尽管有资源分配，yarn 应用程序已被接受但未被接受 运行 cloudera
yarn application accepted but not running cloudera despite resource allocation
我正在使用 Cloudera quickstart VM 5.13.0.0 在 yarn-client 模式下 运行 Spark 应用程序。我已经为我的 Cloudera VM 分配了 10GB 和 3 个内核。当我提交申请时，申请已被接受，但从未进入 运行。当我尝试使用 yarn logs -applicationId 查找日志时，我什么也没看到。完全空白。
我已在以下位置查找过此问题：
我实际上已经修改了这些链接认为有问题的所有配置。我仍然没有我的问题的答案，从表面上看，它看起来像上面链接中的问题。以下是我的 cloudera 集群的配置参数：
mapreduce.map.memory.mb 128M
mapreduce.reduce.memory.mb 128M
mapreduce.job.heap.memory-mb.ratio 0.8
yarn.nodemanager.resource.memory-mb 1900M
yarn.nodemanager.resource.percentage-physical-cpu-limit 100
yarn.nodemanager.resource.cpu-vcores 1
yarn.scheduler.minimum-allocation-mb 1M
yarn.scheduler.increment-allocation-mb 100M
yarn.scheduler.maximum-allocation-mb 1600M
yarn.scheduler.minimum-allocation-vcores 1
yarn.scheduler.increment-allocation-vcores 1
yarn.scheduler.maximum-allocation-vcores 2
yarn.scheduler.fair.continuous-scheduling-enabled unchecked
mapreduce.am.max-attempts 1
yarn.resourcemanager.am.max-retries, yarn.resourcemanager.am.max-attempts 1
yarn.app.mapreduce.am.resource.mb 1G
yarn.app.mapreduce.am.resource.cpu-vcores 1
ApplicationMaster Java Maximum Heap Size 512M
yarn.resourcemanager.scheduler.class org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler
yarn.scheduler.fair.user-as-default-queue unchecked
yarn.scheduler.fair.preemption unchecked
yarn.scheduler.fair.preemption.cluster-utilization-threshold 0.8
yarn.scheduler.fair.sizebasedweight unchecked
Fair Scheduler Allocations (deployed) {"defaultFairSharePreemptionThreshold":null,"defaultFairSharePreemptionTimeout":null,"defaultMinSharePreemptionTimeout":null,"defaultQueueSchedulingPolicy":"drf","queueMaxAMShareDefault":-1.0,"queueMaxAppsDefault":null,"queuePlacementRules":[{"create":true,"name":"specified","queue":null,"rules":null},{"create":null,"name":"nestedUserQueue","queue":null,"rules":[{"create":true,"name":"default","queue":"users","rules":null}]},{"create":null,"name":"default","queue":null,"rules":null}],"queues":[{"aclAdministerApps":null,"aclSubmitApps":null,"allowPreemptionFrom":null,"fairSharePreemptionThreshold":null,"fairSharePreemptionTimeout":null,"minSharePreemptionTimeout":null,"name":"root","queues":[{"aclAdministerApps":null,"aclSubmitApps":null,"allowPreemptionFrom":null,"fairSharePreemptionThreshold":null,"fairSharePreemptionTimeout":null,"minSharePreemptionTimeout":null,"name":"default","queues":[],"schedulablePropertiesList":[{"impalaDefaultQueryMemLimit":null,"impalaDefaultQueryOptions":null,"impalaMaxMemory":null,"impalaMaxQueuedQueries":null,"impalaMaxRunningQueries":null,"impalaQueueTimeout":null,"maxAMShare":-1.0,"maxChildResources":null,"maxResources":null,"maxRunningApps":null,"minResources":null,"scheduleName":"default","weight":1.0}],"schedulingPolicy":"drf","type":null},{"aclAdministerApps":null,"aclSubmitApps":null,"allowPreemptionFrom":null,"fairSharePreemptionThreshold":null,"fairSharePreemptionTimeout":null,"minSharePreemptionTimeout":null,"name":"users","queues":[],"schedulablePropertiesList":[{"impalaDefaultQueryMemLimit":null,"impalaDefaultQueryOptions":null,"impalaMaxMemory":null,"impalaMaxQueuedQueries":null,"impalaMaxRunningQueries":null,"impalaQueueTimeout":null,"maxAMShare":-1.0,"maxChildResources":null,"maxResources":null,"maxRunningApps":null,"minResources":null,"scheduleName":"default","weight":1.0}],"schedulingPolicy":"drf","type":"parent"}],"schedulablePropertiesList":[{"impalaDefaultQueryMemLimit":null,"impalaDefaultQueryOptions":null,"impalaMaxMemory":null,"impalaMaxQueuedQueries":null,"impalaMaxRunningQueries":null,"impalaQueueTimeout":null,"maxAMShare":null,"maxChildResources":null,"maxResources":null,"maxRunningApps":null,"minResources":null,"scheduleName":"default","weight":1.0}],"schedulingPolicy":"drf","type":null}],"userMaxAppsDefault":1,"users":[]}
这是当应用程序仍处于已接受状态时队列描述的样子：
同样，这里是Yarn RM的记录UI（注意资源分配（memory/cpu）和运行容器显示1个容器运行宁):
这是申请摘要：
以下是应用程序日志（空）：
最后，这是驱动程序看到的内容：
enter code here19/12/26 00:16:42 INFO Client:
client token: N/A
diagnostics: Application application_1577297544619_0002 failed 1 times due to AM Container for appattempt_1577297544619_0002_000001 exited with exitCode: 10
For more detailed output, check application tracking page:http://quickstart.cloudera:8088/proxy/application_1577297544619_0002/Then, click on links to logs of each attempt.
Diagnostics: Exception from container-launch.
Container id: container_1577297544619_0002_01_000001
Exit code: 10
Stack trace: ExitCodeException exitCode=10:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:604)
at org.apache.hadoop.util.Shell.run(Shell.java:507)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:789)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:213)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Container exited with a non-zero exit code 10
Failing this attempt. Failing the application.
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: root.default
start time: 1577299469533
final status: FAILED
tracking URL: http://quickstart.cloudera:8088/cluster/app/application_1577297544619_0002
user: shepanch
19/12/26 00:16:42 ERROR SparkContext: Error initializing SparkContext.
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:85)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:165)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:512)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2511)
at org.apache.spark.sql.SparkSession$Builder$$anonfun.apply(SparkSession.scala:909)
at org.apache.spark.sql.SparkSession$Builder$$anonfun.apply(SparkSession.scala:901)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901)
at cloudera.jobs.ClouderaSampleJob$.delayedEndpoint$cloudera$jobs$ClouderaSampleJob(ClouderaSampleJob.scala:17)
at cloudera.jobs.ClouderaSampleJob$delayedInit$body.apply(ClouderaSampleJob.scala:6)
at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main.apply(App.scala:76)
at scala.App$$anonfun$main.apply(App.scala:76)
at scala.collection.immutable.List.foreach(List.scala:392)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.App$class.main(App.scala:76)
at cloudera.jobs.ClouderaSampleJob$.main(ClouderaSampleJob.scala:6)
at cloudera.jobs.ClouderaSampleJob.main(ClouderaSampleJob.scala)
有什么办法可以解决这个问题吗？
经过所有研究，除了我在问题中提到的链接中提到的原因之外，我发现这可能由于多种原因而发生：
- 当您在客户端（驱动程序）和集群中使用不同版本的 spark 时。一旦你确保两者捆绑了相同版本的 spark，它就可以正常运行。
- 您可能需要提及 属性 spark.driver.host。确保这里传入的 IP 可以从来宾 VM ping 通。
我正在使用 Cloudera quickstart VM 5.13.0.0 在 yarn-client 模式下 运行 Spark 应用程序。我已经为我的 Cloudera VM 分配了 10GB 和 3 个内核。当我提交申请时，申请已被接受，但从未进入 运行。当我尝试使用 yarn logs -applicationId 查找日志时，我什么也没看到。完全空白。
我已在以下位置查找过此问题：
我实际上已经修改了这些链接认为有问题的所有配置。我仍然没有我的问题的答案，从表面上看，它看起来像上面链接中的问题。以下是我的 cloudera 集群的配置参数：
mapreduce.map.memory.mb 128M
mapreduce.reduce.memory.mb 128M
mapreduce.job.heap.memory-mb.ratio 0.8
yarn.nodemanager.resource.memory-mb 1900M
yarn.nodemanager.resource.percentage-physical-cpu-limit 100
yarn.nodemanager.resource.cpu-vcores 1
yarn.scheduler.minimum-allocation-mb 1M
yarn.scheduler.increment-allocation-mb 100M
yarn.scheduler.maximum-allocation-mb 1600M
yarn.scheduler.minimum-allocation-vcores 1
yarn.scheduler.increment-allocation-vcores 1
yarn.scheduler.maximum-allocation-vcores 2
yarn.scheduler.fair.continuous-scheduling-enabled unchecked
mapreduce.am.max-attempts 1
yarn.resourcemanager.am.max-retries, yarn.resourcemanager.am.max-attempts 1
yarn.app.mapreduce.am.resource.mb 1G
yarn.app.mapreduce.am.resource.cpu-vcores 1
ApplicationMaster Java Maximum Heap Size 512M
yarn.resourcemanager.scheduler.class org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler
yarn.scheduler.fair.user-as-default-queue unchecked
yarn.scheduler.fair.preemption unchecked
yarn.scheduler.fair.preemption.cluster-utilization-threshold 0.8
yarn.scheduler.fair.sizebasedweight unchecked
Fair Scheduler Allocations (deployed) {"defaultFairSharePreemptionThreshold":null,"defaultFairSharePreemptionTimeout":null,"defaultMinSharePreemptionTimeout":null,"defaultQueueSchedulingPolicy":"drf","queueMaxAMShareDefault":-1.0,"queueMaxAppsDefault":null,"queuePlacementRules":[{"create":true,"name":"specified","queue":null,"rules":null},{"create":null,"name":"nestedUserQueue","queue":null,"rules":[{"create":true,"name":"default","queue":"users","rules":null}]},{"create":null,"name":"default","queue":null,"rules":null}],"queues":[{"aclAdministerApps":null,"aclSubmitApps":null,"allowPreemptionFrom":null,"fairSharePreemptionThreshold":null,"fairSharePreemptionTimeout":null,"minSharePreemptionTimeout":null,"name":"root","queues":[{"aclAdministerApps":null,"aclSubmitApps":null,"allowPreemptionFrom":null,"fairSharePreemptionThreshold":null,"fairSharePreemptionTimeout":null,"minSharePreemptionTimeout":null,"name":"default","queues":[],"schedulablePropertiesList":[{"impalaDefaultQueryMemLimit":null,"impalaDefaultQueryOptions":null,"impalaMaxMemory":null,"impalaMaxQueuedQueries":null,"impalaMaxRunningQueries":null,"impalaQueueTimeout":null,"maxAMShare":-1.0,"maxChildResources":null,"maxResources":null,"maxRunningApps":null,"minResources":null,"scheduleName":"default","weight":1.0}],"schedulingPolicy":"drf","type":null},{"aclAdministerApps":null,"aclSubmitApps":null,"allowPreemptionFrom":null,"fairSharePreemptionThreshold":null,"fairSharePreemptionTimeout":null,"minSharePreemptionTimeout":null,"name":"users","queues":[],"schedulablePropertiesList":[{"impalaDefaultQueryMemLimit":null,"impalaDefaultQueryOptions":null,"impalaMaxMemory":null,"impalaMaxQueuedQueries":null,"impalaMaxRunningQueries":null,"impalaQueueTimeout":null,"maxAMShare":-1.0,"maxChildResources":null,"maxResources":null,"maxRunningApps":null,"minResources":null,"scheduleName":"default","weight":1.0}],"schedulingPolicy":"drf","type":"parent"}],"schedulablePropertiesList":[{"impalaDefaultQueryMemLimit":null,"impalaDefaultQueryOptions":null,"impalaMaxMemory":null,"impalaMaxQueuedQueries":null,"impalaMaxRunningQueries":null,"impalaQueueTimeout":null,"maxAMShare":null,"maxChildResources":null,"maxResources":null,"maxRunningApps":null,"minResources":null,"scheduleName":"default","weight":1.0}],"schedulingPolicy":"drf","type":null}],"userMaxAppsDefault":1,"users":[]}
这是当应用程序仍处于已接受状态时队列描述的样子：
同样，这里是Yarn RM的记录UI（注意资源分配（memory/cpu）和运行容器显示1个容器运行宁):
这是申请摘要：
以下是应用程序日志（空）：
最后，这是驱动程序看到的内容：
enter code here19/12/26 00:16:42 INFO Client:
client token: N/A
diagnostics: Application application_1577297544619_0002 failed 1 times due to AM Container for appattempt_1577297544619_0002_000001 exited with exitCode: 10
For more detailed output, check application tracking page:http://quickstart.cloudera:8088/proxy/application_1577297544619_0002/Then, click on links to logs of each attempt.
Diagnostics: Exception from container-launch.
Container id: container_1577297544619_0002_01_000001
Exit code: 10
Stack trace: ExitCodeException exitCode=10:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:604)
at org.apache.hadoop.util.Shell.run(Shell.java:507)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:789)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:213)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Container exited with a non-zero exit code 10
Failing this attempt. Failing the application.
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: root.default
start time: 1577299469533
final status: FAILED
tracking URL: http://quickstart.cloudera:8088/cluster/app/application_1577297544619_0002
user: shepanch
19/12/26 00:16:42 ERROR SparkContext: Error initializing SparkContext.
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:85)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:165)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:512)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2511)
at org.apache.spark.sql.SparkSession$Builder$$anonfun.apply(SparkSession.scala:909)
at org.apache.spark.sql.SparkSession$Builder$$anonfun.apply(SparkSession.scala:901)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:901)
at cloudera.jobs.ClouderaSampleJob$.delayedEndpoint$cloudera$jobs$ClouderaSampleJob(ClouderaSampleJob.scala:17)
at cloudera.jobs.ClouderaSampleJob$delayedInit$body.apply(ClouderaSampleJob.scala:6)
at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main.apply(App.scala:76)
at scala.App$$anonfun$main.apply(App.scala:76)
at scala.collection.immutable.List.foreach(List.scala:392)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.App$class.main(App.scala:76)
at cloudera.jobs.ClouderaSampleJob$.main(ClouderaSampleJob.scala:6)
at cloudera.jobs.ClouderaSampleJob.main(ClouderaSampleJob.scala)
有什么办法可以解决这个问题吗？
经过所有研究，除了我在问题中提到的链接中提到的原因之外，我发现这可能由于多种原因而发生：
- 当您在客户端（驱动程序）和集群中使用不同版本的 spark 时。一旦你确保两者捆绑了相同版本的 spark，它就可以正常运行。
- 您可能需要提及 属性 spark.driver.host。确保这里传入的 IP 可以从来宾 VM ping 通。