apache-spark - org.apache.spark.rpc.RpcTimeoutException : Futures timed out after [120 seconds]. 此超时由 spark.rpc.lookupTimeout 控制

Question

在向 YARN 提交 Spark 应用程序时，出现关于容器的以下错误。 HADOOP(2.7.3)/SPARK(2.1)环境在单节点集群中运行伪分布式模式。该应用程序在本地模型中运行时完美运行，但尝试使用 YARN 作为 RM 在集群模式下检查其正确性并遇到一些障碍。这个世界的新手因此寻求帮助。

--- 应用日志

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)

****--- 容器日志****

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 失败时的日志

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 参数

<!-- 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 站点.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>

Answer 1

您可以继续增加spark.network.timeout直到你不再看到问题，正如himanshuIIITian在评论中提到的那样。
spark工作量大时，会出现超时异常。如果您的执行程序内存不足，那么 GC 可能会使系统非常繁忙，从而增加工作量。如果出现内存不足错误，请查看日志。请启用 -XX:+PrintGCDetails -XX:+PrintGCTimeStamps在 spark.executor.extraJavaOptions如果在任务完成之前多次调用 full GC，请查看日志。如果是这种情况，请增加您的 executorMemory .这应该有望解决您的问题。