Question

在纱线中提交火花工作罐时，我遇到了一个问题。当我用 - master yarn-client

提交它时，它运作良好并给我预期的结果

命令如下;

./ spark-submit --class main.MainClass --master yarn-client --driver-memory 4g --executor-memory 4g --num-executors 4 --executor-cores 2 job.jar另一选项

但是当提交到群集模式时，同样不起作用;命令如下;

./ spark-submit --class main.MainClass --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 4g --num-executors 4 --executor-cores 2 job.jar其他选项“

我的yarn-site.xml如下;

 <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>

我的纱线stderr日志是

        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://YarnAM@50.31.66.56:50465)
    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：将视图更改为：root 17/03/23 03:30:40 INFO spark.SecurityManager：将修改修改为：ro

但是在我的火花作业没有运行之后，你可以看到这里没有显示任何错误。问题背后的任何想法？

Answer 1

也许，你的奴隶节点不起作用。您应该在命令下面检查您的节点，

sudo -u yarn yarn node -list

如果找不到所有节点，则应修复节点设置。例如，selinux off（检查getenforce）和每个节点＆＃39; yarn-site.xml和core-site.xml。

Spark工作与纱线客户端正常工作，但根本不适用于纱线集群

1 个答案: