我试图运行
pyspark --master yarn
这就是：
16/08/15 10:00:12 DEBUG Client: Using the default MR application classpath: $HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*,$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*
16/08/15 10:00:12 INFO Client: Preparing resources for our AM container
16/08/15 10:00:12 DEBUG Client:
16/08/15 10:00:12 DEBUG DFSClient: /user/mispp/.sparkStaging/application_1471254869164_0006: masked=rwxr-xr-x
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp sending #8
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp got value #8
16/08/15 10:00:12 DEBUG ProtobufRpcEngine: Call: mkdirs took 14ms
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp sending #9
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp got value #9
16/08/15 10:00:12 DEBUG ProtobufRpcEngine: Call: setPermission took 10ms
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp sending #10
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp got value #10
16/08/15 10:00:12 DEBUG ProtobufRpcEngine: Call: getFileInfo took 2ms
16/08/15 10:00:12 INFO Client: Deleting staging directory hdfs://sm/user/mispp/.sparkStaging/application_1471254869164_0006
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp sending #11
16/08/15 10:00:12 DEBUG Client: IPC Client (1933573135) connection to sm/192.168.29.71:8020 from mispp got value #11
16/08/15 10:00:12 DEBUG ProtobufRpcEngine: Call: delete took 14ms
16/08/15 10:00:12 ERROR SparkContext: Error initializing SparkContext.
java.lang.NullPointerException
at scala.collection.mutable.ArrayOps$ofRef$.newBuilder$extension(ArrayOps.scala:190)
at scala.collection.mutable.ArrayOps$ofRef.newBuilder(ArrayOps.scala:186)
at scala.collection.TraversableLike$class.filterImpl(TraversableLike.scala:246)
at scala.collection.TraversableLike$class.filter(TraversableLike.scala:259)
at scala.collection.mutable.ArrayOps$ofRef.filter(ArrayOps.scala:186)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6.apply(Client.scala:484)
at org.apache.spark.deploy.yarn.Client$$anonfun$prepareLocalResources$6.apply(Client.scala:480)
at scala.collection.mutable.ArraySeq.foreach(ArraySeq.scala:74)
at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:480)
at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:834)
at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:167)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:56)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:149)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:500)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:240)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:236)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:211)
at java.lang.Thread.run(Thread.java:745)
16/08/15 10:00:12 DEBUG AbstractLifeCycle: stopping org.spark_project.jetty.server.Server@69e507eb
16/08/15 10:00:12 DEBUG Server: Graceful shutdown org.spark_project.jetty.server.Server@69e507eb by
纱-site.xml中： （最后一个属性是我在网上找到的，所以只要尝试它就可以了）
<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>sm:8025</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>sm:8030</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>sm:8050</value>
</property>
<property>
<name>yarn.application.classpath</name>
<value>/home/mispp/hadoop-2.7.2/share/hadoop/yarn</value>
</property>
</configuration>
.bashrc中：
export HADOOP_PREFIX=/home/mispp/hadoop-2.7.2
export PATH=$PATH:$HADOOP_PREFIX/bin
export HADOOP_HOME=$HADOOP_PREFIX
export HADOOP_COMMON_HOME=$HADOOP_PREFIX
export HADOOP_YARN_HOME=$HADOOP_PREFIX
export HADOOP_HDFS_HOME=$HADOOP_PREFIX
export HADOOP_MAPRED_HOME=$HADOOP_PREFIX
export HADOOP_CONF_DIR=$HADOOP_PREFIX/etc/hadoop
export YARN_CONF_DIR=$HADOOP_PREFIX/etc/hadoop
知道为什么会这样吗？ 它在一个16GB RAM的服务器上设置了3个LXD容器（主机+两个计算机）。
答案 0 :(得分：3)
给出Spark 2.0.0代码中错误的位置：
我怀疑由于spark.yarn.jars配置错误而导致错误发生。根据{{3}}的文档，我会仔细检查您的设置中此配置的值是否正确。
答案 1 :(得分：0)
我刚刚提高了@tinfoiled的答案，但我想在这里评论一下spark.yarn.jars（它以's'结尾）属性的语法，因为我花了很长时间搞清楚。
正确的语法（哪个OP已经知道）是 -
spark.yarn.jars=hdfs://xxx:9000/user/spark/share/lib/*.jar
实际上我最终没有放入* .jar，导致“无法加载ApplicationMaster”。我尝试了各种组合，但它没有用。事实上，我在Property spark.yarn.jars - how to deal with it?
上针对同一问题在SOF上发布了一个问题我甚至不确定我正在做的事情是否正确，但OP的问题和@tinfoiled的答案给了我一些信心，我终于能够利用这个属性了。