在Hadoop Yarn 运行 pyspark 的一些问题

hduser@master:~$ pyspark --master local[4]
Python 2.7.12 (default, Dec  4 2017, 14:50:18) 
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
18/08/16 09:13:28 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.3.1
      /_/

Using Python version 2.7.12 (default, Dec  4 2017 14:50:18)
SparkSession available as 'spark'.
>>> sc.master
u'local[4]'
>>> textFile=sc.textFile("file:/usr/local/spark/README.md")
>>> textFile.count()
103                                                                             
>>> textFile =sc.textFile("hdfs://master:9000/user/hduser/wordcount/input/LICENSE.txt")
>>> textFile.count()
1594
>>> exit()
hduser@master:~$ HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop pyspark --master yarn --deploy-mode client
Python 2.7.12 (default, Dec  4 2017, 14:50:18) 
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
18/08/16 09:16:05 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
18/08/16 09:16:10 WARN Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.3.1
      /_/

Using Python version 2.7.12 (default, Dec  4 2017 14:50:18)
SparkSession available as 'spark'.
>>> 18/08/16 09:16:46 ERROR YarnClientSchedulerBackend: Yarn application has already exited with state FINISHED!
18/08/16 09:16:47 ERROR TransportClient: Failed to send RPC 7397841312553810412 to /192.168.0.102:39808: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
	at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)
18/08/16 09:16:47 ERROR YarnSchedulerBackend$YarnSchedulerEndpoint: Sending RequestExecutors(0,0,Map(),Set()) to AM was unsuccessful
java.io.IOException: Failed to send RPC 7397841312553810412 to /192.168.0.102:39808: 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.access$000(DefaultPromise.java:34)
	at io.netty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:431)
	at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:163)
	at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:403)
	at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:463)
	at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:858)
	at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
	at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
	at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)
18/08/16 09:16:47 ERROR Utils: Uncaught exception in thread Yarn application state monitor
org.apache.spark.SparkException: Exception thrown in awaitResult: 
	at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
	at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
	at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.requestTotalExecutors(CoarseGrainedSchedulerBackend.scala:567)
	at org.apache.spark.scheduler.cluster.YarnSchedulerBackend.stop(YarnSchedulerBackend.scala:95)
	at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.stop(YarnClientSchedulerBackend.scala:155)
	at org.apache.spark.scheduler.TaskSchedulerImpl.stop(TaskSchedulerImpl.scala:508)
	at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1755)
	at org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1931)
	at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1360)
	at org.apache.spark.SparkContext.stop(SparkContext.scala:1930)
	at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend$MonitorThread.run(YarnClientSchedulerBackend.scala:112)
Caused by: java.io.IOException: Failed to send RPC 7397841312553810412 to /192.168.0.102:39808: java.nio.channels.ClosedChannelException
	at org.apache.spark.network.client.TransportClient.lambda$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.access$000(DefaultPromise.java:34)
	at io.netty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:431)
	at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:163)
	at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:403)
	at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:463)
	at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:858)
	at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
	at java.lang.Thread.run(Thread.java:748)
Caused by: java.nio.channels.ClosedChannelException
	at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

>>> sc.master
u'yarn'
>>> textFile = sc.textFile("hdfs://master:9000/user/hduser/wordcount/input/LICENSE.txt")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/spark/python/pyspark/context.py", line 546, in textFile
    minPartitions = minPartitions or min(self.defaultParallelism, 2)
  File "/usr/local/spark/python/pyspark/context.py", line 400, in defaultParallelism
    return self._jsc.sc().defaultParallelism()
  File "/usr/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
  File "/usr/local/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/usr/local/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o30.defaultParallelism.
: java.lang.IllegalStateException: Cannot call methods on a stopped SparkContext.
This stopped SparkContext was created at:

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
java.lang.reflect.Constructor.newInstance(Constructor.java:423)
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
py4j.Gateway.invoke(Gateway.java:238)
py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
py4j.GatewayConnection.run(GatewayConnection.java:238)
java.lang.Thread.run(Thread.java:748)

The currently active SparkContext was created at:

(No active SparkContext.)
         
	at org.apache.spark.SparkContext.assertNotStopped(SparkContext.scala:99)
	at org.apache.spark.SparkContext.defaultParallelism(SparkContext.scala:2332)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:282)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.GatewayConnection.run(GatewayConnection.java:238)
	at java.lang.Thread.run(Thread.java:748)

>>> textFile.count()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'textFile' is not defined
>>> 

　　在本地运行pyspark程序查询没问题，但在Hadoop YARN 运行pyspark出现上述问题，希望有关大神看到，指点一下迷津。十分感谢~~~

下面附上我的yarn-site.xml设置

<?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>

<!-- Site specific YARN configuration properties -->
<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.resource-tracker.address</name> <value>master:8025</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name> <value>master:8030</value>
</property>
<property>
<name>yarn.resourcemanager.address</name> <value>master:8050</value>
</property>

<property>
        <name>yarn.nodemanager.vmem-check-enabled</name>
        <value>false</value>
</property>
 

 
</configuration>