问题
Getting the below error with respect to the container while submitting an spark application to YARN. The HADOOP(2.7.3)/SPARK (2.1) environment is running a pseudo-distributed mode in a single node cluster. The application works perfectly when made to run in local model however trying to check its correctness in a cluster mode using YARN as RM and hit some roadblock. New to this world hence looking for help.
--- Applications logs
2017-04-11 07:13:28 INFO Client:58 - Submitting application 1 to ResourceManager
2017-04-11 07:13:28 INFO YarnClientImpl:174 - Submitted application application_1491909036583_0001 to ResourceManager at /0.0.0.0:8032
2017-04-11 07:13:29 INFO Client:58 - Application report for application_1491909036583_0001 (state: ACCEPTED)
2017-04-11 07:13:29 INFO Client:58 -
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: default
start time: 1491909208425
final status: UNDEFINED
tracking URL: http://ip-xxx.xx.xx.xxx:8088/proxy/application_1491909036583_0001/
user: xxxx
2017-04-11 07:13:30 INFO Client:58 - Application report for application_1491909036583_0001 (state: ACCEPTED)
2017-04-11 07:13:31 INFO Client:58 - Application report for application_1491909036583_0001 (state: ACCEPTED)
2017-04-11 07:13:32 INFO Client:58 - Application report for application_1491909036583_0001 (state: ACCEPTED)
2017-04-11 07:17:37 INFO Client:58 - Application report for application_1491909036583_0001 (state: FAILED)
2017-04-11 07:17:37 INFO Client:58 -
client token: N/A
diagnostics: Application application_1491909036583_0001 failed 2 times due to AM Container for appattempt_1491909036583_0001_000002 exited with exitCode: 10
For more detailed output, check application tracking page:http://"hostname":8088/cluster/app/application_1491909036583_0001Then, click on links to logs of each attempt.
Diagnostics: Exception from container-launch.
Container id: container_1491909036583_0001_02_000001
Exit code: 10
Stack trace: ExitCodeException exitCode=10:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
at org.apache.hadoop.util.Shell.run(Shell.java:479)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
****--- Container Logs****
2017-04-11 07:13:30 INFO ApplicationMaster:47 - Registered signal handlers for [TERM, HUP, INT]
2017-04-11 07:13:31 INFO ApplicationMaster:59 - ApplicationAttemptId: appattempt_1491909036583_0001_000001
2017-04-11 07:13:32 INFO SecurityManager:59 - Changing view acls to: root,xxxx
2017-04-11 07:13:32 INFO SecurityManager:59 - Changing modify acls to: root,xxxx
2017-04-11 07:13:32 INFO SecurityManager:59 - SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root, xxxx); users with modify permissions: Set(root, xxxx)
2017-04-11 07:13:32 INFO Slf4jLogger:80 - Slf4jLogger started
2017-04-11 07:13:32 INFO Remoting:74 - Starting remoting
2017-04-11 07:13:32 INFO Remoting:74 - Remoting started; listening on addresses :[akka.tcp://sparkYarnAM@xxx.xx.xx.xxx:45446]
2017-04-11 07:13:32 INFO Remoting:74 - Remoting now listens on addresses: [akka.tcp://sparkYarnAM@xxx.xx.xx.xxx:45446]
2017-04-11 07:13:32 INFO Utils:59 - Successfully started service 'sparkYarnAM' on port 45446.
2017-04-11 07:13:32 INFO ApplicationMaster:59 - Waiting for Spark driver to be reachable.
2017-04-11 07:13:32 INFO ApplicationMaster:59 - Driver now available: xxx.xx.xx.xxx:47503
2017-04-11 07:15:32 ERROR ApplicationMaster:96 - Uncaught exception:
org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [120 seconds]. This timeout is controlled by spark.rpc.lookupTimeout
at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcEnv.scala:214)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcEnv.scala:229)
at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcEnv.scala:225)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcEnv.scala:242)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:98)
at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:116)
at org.apache.spark.deploy.yarn.ApplicationMaster.runAMEndpoint(ApplicationMaster.scala:279)
at org.apache.spark.deploy.yarn.ApplicationMaster.waitForSparkDriver(ApplicationMaster.scala:473)
at org.apache.spark.deploy.yarn.ApplicationMaster.runExecutorLauncher(ApplicationMaster.scala:315)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:157)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$main$1.apply$mcV$sp(ApplicationMaster.scala:625)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:69)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:68)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:68)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:623)
at org.apache.spark.deploy.yarn.ExecutorLauncher$.main(ApplicationMaster.scala:646)
at org.apache.spark.deploy.yarn.ExecutorLauncher.main(ApplicationMaster.scala)
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [120 seconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107)
at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
at scala.concurrent.Await$.result(package.scala:107)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcEnv.scala:241)
... 16 more
2017-04-11 07:15:32 INFO ApplicationMaster:59 - Final app status: FAILED, exitCode: 10, (reason: Uncaught exception: org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [120 seconds]. This timeout is controlled by spark.rpc.lookupTimeout)
2017-04-11 07:15:32 INFO ShutdownHookManager:59 - Shutdown hook called
--Yarn Node Manager logs at the time of failure
2017-04-11 07:15:18,728 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Memory usage of ProcessTree 30015 for container-id container_1491909036583_0001_01_000001: 201.6 MB of 1 GB physical memory used; 2.3 GB of 4 GB virtual memory used
2017-04-11 07:15:21,735 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Memory usage of ProcessTree 30015 for container-id container_1491909036583_0001_01_000001: 201.6 MB of 1 GB physical memory used; 2.3 GB of 4 GB virtual memory used
2017-04-11 07:15:24,742 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Memory usage of ProcessTree 30015 for container-id container_1491909036583_0001_01_000001: 201.6 MB of 1 GB physical memory used; 2.3 GB of 4 GB virtual memory used
2017-04-11 07:15:27,749 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Memory usage of ProcessTree 30015 for container-id container_1491909036583_0001_01_000001: 201.6 MB of 1 GB physical memory used; 2.3 GB of 4 GB virtual memory used
2017-04-11 07:15:30,756 INFO org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Memory usage of ProcessTree 30015 for container-id container_1491909036583_0001_01_000001: 201.6 MB of 1 GB physical memory used; 2.3 GB of 4 GB virtual memory used
2017-04-11 07:15:33,018 WARN org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor: Exit code from container container_1491909036583_0001_01_000001 is : 10
2017-04-11 07:15:33,019 WARN org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor: Exception from container-launch with container ID: container_1491909036583_0001_01_000001 and exit code: 10
ExitCodeException exitCode=10:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:582)
-- SparkCOntext parameters
<!-- Spark Configuration -->
<bean id="sparkInfo" class="SparkInfo">
<property name="appName" value="framework"></property>
<property name="master" value="yarn-client"></property>
<property name="dynamicAllocation" value="false"></property>
<property name="executorInstances" value="2"></property>
<property name="executorMemory" value="1g"></property>
<property name="executorCores" value="4"></property>
<property name="executorCoresMax" value="2"></property>
<property name="taskCpus" value="4"></property>
<property name="executorClassPath" value="/usr/hadoop/hadoop-2.7.3/share/hadoop/yarn/lib/*"></property>
<property name="yarnJar"
value="${framework.hdfsURI}/app/spark-1.5.0-bin-hadoop2.6/lib/spark-assembly-1.5.0-hadoop2.6.0.jar"></property>
<property name="yarnQueue" value="default"></property>
<property name="memoryFraction" value="0.4"></property>
</bean>
sparks.default.conf
spark.driver.memory 1g
spark.executor.extraJavaOptions -XX:ReservedCodeCacheSize=100M -XX:MaxMetaspaceSize=256m -XX:CompressedClassSpaceSize=256m
spark.rpc.lookupTimeout 600s
yarn-site.xml
<!-- Site specific YARN configuration properties -->
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>1024</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>3096</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>3096</value>
</property>
<property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>4</value>
</property>
</configuration>
回答1:
You can keep increasing spark.network.timeout until you stop seeing the problem , as mentioned by himanshuIIITian in comment.
When spark is under heavy workload, timeout exception can occur. If you have low executor memory then GC may keep system very busy which increases workload. Look into the logs if there is Out Of Memory error. Please enable -XX:+PrintGCDetails -XX:+PrintGCTimeStamps in spark.executor.extraJavaOptions and look into logs if full GC is invoked a number of times before a task completes. If that is the case then increase your executorMemory . That should hopefully solve your problem.
回答2:
for me it is the firewall settings in spark cluster which prevents the executors from connecting correctly, the problem I couldn't figure that promptly as spark UI shows all workers connected to the master, but there are other connections blocked by my firewall. After setting the following ports and allowing them in the firewall problem solved. ( please note that Spark use a random port for these settings by default)
spark.driver.port
spark.blockManager.port
来源：https://stackoverflow.com/questions/43346855/org-apache-spark-rpc-rpctimeoutexception-futures-timed-out-after-120-seconds