluster mode for that build. Works
 successfully with spark 1.2 (and also master from 2015-01-16), so something
 has changed since then that prevents the job from receiving any executors
 on the cluster.

 Basic symptoms are that the jobs fires up the AM, but after examining the
 executors page in the web ui, only the driver is listed, no executors
 are ever received, and the driver keep waiting forever. Has anyone seemed
 similar problems?

 Thanks for any insights,
 Anders