Re: No executors allocated on yarn with latest master branch
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 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 > 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 >> 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 >>> 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 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 >> 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.(SparkContext.scala:370) >>> at >>> com.spotify.analytics.AnalyticsSparkContext.(AnalyticsSparkContext.scala:8) >>> at >>> com.spotify.analytics.DataSampler$.m
Re: No executors allocated on yarn with latest master branch
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 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 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 >> 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 >>> 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 > 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.(SparkContext.scala:370) >> at >> com.spotify.analytics.AnalyticsSparkContext.(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 >>
Re: No executors allocated on yarn with latest master branch
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 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 > 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 >> 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 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.(SparkContext.scala:370) > at > com.spotify.analytics.AnalyticsSparkContext.(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(SparkSubmi
Re: No executors allocated on yarn with latest master branch
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 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 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 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.(SparkContext.scala:370) at com.spotify.analytics.AnalyticsSparkContext.(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 wrote: > Hi Anders, > > I just tried this out and was able to successfully acquire executors. > Any stra
Re: No executors allocated on yarn with latest master branch
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 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 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.(SparkContext.scala:370) >>> at >>> com.spotify.analytics.AnalyticsSparkContext.(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 >>> 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 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
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 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.(SparkContext.scala:370) >> at >> com.spotify.analytics.AnalyticsSparkContext.(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 >> 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 >>> 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
I ran against 2.6, not 2.2. For that yarn-client run, do you have the application master log? On Thu, Feb 12, 2015 at 6:11 AM, 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 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.(SparkContext.scala:370) >> at >> com.spotify.analytics.AnalyticsSparkContext.(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 >> 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 >>> 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
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 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.(SparkContext.scala:370) > at > com.spotify.analytics.AnalyticsSparkContext.(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 > 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 >> 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
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.(SparkContext.scala:370) at com.spotify.analytics.AnalyticsSparkContext.(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 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 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
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 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 >
