Rework from pull request. Removed --user option from Spark on Yarn Client, made the user of JAVA_HOME environment

variable conditional on if its set, and created addCredentials in each of the SparkHadoopUtil classes
to only add the credentials when the profile is hadoop2-yarn.

10 files changed, 37 insertions, 37 deletions

diff --git a/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala b/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala
index a0fb4fe25d..f1c86de4cc 100644
--- a/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala
+++ b/core/src/hadoop1/scala/spark/deploy/SparkHadoopUtil.scala
@@ -1,5 +1,6 @@
 package spark.deploy
 import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.mapred.JobConf
 
 
 /**
@@ -20,4 +21,7 @@ object SparkHadoopUtil {
 
   // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems
   def newConfiguration(): Configuration = new Configuration()
+
+  // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster
+  def addCredentials(conf: JobConf) {}
 }
diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala b/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala
index b96c047e10..301a57fffa 100644
--- a/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala
+++ b/core/src/hadoop2-yarn/scala/spark/deploy/SparkHadoopUtil.scala
@@ -1,6 +1,7 @@
 package spark.deploy
 
 import collection.mutable.HashMap
+import org.apache.hadoop.mapred.JobConf
 import org.apache.hadoop.security.UserGroupInformation
 import org.apache.hadoop.yarn.conf.YarnConfiguration
 import org.apache.hadoop.conf.Configuration
@@ -49,4 +50,10 @@ object SparkHadoopUtil {
   // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems
   // Always create a new config, dont reuse yarnConf.
   def newConfiguration(): Configuration = new YarnConfiguration(new Configuration())
+
+  // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster
+  def addCredentials(conf: JobConf) {
+    val jobCreds = conf.getCredentials();
+    jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
+  }
 }
diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala
index f20cc31c7c..514c17f241 100644
--- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala
+++ b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/Client.scala
@@ -45,7 +45,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
 
     appContext.setQueue(args.amQueue)
     appContext.setAMContainerSpec(amContainer)
-    appContext.setUser(args.amUser)
+    appContext.setUser(UserGroupInformation.getCurrentUser().getShortUserName())
 
     submitApp(appContext)
     
@@ -141,9 +141,6 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
     val log4jConfLocalRes = localResources.getOrElse("log4j.properties", null)
 
     val env = new HashMap[String, String]()
-    Apps.addToEnvironment(env, Environment.USER.name, args.amUser)
-    // set this so that UGI set to correct user in unsecure mode
-    Apps.addToEnvironment(env, "HADOOP_USER_NAME", args.amUser)
 
     // If log4j present, ensure ours overrides all others
     if (log4jConfLocalRes != null) Apps.addToEnvironment(env, Environment.CLASSPATH.name, "./")
@@ -171,6 +168,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
       env("SPARK_YARN_LOG4J_SIZE") =  log4jConfLocalRes.getSize().toString()
     }
 
+
     // Add each SPARK-* key to the environment
     System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k,v) => env(k) = v }
     return env
@@ -224,7 +222,13 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
     }
 
     // Command for the ApplicationMaster
-    val commands = List[String](Environment.JAVA_HOME.$() + "/bin/java " +
+    var javaCommand = "java";
+    val javaHome = System.getenv("JAVA_HOME")
+    if (javaHome != null && !javaHome.isEmpty()) {
+      javaCommand = Environment.JAVA_HOME.$() + "/bin/java"
+    }
+
+    val commands = List[String](javaCommand + 
       " -server " +
       JAVA_OPTS +
       " spark.deploy.yarn.ApplicationMaster" +
diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala
index 24110558e7..07e7edea36 100644
--- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala
+++ b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/ClientArguments.scala
@@ -13,7 +13,6 @@ class ClientArguments(val args: Array[String]) {
   var workerMemory = 1024
   var workerCores = 1
   var numWorkers = 2
-  var amUser = System.getProperty("user.name")
   var amQueue = System.getProperty("QUEUE", "default")
   var amMemory: Int = 512
   // TODO
@@ -58,10 +57,6 @@ class ClientArguments(val args: Array[String]) {
           workerCores = value
           args = tail
 
-        case ("--user") :: value :: tail =>
-          amUser = value
-          args = tail
-
         case ("--queue") :: value :: tail =>
           amQueue = value
           args = tail
@@ -96,8 +91,7 @@ class ClientArguments(val args: Array[String]) {
       "  --worker-cores NUM   Number of cores for the workers (Default: 1). This is unsused right now.\n" +
       "  --master-memory MEM  Memory for Master (e.g. 1000M, 2G) (Default: 512 Mb)\n" +
       "  --worker-memory MEM  Memory per Worker (e.g. 1000M, 2G) (Default: 1G)\n" +
-      "  --queue QUEUE        The hadoop queue to use for allocation requests (Default: 'default')\n" +
-      "  --user USERNAME      Run the ApplicationMaster (and slaves) as a different user\n"
+      "  --queue QUEUE        The hadoop queue to use for allocation requests (Default: 'default')"
       )
     System.exit(exitCode)
   }
diff --git a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala
index e22d256a84..cc6f3344a1 100644
--- a/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala
+++ b/core/src/hadoop2-yarn/scala/spark/deploy/yarn/WorkerRunnable.scala
@@ -85,7 +85,13 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
     credentials.writeTokenStorageToStream(dob)
     ctx.setContainerTokens(ByteBuffer.wrap(dob.getData()))
 
-    val commands = List[String](Environment.JAVA_HOME.$() + "/bin/java " +
+    var javaCommand = "java";
+    val javaHome = System.getenv("JAVA_HOME")
+    if (javaHome != null && !javaHome.isEmpty()) {
+      javaCommand = Environment.JAVA_HOME.$() + "/bin/java"
+    }
+
+    val commands = List[String](javaCommand +
       " -server " +
       // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling.
       // Not killing the task leaves various aspects of the worker and (to some extent) the jvm in an inconsistent state.
@@ -152,10 +158,6 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
   
   def prepareEnvironment: HashMap[String, String] = {
     val env = new HashMap[String, String]()
-    // should we add this ?
-    Apps.addToEnvironment(env, Environment.USER.name, Utils.getUserNameFromEnvironment())
-    // set this so that UGI set to correct user in unsecure mode
-    Apps.addToEnvironment(env, "HADOOP_USER_NAME", Utils.getUserNameFromEnvironment())
 
     // If log4j present, ensure ours overrides all others
     if (System.getenv("SPARK_YARN_LOG4J_PATH") != null) {
diff --git a/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala b/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala
index a0fb4fe25d..f1c86de4cc 100644
--- a/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala
+++ b/core/src/hadoop2/scala/spark/deploy/SparkHadoopUtil.scala
@@ -1,5 +1,6 @@
 package spark.deploy
 import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.mapred.JobConf
 
 
 /**
@@ -20,4 +21,7 @@ object SparkHadoopUtil {
 
   // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems
   def newConfiguration(): Configuration = new Configuration()
+
+  // add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster
+  def addCredentials(conf: JobConf) {}
 }
diff --git a/core/src/main/scala/spark/PairRDDFunctions.scala b/core/src/main/scala/spark/PairRDDFunctions.scala
index b397601184..c9d698fc09 100644
--- a/core/src/main/scala/spark/PairRDDFunctions.scala
+++ b/core/src/main/scala/spark/PairRDDFunctions.scala
@@ -614,10 +614,6 @@ class PairRDDFunctions[K: ClassManifest, V: ClassManifest](
       outputFormatClass: Class[_ <: OutputFormat[_, _]],
       conf: JobConf = new JobConf(self.context.hadoopConfiguration),
       codec: Option[Class[_ <: CompressionCodec]] = None) {
-    // make sure to propogate any credentials from the current user to the jobConf
-    // for Hadoop security
-    val jobCreds = conf.getCredentials();
-    jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
     conf.setOutputKeyClass(keyClass)
     conf.setOutputValueClass(valueClass)
     // conf.setOutputFormat(outputFormatClass) // Doesn't work in Scala 2.9 due to what may be a generics bug
diff --git a/core/src/main/scala/spark/SparkContext.scala b/core/src/main/scala/spark/SparkContext.scala
index c3a56938b5..6c37203707 100644
--- a/core/src/main/scala/spark/SparkContext.scala
+++ b/core/src/main/scala/spark/SparkContext.scala
@@ -295,10 +295,6 @@ class SparkContext(
       valueClass: Class[V],
       minSplits: Int = defaultMinSplits
       ): RDD[(K, V)] = {
-    // make sure to propogate any credentials from the current user to the jobConf 
-    // for Hadoop security
-    val jobCreds = conf.getCredentials();
-    jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
     new HadoopRDD(this, conf, inputFormatClass, keyClass, valueClass, minSplits)
   }
 
@@ -311,10 +307,6 @@ class SparkContext(
       minSplits: Int = defaultMinSplits
       ) : RDD[(K, V)] = {
     val conf = new JobConf(hadoopConfiguration)
-    // make sure to propogate any credentials from the current user to the jobConf 
-    // for Hadoop security
-    val jobCreds = conf.getCredentials();
-    jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
     FileInputFormat.setInputPaths(conf, path)
     new HadoopRDD(this, conf, inputFormatClass, keyClass, valueClass, minSplits)
   }
diff --git a/core/src/main/scala/spark/rdd/HadoopRDD.scala b/core/src/main/scala/spark/rdd/HadoopRDD.scala
index cbf5512e24..07c103503c 100644
--- a/core/src/main/scala/spark/rdd/HadoopRDD.scala
+++ b/core/src/main/scala/spark/rdd/HadoopRDD.scala
@@ -15,6 +15,7 @@ import org.apache.hadoop.mapred.RecordReader
 import org.apache.hadoop.mapred.Reporter
 import org.apache.hadoop.util.ReflectionUtils
 
+import spark.deploy.SparkHadoopUtil
 import spark.{Dependency, Logging, Partition, RDD, SerializableWritable, SparkContext, TaskContext}
 import spark.util.NextIterator
 import org.apache.hadoop.conf.Configurable
@@ -50,6 +51,7 @@ class HadoopRDD[K, V](
   private val confBroadcast = sc.broadcast(new SerializableWritable(conf))
 
   override def getPartitions: Array[Partition] = {
+    SparkHadoopUtil.addCredentials(conf);
     val inputFormat = createInputFormat(conf)
     if (inputFormat.isInstanceOf[Configurable]) {
       inputFormat.asInstanceOf[Configurable].setConf(conf)
diff --git a/core/src/main/scala/spark/scheduler/InputFormatInfo.scala b/core/src/main/scala/spark/scheduler/InputFormatInfo.scala
index 30a56d7135..17d0ea4f80 100644
--- a/core/src/main/scala/spark/scheduler/InputFormatInfo.scala
+++ b/core/src/main/scala/spark/scheduler/InputFormatInfo.scala
@@ -9,6 +9,7 @@ import org.apache.hadoop.mapreduce.Job
 import org.apache.hadoop.conf.Configuration
 import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet}
 import scala.collection.JavaConversions._
+import spark.deploy.SparkHadoopUtil
 
 
 /**
@@ -71,10 +72,7 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl
   // This method does not expect failures, since validate has already passed ...
   private def prefLocsFromMapreduceInputFormat(): Set[SplitInfo] = {
     val conf = new JobConf(configuration)
-    // make sure to propogate any credentials from the current user to the jobConf
-    // for Hadoop security
-    val jobCreds = conf.getCredentials();
-    jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
+    SparkHadoopUtil.addCredentials(conf);
     FileInputFormat.setInputPaths(conf, path)
 
     val instance: org.apache.hadoop.mapreduce.InputFormat[_, _] =
@@ -94,10 +92,7 @@ class InputFormatInfo(val configuration: Configuration, val inputFormatClazz: Cl
   // This method does not expect failures, since validate has already passed ...
   private def prefLocsFromMapredInputFormat(): Set[SplitInfo] = {
     val jobConf = new JobConf(configuration)
-    // make sure to propogate any credentials from the current user to the jobConf
-    // for Hadoop security
-    val jobCreds = jobConf.getCredentials();
-    jobCreds.mergeAll(UserGroupInformation.getCurrentUser().getCredentials())
+    SparkHadoopUtil.addCredentials(jobConf);
     FileInputFormat.setInputPaths(jobConf, path)
 
     val instance: org.apache.hadoop.mapred.InputFormat[_, _] =