Kafka：ZK+Kafka+Spark Streaming集群环境搭建（六）针对spark2.2.1以yarn方式启动spark-shell抛出异常：ERROR cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Sending RequestExecutors(0,0,Map(),Set()) to AM was unsuccessful

Spark以yarn方式运行时抛出异常：

[spark@master bin]$ cd /opt/spark-2.2.1-bin-hadoop2.7/bin
[spark@master bin]$ ./spark-shell --master yarn-client
Warning: Master yarn-client is deprecated since 2.0. Please use master "yarn" with specified deploy mode instead.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
18/06/30 23:13:49 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/06/30 23:13:51 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
Spark context Web UI available at http://192.168.0.120:4040
Spark context available as 'sc' (master = yarn, app id = application_1530369937777_0003).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.2.1
      /_/
         
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_171)
Type in expressions to have them evaluated.
Type :help for more information.

scala> 18/06/30 23:14:42 ERROR cluster.YarnClientSchedulerBackend: Yarn application has already exited with state FAILED!
18/06/30 23:14:42 ERROR client.TransportClient: Failed to send RPC 6363337827096152590 to /192.168.0.121:42926: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
        at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)
18/06/30 23:14:42 ERROR cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Sending RequestExecutors(0,0,Map(),Set()) to AM was unsuccessful
java.io.IOException: Failed to send RPC 6363337827096152590 to /192.168.0.121:42926: java.nio.channels.ClosedChannelException
        at org.apache.spark.network.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)
        at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)
        at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)
        at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)
        at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:122)
        at io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetFailure(AbstractChannel.java:852)
        at io.netty.channel.AbstractChannel$AbstractUnsafe.write(AbstractChannel.java:738)
        at io.netty.channel.DefaultChannelPipeline$HeadContext.write(DefaultChannelPipeline.java:1251)
        at io.netty.channel.AbstractChannelHandlerContext.invokeWrite0(AbstractChannelHandlerContext.java:733)
        at io.netty.channel.AbstractChannelHandlerContext.invokeWrite(AbstractChannelHandlerContext.java:725)
        at io.netty.channel.AbstractChannelHandlerContext.access$1900(AbstractChannelHandlerContext.java:35)
        at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.write(AbstractChannelHandlerContext.java:1062)
        at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)
        at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1051)
        at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)
        at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)
        at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
        at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
        at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
        at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)
18/06/30 23:14:42 ERROR util.Utils: Uncaught exception in thread Yarn application state monitor
org.apache.spark.SparkException: Exception thrown in awaitResult: 
        at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
        at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
        at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.requestTotalExecutors(CoarseGrainedSchedulerBackend.scala:551)
        at org.apache.spark.scheduler.cluster.YarnSchedulerBackend.stop(YarnSchedulerBackend.scala:97)
        at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.stop(YarnClientSchedulerBackend.scala:151)
        at org.apache.spark.scheduler.TaskSchedulerImpl.stop(TaskSchedulerImpl.scala:517)
        at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1670)
        at org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1928)
        at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1317)
        at org.apache.spark.SparkContext.stop(SparkContext.scala:1927)
        at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend$MonitorThread.run(YarnClientSchedulerBackend.scala:108)
Caused by: java.io.IOException: Failed to send RPC 6363337827096152590 to /192.168.0.121:42926: java.nio.channels.ClosedChannelException
        at org.apache.spark.network.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)
        at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)
        at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)
        at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)
        at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:122)
        at io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetFailure(AbstractChannel.java:852)
        at io.netty.channel.AbstractChannel$AbstractUnsafe.write(AbstractChannel.java:738)
        at io.netty.channel.DefaultChannelPipeline$HeadContext.write(DefaultChannelPipeline.java:1251)
        at io.netty.channel.AbstractChannelHandlerContext.invokeWrite0(AbstractChannelHandlerContext.java:733)
        at io.netty.channel.AbstractChannelHandlerContext.invokeWrite(AbstractChannelHandlerContext.java:725)
        at io.netty.channel.AbstractChannelHandlerContext.access$1900(AbstractChannelHandlerContext.java:35)
        at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.write(AbstractChannelHandlerContext.java:1062)
        at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)
        at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1051)
        at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)
        at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)
        at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
        at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
        at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
        at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

解决方案：

主要是给节点分配的内存少，yarn kill了spark application。
给yarn-site.xml增加配置：

<property>
    <name>yarn.nodemanager.pmem-check-enabled</name>
    <value>false</value>
</property>
<property>
    <name>yarn.nodemanager.vmem-check-enabled</name>
    <value>false</value>
    <description>Whether virtual memory limits will be enforced for containers</description>
</property>
<property>
    <name>yarn.nodemanager.vmem-pmem-ratio</name>
    <value>4</value>
    <description>Ratio between virtual memory to physical memory when setting memory limits for containers</description>
</property>

重启hadoop。然后再重新执行./spark-shell --master yarn-client即可。

问题解决过程记录：

1）在master上将hadoop,spark服务停掉

[spark@master hadoop]$ cd /opt/hadoop-2.9.0
[spark@master hadoop]$ sbin/stop-all.sh
[spark@master hadoop]$ cd /opt/spark-2.2.1-bin-hadoop2.7
[spark@master hadoop]$ sbin/stop-all.sh

2）在master上修改yarn-site.xml 

[spark@master hadoop]$ cd /opt/hadoop-2.9.0/etc/hadoop
[spark@master hadoop]$ ls
capacity-scheduler.xml  hadoop-env.cmd              hadoop-policy.xml        httpfs-signature.secret  kms-log4j.properties  mapred-env.sh               slaves                  yarn-env.sh
configuration.xsl       hadoop-env.sh               hdfs-site.xml            httpfs-site.xml          kms-site.xml          mapred-queues.xml.template  ssl-client.xml.example  yarn-site.xml
container-executor.cfg  hadoop-metrics2.properties  httpfs-env.sh            kms-acls.xml             log4j.properties      mapred-site.xml             ssl-server.xml.example
core-site.xml           hadoop-metrics.properties   httpfs-log4j.properties  kms-env.sh               mapred-env.cmd        mapred-site.xml.template    yarn-env.cmd
[spark@master hadoop]$ vi yarn-site.xml 
<?xml version="1.0"?>
<!--
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License. See accompanying LICENSE file.
-->
<configuration>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
        <value>org.apache.hadoop.mapred.ShuffleHandler</value>
    </property>
    <property>
        <name>yarn.resourcemanager.address</name>
        <value>master:8032</value>
    </property>
    <property>
        <name>yarn.resourcemanager.scheduler.address</name>
        <value>master:8030</value>
    </property>
    <property>
        <name>yarn.resourcemanager.resource-tracker.address</name>
        <value>master:8035</value>
    </property>
    <property>
        <name>yarn.resourcemanager.admin.address</name>
        <value>master:8033</value>
    </property>
    <property>
        <name>yarn.resourcemanager.webapp.address</name>
        <value>master:8088</value>
    </property>
    <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>master</value>
    </property>
    <property>
        <name>yarn.nodemanager.resource.memory-mb</name>
        <value>2048</value>
    </property>
    <property>
        <name>yarn.nodemanager.pmem-check-enabled</name>
        <value>false</value>
    </property>
    <property>
        <name>yarn.nodemanager.vmem-check-enabled</name>
        <value>false</value>
        <description>Whether virtual memory limits will be enforced for containers</description>
    </property>
    <property>
        <name>yarn.nodemanager.vmem-pmem-ratio</name>
        <value>4</value>
        <description>Ratio between virtual memory to physical memory when setting memory limits for containers</description>
    </property>
</configuration>
~                                                                                                                                                                                                           
~                                                                                                                                                                                                           
~                                                                                                                                                                                                           
"yarn-site.xml" 66L, 2285C written

3）将master上将l修改后的yarn-site.xm文件覆盖到各个slaves节点

[spark@master hadoop]$ scp -r /opt/hadoop-2.9.0/etc/hadoop/yarn-site.xml spark@slave1:/opt/hadoop-2.9.0/etc/hadoop/
yarn-site.xml                                                                                                                                                             100% 2285   577.6KB/s   00:00    
[spark@master hadoop]$ scp -r /opt/hadoop-2.9.0/etc/hadoop/yarn-site.xml spark@slave2:/opt/hadoop-2.9.0/etc/hadoop/
yarn-site.xml                                                                                                                                                             100% 2285   795.3KB/s   00:00    
[spark@master hadoop]$ scp -r /opt/hadoop-2.9.0/etc/hadoop/yarn-site.xml spark@slave3:/opt/hadoop-2.9.0/etc/hadoop/
yarn-site.xml                                                                                                                                                             100% 2285     1.5MB/s   00:00

4）重新启动hadoop,spark服务

[spark@master hadoop]$ cd /opt/hadoop-2.9.0
[spark@master hadoop]$ sbin/start-all.sh
[spark@master hadoop]$ cd /opt/spark-2.2.1-bin-hadoop2.7
[spark@master spark-2.2.1-bin-hadoop2.7]$ sbin/start-all.sh
[spark@master spark-2.2.1-bin-hadoop2.7]$ jps
5938 ResourceManager
6227 Master
5780 SecondaryNameNode
6297 Jps
5579 NameNode

5）验证spark on yarn是否正常运行

[spark@master spark-2.2.1-bin-hadoop2.7]$ cd /opt/spark-2.2.1-bin-hadoop2.7/bin
[spark@master bin]$ ./spark-shell --master yarn-client
Warning: Master yarn-client is deprecated since 2.0. Please use master "yarn" with specified deploy mode instead.
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
18/06/30 23:50:17 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/06/30 23:50:19 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
Spark context Web UI available at http://192.168.0.120:4040
Spark context available as 'sc' (master = yarn, app id = application_1530373644791_0001).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.2.1
      /_/
         
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_171)
Type in expressions to have them evaluated.
Type :help for more information.

scala> 

[spark@master bin]$ ./spark-shell --master yarn
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
18/06/30 23:51:47 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/06/30 23:51:49 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
Spark context Web UI available at http://192.168.0.120:4040
Spark context available as 'sc' (master = yarn, app id = application_1530373644791_0002).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.2.1
      /_/
         
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_171)
Type in expressions to have them evaluated.
Type :help for more information.

scala>

spark on yarn启动spark-shell后，可以在yarn管理界面看到一个Runing Application

6）继续验证：以yarn-cluster方式运行一个spark任务测试是否正常

[spark@master bin]$ cd /opt/spark-2.2.1-bin-hadoop2.7/
[spark@master spark-2.2.1-bin-hadoop2.7]$ ./bin/spark-submit \
> --class org.apache.spark.examples.SparkPi \
> --master yarn \
> /opt/spark-2.2.1-bin-hadoop2.7/examples/jars/spark-examples_2.11-2.2.1.jar \
> 10
18/07/01 00:11:10 INFO spark.SparkContext: Running Spark version 2.2.1
18/07/01 00:11:11 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/07/01 00:11:11 INFO spark.SparkContext: Submitted application: Spark Pi
18/07/01 00:11:11 INFO spark.SecurityManager: Changing view acls to: spark
18/07/01 00:11:11 INFO spark.SecurityManager: Changing modify acls to: spark
18/07/01 00:11:11 INFO spark.SecurityManager: Changing view acls groups to: 
18/07/01 00:11:11 INFO spark.SecurityManager: Changing modify acls groups to: 
18/07/01 00:11:11 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(spark); groups with view permissions: Set(); users  with modify permissions: Set(spark); groups with modify permissions: Set()
18/07/01 00:11:11 INFO util.Utils: Successfully started service 'sparkDriver' on port 41922.
18/07/01 00:11:11 INFO spark.SparkEnv: Registering MapOutputTracker
18/07/01 00:11:11 INFO spark.SparkEnv: Registering BlockManagerMaster
18/07/01 00:11:11 INFO storage.BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
18/07/01 00:11:11 INFO storage.BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
18/07/01 00:11:11 INFO storage.DiskBlockManager: Created local directory at /opt/spark-2.2.1-bin-hadoop2.7/blockmgr-121559e6-2f03-4f68-9738-faf513bca0ac
18/07/01 00:11:11 INFO memory.MemoryStore: MemoryStore started with capacity 366.3 MB
18/07/01 00:11:11 INFO spark.SparkEnv: Registering OutputCommitCoordinator
18/07/01 00:11:11 INFO util.log: Logging initialized @1288ms
18/07/01 00:11:11 INFO server.Server: jetty-9.3.z-SNAPSHOT
18/07/01 00:11:11 INFO server.Server: Started @1345ms
18/07/01 00:11:11 INFO server.AbstractConnector: Started ServerConnector@596df867{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
18/07/01 00:11:11 INFO util.Utils: Successfully started service 'SparkUI' on port 4040.
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@425357dd{/jobs,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@52eacb4b{/jobs/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@2a551a63{/jobs/job,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@ec2bf82{/jobs/job/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@6cc0bcf6{/stages,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@32f61a31{/stages/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@669253b7{/stages/stage,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@49a64d82{/stages/stage/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@66d23e4a{/stages/pool,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4d9d1b69{/stages/pool/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@251f7d26{/storage,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@52d10fb8{/storage/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@1fe8d51b{/storage/rdd,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@22680f52{/storage/rdd/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@39c11e6c{/environment,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@503d56b5{/environment/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@433ffad1{/executors,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@2575f671{/executors/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@ecf9fb3{/executors/threadDump,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@27f9e982{/executors/threadDump/json,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@37d3d232{/static,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@21680803{/,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@c8b96ec{/api,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@58a55449{/jobs/job/kill,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@6e0ff644{/stages/stage/kill,null,AVAILABLE,@Spark}
18/07/01 00:11:11 INFO ui.SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.0.120:4040
18/07/01 00:11:11 INFO spark.SparkContext: Added JAR file:/opt/spark-2.2.1-bin-hadoop2.7/examples/jars/spark-examples_2.11-2.2.1.jar at spark://192.168.0.120:41922/jars/spark-examples_2.11-2.2.1.jar with timestamp 1530375071834
18/07/01 00:11:12 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.0.120:8032
18/07/01 00:11:12 INFO yarn.Client: Requesting a new application from cluster with 3 NodeManagers
18/07/01 00:11:12 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (2048 MB per container)
18/07/01 00:11:12 INFO yarn.Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
18/07/01 00:11:12 INFO yarn.Client: Setting up container launch context for our AM
18/07/01 00:11:12 INFO yarn.Client: Setting up the launch environment for our AM container
18/07/01 00:11:12 INFO yarn.Client: Preparing resources for our AM container
18/07/01 00:11:13 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
18/07/01 00:11:14 INFO yarn.Client: Uploading resource file:/opt/spark-2.2.1-bin-hadoop2.7/spark-c4987503-2802-4e4c-b170-301856a36773/__spark_libs__7066117465738289067.zip -> hdfs://master:9000/user/spark/.sparkStaging/application_1530373644791_0003/__spark_libs__7066117465738289067.zip
18/07/01 00:11:18 INFO yarn.Client: Uploading resource file:/opt/spark-2.2.1-bin-hadoop2.7/spark-c4987503-2802-4e4c-b170-301856a36773/__spark_conf__2688610535686541958.zip -> hdfs://master:9000/user/spark/.sparkStaging/application_1530373644791_0003/__spark_conf__.zip
18/07/01 00:11:18 INFO spark.SecurityManager: Changing view acls to: spark
18/07/01 00:11:18 INFO spark.SecurityManager: Changing modify acls to: spark
18/07/01 00:11:18 INFO spark.SecurityManager: Changing view acls groups to: 
18/07/01 00:11:18 INFO spark.SecurityManager: Changing modify acls groups to: 
18/07/01 00:11:18 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(spark); groups with view permissions: Set(); users  with modify permissions: Set(spark); groups with modify permissions: Set()
18/07/01 00:11:18 INFO yarn.Client: Submitting application application_1530373644791_0003 to ResourceManager
18/07/01 00:11:18 INFO impl.YarnClientImpl: Submitted application application_1530373644791_0003
18/07/01 00:11:18 INFO cluster.SchedulerExtensionServices: Starting Yarn extension services with app application_1530373644791_0003 and attemptId None
18/07/01 00:11:19 INFO yarn.Client: Application report for application_1530373644791_0003 (state: ACCEPTED)
18/07/01 00:11:19 INFO yarn.Client: 
         client token: N/A
         diagnostics: AM container is launched, waiting for AM container to Register with RM
         ApplicationMaster host: N/A
         ApplicationMaster RPC port: -1
         queue: default
         start time: 1530375078885
         final status: UNDEFINED
         tracking URL: http://master:8088/proxy/application_1530373644791_0003/
         user: spark
18/07/01 00:11:20 INFO yarn.Client: Application report for application_1530373644791_0003 (state: ACCEPTED)
18/07/01 00:11:21 INFO yarn.Client: Application report for application_1530373644791_0003 (state: ACCEPTED)
18/07/01 00:11:22 INFO yarn.Client: Application report for application_1530373644791_0003 (state: ACCEPTED)
18/07/01 00:11:23 INFO yarn.Client: Application report for application_1530373644791_0003 (state: ACCEPTED)
18/07/01 00:11:24 INFO cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: ApplicationMaster registered as NettyRpcEndpointRef(spark-client://YarnAM)
18/07/01 00:11:24 INFO cluster.YarnClientSchedulerBackend: Add WebUI Filter. org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter, Map(PROXY_HOSTS -> master, PROXY_URI_BASES -> http://master:8088/proxy/application_1530373644791_0003), /proxy/application_1530373644791_0003
18/07/01 00:11:24 INFO ui.JettyUtils: Adding filter: org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter
18/07/01 00:11:24 INFO yarn.Client: Application report for application_1530373644791_0003 (state: RUNNING)
18/07/01 00:11:24 INFO yarn.Client: 
         client token: N/A
         diagnostics: N/A
         ApplicationMaster host: 192.168.0.121
         ApplicationMaster RPC port: 0
         queue: default
         start time: 1530375078885
         final status: UNDEFINED
         tracking URL: http://master:8088/proxy/application_1530373644791_0003/
         user: spark
18/07/01 00:11:24 INFO cluster.YarnClientSchedulerBackend: Application application_1530373644791_0003 has started running.
18/07/01 00:11:24 INFO util.Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 42209.
18/07/01 00:11:24 INFO netty.NettyBlockTransferService: Server created on 192.168.0.120:42209
18/07/01 00:11:24 INFO storage.BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
18/07/01 00:11:24 INFO storage.BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.0.120, 42209, None)
18/07/01 00:11:24 INFO storage.BlockManagerMasterEndpoint: Registering block manager 192.168.0.120:42209 with 366.3 MB RAM, BlockManagerId(driver, 192.168.0.120, 42209, None)
18/07/01 00:11:24 INFO storage.BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.0.120, 42209, None)
18/07/01 00:11:24 INFO storage.BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.0.120, 42209, None)
18/07/01 00:11:25 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@58aa1d72{/metrics/json,null,AVAILABLE,@Spark}
18/07/01 00:11:35 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Registered executor NettyRpcEndpointRef(spark-client://Executor) (192.168.0.123:59710) with ID 1
18/07/01 00:11:35 INFO storage.BlockManagerMasterEndpoint: Registering block manager slave3:34708 with 366.3 MB RAM, BlockManagerId(1, slave3, 34708, None)
18/07/01 00:11:38 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Registered executor NettyRpcEndpointRef(spark-client://Executor) (192.168.0.122:36090) with ID 2
18/07/01 00:11:38 INFO cluster.YarnClientSchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.8
18/07/01 00:11:38 INFO storage.BlockManagerMasterEndpoint: Registering block manager slave2:35749 with 366.3 MB RAM, BlockManagerId(2, slave2, 35749, None)
18/07/01 00:11:38 INFO spark.SparkContext: Starting job: reduce at SparkPi.scala:38
18/07/01 00:11:38 INFO scheduler.DAGScheduler: Got job 0 (reduce at SparkPi.scala:38) with 10 output partitions
18/07/01 00:11:38 INFO scheduler.DAGScheduler: Final stage: ResultStage 0 (reduce at SparkPi.scala:38)
18/07/01 00:11:38 INFO scheduler.DAGScheduler: Parents of final stage: List()
18/07/01 00:11:38 INFO scheduler.DAGScheduler: Missing parents: List()
18/07/01 00:11:38 INFO scheduler.DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:34), which has no missing parents
18/07/01 00:11:38 INFO memory.MemoryStore: Block broadcast_0 stored as values in memory (estimated size 1832.0 B, free 366.3 MB)
18/07/01 00:11:38 INFO memory.MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 1172.0 B, free 366.3 MB)
18/07/01 00:11:38 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.0.120:42209 (size: 1172.0 B, free: 366.3 MB)
18/07/01 00:11:38 INFO spark.SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006
18/07/01 00:11:38 INFO scheduler.DAGScheduler: Submitting 10 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:34) (first 15 tasks are for partitions Vector(0, 1, 2, 3, 4, 5, 6, 7, 8, 9))
18/07/01 00:11:38 INFO cluster.YarnScheduler: Adding task set 0.0 with 10 tasks
18/07/01 00:11:38 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, slave2, executor 2, partition 0, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:38 INFO scheduler.TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, slave3, executor 1, partition 1, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:38 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on slave3:34708 (size: 1172.0 B, free: 366.3 MB)
18/07/01 00:11:39 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on slave2:35749 (size: 1172.0 B, free: 366.3 MB)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 2.0 in stage 0.0 (TID 2, slave3, executor 1, partition 2, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 531 ms on slave3 (executor 1) (1/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 3.0 in stage 0.0 (TID 3, slave3, executor 1, partition 3, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 2.0 in stage 0.0 (TID 2) in 64 ms on slave3 (executor 1) (2/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 4.0 in stage 0.0 (TID 4, slave3, executor 1, partition 4, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 3.0 in stage 0.0 (TID 3) in 44 ms on slave3 (executor 1) (3/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 5.0 in stage 0.0 (TID 5, slave3, executor 1, partition 5, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 4.0 in stage 0.0 (TID 4) in 62 ms on slave3 (executor 1) (4/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 6.0 in stage 0.0 (TID 6, slave2, executor 2, partition 6, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 731 ms on slave2 (executor 2) (5/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 7.0 in stage 0.0 (TID 7, slave3, executor 1, partition 7, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 5.0 in stage 0.0 (TID 5) in 58 ms on slave3 (executor 1) (6/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 8.0 in stage 0.0 (TID 8, slave2, executor 2, partition 8, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 6.0 in stage 0.0 (TID 6) in 49 ms on slave2 (executor 2) (7/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Starting task 9.0 in stage 0.0 (TID 9, slave2, executor 2, partition 9, PROCESS_LOCAL, 4836 bytes)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 7.0 in stage 0.0 (TID 7) in 70 ms on slave3 (executor 1) (8/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 8.0 in stage 0.0 (TID 8) in 51 ms on slave2 (executor 2) (9/10)
18/07/01 00:11:39 INFO scheduler.TaskSetManager: Finished task 9.0 in stage 0.0 (TID 9) in 44 ms on slave2 (executor 2) (10/10)
18/07/01 00:11:39 INFO cluster.YarnScheduler: Removed TaskSet 0.0, whose tasks have all completed, from pool 
18/07/01 00:11:39 INFO scheduler.DAGScheduler: ResultStage 0 (reduce at SparkPi.scala:38) finished in 0.857 s
18/07/01 00:11:39 INFO scheduler.DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 1.104223 s
Pi is roughly 3.143763143763144
18/07/01 00:11:39 INFO server.AbstractConnector: Stopped Spark@596df867{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
18/07/01 00:11:39 INFO ui.SparkUI: Stopped Spark web UI at http://192.168.0.120:4040
18/07/01 00:11:39 INFO cluster.YarnClientSchedulerBackend: Interrupting monitor thread
18/07/01 00:11:39 INFO cluster.YarnClientSchedulerBackend: Shutting down all executors
18/07/01 00:11:39 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Asking each executor to shut down
18/07/01 00:11:39 INFO cluster.SchedulerExtensionServices: Stopping SchedulerExtensionServices
(serviceOption=None,
 services=List(),
 started=false)
18/07/01 00:11:39 INFO cluster.YarnClientSchedulerBackend: Stopped
18/07/01 00:11:39 INFO spark.MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
18/07/01 00:11:39 INFO memory.MemoryStore: MemoryStore cleared
18/07/01 00:11:39 INFO storage.BlockManager: BlockManager stopped
18/07/01 00:11:39 INFO storage.BlockManagerMaster: BlockManagerMaster stopped
18/07/01 00:11:39 INFO scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
18/07/01 00:11:39 INFO spark.SparkContext: Successfully stopped SparkContext
18/07/01 00:11:39 INFO util.ShutdownHookManager: Shutdown hook called
18/07/01 00:11:39 INFO util.ShutdownHookManager: Deleting directory /opt/spark-2.2.1-bin-hadoop2.7/spark-c4987503-2802-4e4c-b170-301856a36773

通过yarn resource manager界面查看任务运行状态：

 

参考《https://blog.csdn.net/rongyongfeikai2/article/details/69361333》

《https://blog.csdn.net/chengyuqiang/article/details/77864246》

posted @ 2018-06-30 16:07  cctext  阅读(5250)  评论(0)  编辑  收藏  举报