Merge pull request alteryx#23 from jerryshao/multi-user

Add Spark multi-user support for standalone mode and Mesos This PR add multi-user support for Spark both standalone mode and Mesos (coarse and fine grained ) mode, user can specify the user name who submit app through environment variable `SPARK_USER` or use default one. Executor will communicate with Hadoop using specified user name. Also I fixed one bug in JobLogger when different user wrote job log to specified folder which has no right file permission. I separate previous [PR750](mesos/spark#750) into two PRs, in this PR I only solve multi-user support problem. I will try to solve security auth problem in subsequent PR because security auth is a complicated problem especially for Shark Server like long-run app (both Kerberos TGT and HDFS delegation token should be renewed or re-created through app's run time). (cherry picked from commit be7e8da) Signed-off-by: Reynold Xin <[email protected]>
jhartlaub · Nov 7, 2013 · d5ae953 · d5ae953
1 parent 1d9412b
commit d5ae953
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Showing 5 changed files with 417 additions and 379 deletions.
diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala
@@ -145,6 +145,14 @@ class SparkContext(
     executorEnvs ++= environment
   }
 
+  // Set SPARK_USER for user who is running SparkContext.
+  val sparkUser = Option {
+    Option(System.getProperty("user.name")).getOrElse(System.getenv("SPARK_USER"))
+  }.getOrElse {
+    SparkContext.SPARK_UNKNOWN_USER
+  }
+  executorEnvs("SPARK_USER") = sparkUser
+
   // Create and start the scheduler
   private[spark] var taskScheduler: TaskScheduler = {
     // Regular expression used for local[N] master format
@@ -984,6 +992,8 @@ object SparkContext {
 
   private[spark] val SPARK_JOB_GROUP_ID = "spark.jobGroup.id"
 
+  private[spark] val SPARK_UNKNOWN_USER = "<unknown>"
+
   implicit object DoubleAccumulatorParam extends AccumulatorParam[Double] {
     def addInPlace(t1: Double, t2: Double): Double = t1 + t2
     def zero(initialValue: Double) = 0.0

diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
@@ -17,8 +17,11 @@
 
 package org.apache.spark.deploy
 
+import java.security.PrivilegedExceptionAction
+
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.mapred.JobConf
+import org.apache.hadoop.security.UserGroupInformation
 
 import org.apache.spark.SparkException
 
@@ -27,6 +30,15 @@ import org.apache.spark.SparkException
  */
 private[spark]
 class SparkHadoopUtil {
+  val conf = newConfiguration()
+  UserGroupInformation.setConfiguration(conf)
+
+  def runAsUser(user: String)(func: () => Unit) {
+    val ugi = UserGroupInformation.createRemoteUser(user)
+    ugi.doAs(new PrivilegedExceptionAction[Unit] {
+      def run: Unit = func()
+    })
+  }
 
   /**
    * Return an appropriate (subclass) of Configuration. Creating config can initializes some Hadoop
@@ -42,9 +54,9 @@ class SparkHadoopUtil {
 
   def isYarnMode(): Boolean = { false }
 }
-  
+
 object SparkHadoopUtil {
-  private val hadoop = { 
+  private val hadoop = {
     val yarnMode = java.lang.Boolean.valueOf(System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE")))
     if (yarnMode) {
       try {
@@ -56,7 +68,7 @@ object SparkHadoopUtil {
       new SparkHadoopUtil
     }
   }
-  
+
   def get: SparkHadoopUtil = {
     hadoop
   }

diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala
@@ -25,8 +25,9 @@ import java.util.concurrent._
 import scala.collection.JavaConversions._
 import scala.collection.mutable.HashMap
 
-import org.apache.spark.scheduler._
 import org.apache.spark._
+import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.scheduler._
 import org.apache.spark.storage.{StorageLevel, TaskResultBlockId}
 import org.apache.spark.util.Utils
 
@@ -129,6 +130,8 @@ private[spark] class Executor(
   // Maintains the list of running tasks.
   private val runningTasks = new ConcurrentHashMap[Long, TaskRunner]
 
+  val sparkUser = Option(System.getenv("SPARK_USER")).getOrElse(SparkContext.SPARK_UNKNOWN_USER)
+
   def launchTask(context: ExecutorBackend, taskId: Long, serializedTask: ByteBuffer) {
     val tr = new TaskRunner(context, taskId, serializedTask)
     runningTasks.put(taskId, tr)
@@ -176,7 +179,7 @@ private[spark] class Executor(
       }
     }
 
-    override def run() {
+    override def run(): Unit = SparkHadoopUtil.get.runAsUser(sparkUser) { () =>
       val startTime = System.currentTimeMillis()
       SparkEnv.set(env)
       Thread.currentThread.setContextClassLoader(replClassLoader)