I am facing a issue when submitting a spark job jar in yarn. It is working well and giving me as expected result when I am submitting it with --master yarn-client
The command is as follow;
./spark-submit --class main.MainClass --master yarn-client --driver-memory 4g --executor-memory 4g --num-executors 4 --executor-cores 2 job.jar other-options
But the same is not working when submitting into cluster mode; command as follow;
./spark-submit --class main.MainClass --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 4g --num-executors 4 --executor-cores 2 job.jar other-options"
My yarn-site.xml is as follow;
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>128</value>
<description>Minimum limit of memory to allocate to each container request at the Resource Manager.</description>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>20048</value>
<description>Maximum limit of memory to allocate to each container request at the Resource Manager.</description>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-vcores</name>
<value>1</value>
<description>The minimum allocation for every container request at the RM, in terms of virtual CPU cores. Requests lower than this won't take effect, and the specified value will get allocated the minimum.</description>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-vcores</name>
<value>2</value>
<description>The maximum allocation for every container request at the RM, in terms of virtual CPU cores. Requests higher than this won't take effect, and will get capped to this value.</description>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>24096</value>
<description>Physical memory, in MB, to be made available to running containers</description>
</property>
<property>
<name>yarn.nodemanager.resource.cpu-vcores</name>
<value>4</value>
<description>Number of CPU cores that can be allocated for containers.</description>
</property>
<property>
<name>yarn.nodemanager.pmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
My yarn stderr log is
17/03/23 03:30:44 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3315fed4{/static,null,AVAILABLE}
17/03/23 03:30:44 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3e430b9a{/,null,AVAILABLE}
17/03/23 03:30:44 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@77184f65{/api,null,AVAILABLE}
17/03/23 03:30:44 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@643f7b84{/stages/stage/kill,null,AVAILABLE}
17/03/23 03:30:44 INFO server.ServerConnector: Started ServerConnector@27614db2{HTTP/1.1}{0.0.0.0:37212}
17/03/23 03:30:44 INFO server.Server: Started @7799ms
17/03/23 03:30:44 INFO util.Utils: Successfully started service 'SparkUI' on port 37212.
17/03/23 03:30:44 INFO ui.SparkUI: Bound SparkUI to 0.0.0.0, and started at http://50.31.66.56:37212
17/03/23 03:30:44 INFO cluster.YarnClusterScheduler: Created YarnClusterScheduler
17/03/23 03:30:44 INFO cluster.SchedulerExtensionServices: Starting Yarn extension services with app application_1490254182417_0001 and attemptId Some(appattempt_1490254182417_0001_000001)
17/03/23 03:30:44 INFO util.Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 45469.
17/03/23 03:30:44 INFO netty.NettyBlockTransferService: Server created on 50.31.66.56:45469
17/03/23 03:30:44 INFO storage.BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 50.31.66.56, 45469)
17/03/23 03:30:44 INFO storage.BlockManagerMasterEndpoint: Registering block manager 50.31.66.56:45469 with 2004.6 MB RAM, BlockManagerId(driver, 50.31.66.56, 45469)
17/03/23 03:30:44 INFO storage.BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 50.31.66.56, 45469)
17/03/23 03:30:44 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@60245f4e{/metrics/json,null,AVAILABLE}
17/03/23 03:30:49 INFO scheduler.EventLoggingListener: Logging events to hdfs://mecku-1:54310/spark/application_1490254182417_0001_1
17/03/23 03:30:49 INFO cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: ApplicationMaster registered as NettyRpcEndpointRef(spark://[email protected]:50465)
17/03/23 03:30:49 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8030
17/03/23 03:30:49 INFO yarn.YarnRMClient: Registering the ApplicationMaster
17/03/23 03:30:49 INFO yarn.YarnAllocator: Will request 4 executor containers, each with 2 cores and 4505 MB memory including 409 MB overhead
17/03/23 03:30:49 INFO yarn.YarnAllocator: Canceled 0 container requests (locality no longer needed)
17/03/23 03:30:49 INFO yarn.YarnAllocator: Submitted container request (host: Any, capability: <memory:4505, vCores:2>)
17/03/23 03:30:49 INFO yarn.YarnAllocator: Submitted container request (host: Any, capability: <memory:4505, vCores:2>)
17/03/23 03:30:49 INFO yarn.YarnAllocator: Submitted container request (host: Any, capability: <memory:4505, vCores:2>)
17/03/23 03:30:49 INFO yarn.YarnAllocator: Submitted container request (host: Any, capability: <memory:4505, vCores:2>)
17/03/23 03:30:49 INFO yarn.ApplicationMaster: Started progress reporter thread with (heartbeat : 3000, initial allocation : 200) intervals
17/03/23 03:30:49 INFO yarn.ApplicationMaster: Unregistering ApplicationMaster with SUCCEEDED
17/03/23 03:30:49 INFO impl.AMRMClientImpl: Waiting for application to be successfully unregistered.
17/03/23 03:30:49 INFO yarn.ApplicationMaster: Deleting staging directory hdfs://localhost:54310/user/root/.sparkStaging/application_1490254182417_0001
17/03/23 03:30:49 INFO storage.DiskBlockManager: Shutdown hook called
17/03/23 03:30:49 INFO util.ShutdownHookManager: Shutdown hook called
17/03/23 03:30:49 INFO util.ShutdownHookManager: Deleting directory /tmp/hadoop-root/nm-local-dir/usercache/root/appcache/application_1490254182417_0001/spark-d77de654-4040-4b43-8155-efb155008b4b
17/03/23 03:30:49 INFO util.ShutdownHookManager: Deleting directory /tmp/hadoop-root/nm-local-dir/usercache/root/appcache/application_1490254182417_0001/spark-d77de654-4040-4b43-8155-efb155008b4b/userFiles-d71596df-df26-4b88-b51e-f0b962daf84a
17/03/23 03:30:40 INFO yarn.ApplicationMaster: ApplicationAttemptId: appattempt_1490254182417_0001_000001
17/03/23 03:30:40 INFO spark.SecurityManager: Changing view acls to: root 17/03/23 03:30:40 INFO spark.SecurityManager: Changing modify acls to: ro
But after everything my spark job is not running, as you can see no error is shown here. Any idea behind the issue?
