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我们有一个运行在AWS Elastic MapReduce（EMR）和Spark 1.6.1中的Hadoop集群。没有任何问题在群集主机上提交并提交Spark作业，但我们希望能够从另一个独立的EC2实例提交它们。从EMR集群主节点使用spark-submission外部
其他“外部”EC2实例具有安全组设置，以允许所有来往于EMR实例主节点的TCP流量和来自其实例的TCP流量。它具有从Apache网站直接下载的Spark二进制安装。
复制了的/ etc/Hadoop的/ conf文件夹从主到这个实例，并相应设置$ HADOOP_CONF_DIR，当试图提交的SparkPi例子，我碰到以下权限问题：
$ /usr/local/spark/bin/spark-submit --master yarn --deploy-mode client --class org.apache.spark.examples.SparkPi /usr/local/spark/lib/spark-examples-1.6.1-hadoop2.6.0.jar
16/06/22 13:58:52 INFO spark.SparkContext: Running Spark version 1.6.1
16/06/22 13:58:52 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/06/22 13:58:52 INFO spark.SecurityManager: Changing view acls to: jungd
16/06/22 13:58:52 INFO spark.SecurityManager: Changing modify acls to: jungd
16/06/22 13:58:52 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(jungd); users with modify permissions: Set(jungd)
16/06/22 13:58:52 INFO util.Utils: Successfully started service 'sparkDriver' on port 34757.
16/06/22 13:58:52 INFO slf4j.Slf4jLogger: Slf4jLogger started
16/06/22 13:58:52 INFO Remoting: Starting remoting
16/06/22 13:58:53 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://[email protected]:39241]
16/06/22 13:58:53 INFO util.Utils: Successfully started service 'sparkDriverActorSystem' on port 39241.
16/06/22 13:58:53 INFO spark.SparkEnv: Registering MapOutputTracker
16/06/22 13:58:53 INFO spark.SparkEnv: Registering BlockManagerMaster
16/06/22 13:58:53 INFO storage.DiskBlockManager: Created local directory at /tmp/blockmgr-300d738e-d7e4-4ae9-9cfe-4e257a05d456
16/06/22 13:58:53 INFO storage.MemoryStore: MemoryStore started with capacity 511.1 MB
16/06/22 13:58:53 INFO spark.SparkEnv: Registering OutputCommitCoordinator
16/06/22 13:58:53 INFO server.Server: jetty-8.y.z-SNAPSHOT
16/06/22 13:58:53 INFO server.AbstractConnector: Started [email protected]:4040
16/06/22 13:58:53 INFO util.Utils: Successfully started service 'SparkUI' on port 4040.
16/06/22 13:58:53 INFO ui.SparkUI: Started SparkUI at http://172.31.61.189:4040
16/06/22 13:58:53 INFO spark.HttpFileServer: HTTP File server directory is /tmp/spark-5e332986-ae2a-4bde-9ae4-edb4fac5e1d7/httpd-e475fd1b-c5c8-4f31-9699-be89fff4a69c
16/06/22 13:58:53 INFO spark.HttpServer: Starting HTTP Server
16/06/22 13:58:53 INFO server.Server: jetty-8.y.z-SNAPSHOT
16/06/22 13:58:53 INFO server.AbstractConnector: Started [email protected]:43525
16/06/22 13:58:53 INFO util.Utils: Successfully started service 'HTTP file server' on port 43525.
16/06/22 13:58:53 INFO spark.SparkContext: Added JAR file:/usr/local/spark/lib/spark-examples-1.6.1-hadoop2.6.0.jar at http://172.31.61.189:43525/jars/spark-examples-1.6.1-hadoop2.6.0.jar with timestamp 1466603933454
16/06/22 13:58:53 INFO client.RMProxy: Connecting to ResourceManager at ip-172-31-60-166.ec2.internal/172.31.60.166:8032
16/06/22 13:58:53 INFO yarn.Client: Requesting a new application from cluster with 2 NodeManagers
16/06/22 13:58:53 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (11520 MB per container)
16/06/22 13:58:53 INFO yarn.Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
16/06/22 13:58:53 INFO yarn.Client: Setting up container launch context for our AM
16/06/22 13:58:53 INFO yarn.Client: Setting up the launch environment for our AM container
16/06/22 13:58:53 INFO yarn.Client: Preparing resources for our AM container
16/06/22 13:58:54 ERROR spark.SparkContext: Error initializing SparkContext.
org.apache.hadoop.security.AccessControlException: Permission denied: user=jungd, access=WRITE, inode="/user/jungd/.sparkStaging/application_1466437015320_0014":hdfs:hadoop:drwxr-xr-x
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:319)
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:292)
at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:213)
它如果使用集群部署模式进行提交，则不会有任何区别。有问题的用户是在外部EC2实例（我们有多个开发人员帐户）上的本地用户，该用户在群集的主节点或从节点上不存在（甚至在本地，用户主目录位于/ home，而不是/用户）。
我不知道发生了什么。任何帮助不胜感激。
更新：如果我创建本地“hadoop”用户并以该用户的身份运行spark-submit或pyspark，它确实会按预期工作，但这不是我们想要的。 – DavidJ