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From harishreedharan <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-5342][YARN] Allow long running Spark ap...
Date Fri, 27 Feb 2015 19:41:15 GMT
Github user harishreedharan commented on a diff in the pull request:

    https://github.com/apache/spark/pull/4688#discussion_r25532849
  
    --- Diff: yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala ---
    @@ -82,6 +93,102 @@ class YarnSparkHadoopUtil extends SparkHadoopUtil {
         if (credentials != null) credentials.getSecretKey(new Text(key)) else null
       }
     
    +  override def setPrincipalAndKeytabForLogin(principal: String, keytab: String): Unit
= {
    +    loginPrincipal = Option(principal)
    +    keytabFile = Option(keytab)
    +  }
    +
    +  private[spark] override def scheduleLoginFromKeytab(
    +    callback: (SerializableBuffer)  => Unit): Unit = {
    +
    +    loginPrincipal match {
    +      case Some(principal) =>
    +        val keytab = keytabFile.get
    +        val remoteFs = FileSystem.get(conf)
    +        val remoteKeytabPath = new Path(
    +          remoteFs.getHomeDirectory, System.getenv("SPARK_STAGING_DIR") + Path.SEPARATOR
+ keytab)
    +        val localFS = FileSystem.getLocal(conf)
    +        // At this point, SparkEnv is likely no initialized, so create a dir, put the
keytab there.
    +        val tempDir = Utils.createTempDir()
    +        val localURI = new URI(tempDir.getAbsolutePath + Path.SEPARATOR + keytab)
    +        val qualifiedURI = new  URI(localFS.makeQualified(new Path(localURI)).toString)
    +        FileUtil.copy(
    --- End diff --
    
    Sure, I am not saying we can't. I am just saying I have not been able to figure out how
to :)


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