Github user tgravescs commented on a diff in the pull request:
https://github.com/apache/spark/pull/4688#discussion_r25538854
--- 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 --
Yeah I was saying use distributed cache for the keytab to the AM. The
distributed cache code is in Client.prepareLocalResources which populates stuff
to go to the AM, then for each executor its handled in
ExecutorRunnable.prepareLocalResources. You would need some way or use new
config that would say only send this to the AM and not on to the executors. We
used to do that for jars when we used the Spark addJar distribution mechanism.
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