[SPARK-13577][YARN] Allow Spark jar to be multiple jars, archive.

In preparation for the demise of assemblies, this change allows the
YARN backend to use multiple jars and globs as the "Spark jar". The
config option has been renamed to "spark.yarn.jars" to reflect that.

A second option "spark.yarn.archive" was also added; if set, this
takes precedence and uploads an archive expected to contain the jar
files with the Spark code and its dependencies.

Existing deployments should keep working, mostly. This change drops
support for the "SPARK_JAR" environment variable, and also does not
fall back to using "jarOfClass" if no configuration is set, falling
back to finding files under SPARK_HOME instead. This should be fine
since "jarOfClass" probably wouldn't work unless you were using
spark-submit anyway.

Tested with the unit tests, and trying the different config options
on a YARN cluster.

Author: Marcelo Vanzin <[email protected]>

Closes #11500 from vanzin/SPARK-13577.

Author: Marcelo Vanzin

core/src/main/scala/org/apache/spark/SparkConf.scala

@@ -656,7 +656,9 @@ private[spark] object SparkConf extends Logging {
     "spark.memory.offHeap.enabled" -> Seq(
       AlternateConfig("spark.unsafe.offHeap", "1.6")),
     "spark.rpc.message.maxSize" -> Seq(
-      AlternateConfig("spark.akka.frameSize", "1.6"))
+      AlternateConfig("spark.akka.frameSize", "1.6")),
+    "spark.yarn.jars" -> Seq(
+      AlternateConfig("spark.yarn.jar", "2.0"))
     )
 
   /**

core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala

@@ -626,7 +626,6 @@ object SparkSubmit {
     val pathConfigs = Seq(
       "spark.jars",
       "spark.files",
-      "spark.yarn.jar",
       "spark.yarn.dist.files",
       "spark.yarn.dist.archives")
     pathConfigs.foreach { config =>

docs/running-on-yarn.md

@@ -272,14 +272,25 @@ If you need a reference to the proper location to put log files in the YARN so t
   </td>
 </tr>
 <tr>
-  <td><code>spark.yarn.jar</code></td>
+  <td><code>spark.yarn.jars</code></td>
   <td>(none)</td>
   <td>
-    The location of the Spark jar file, in case overriding the default location is desired.
-    By default, Spark on YARN will use a Spark jar installed locally, but the Spark jar can also be
+    List of libraries containing Spark code to distribute to YARN containers.
+    By default, Spark on YARN will use Spark jars installed locally, but the Spark jars can also be
     in a world-readable location on HDFS. This allows YARN to cache it on nodes so that it doesn't
-    need to be distributed each time an application runs. To point to a jar on HDFS, for example,
-    set this configuration to <code>hdfs:///some/path</code>.
+    need to be distributed each time an application runs. To point to jars on HDFS, for example,
+    set this configuration to <code>hdfs:///some/path</code>. Globs are allowed.
+  </td>
+</tr>
+<tr>
+  <td><code>spark.yarn.archive</code></td>
+  <td>(none)</td>
+  <td>
+    An archive containing needed Spark jars for distribution to the YARN cache. If set, this
+    configuration replaces <code>spark.yarn.jars</code> and the archive is used in all the
+    application's containers. The archive should contain jar files in its root directory.
+    Like with the previous option, the archive can also be hosted on HDFS to speed up file
+    distribution.
   </td>
 </tr>
 <tr>
@@ -288,8 +299,8 @@ If you need a reference to the proper location to put log files in the YARN so t
   <td>
     A comma-separated list of secure HDFS namenodes your Spark application is going to access. For
     example, <code>spark.yarn.access.namenodes=hdfs://nn1.com:8032,hdfs://nn2.com:8032,
-    webhdfs://nn3.com:50070</code>. The Spark application must have access to the namenodes listed 
-    and Kerberos must be properly configured to be able to access them (either in the same realm 
+    webhdfs://nn3.com:50070</code>. The Spark application must have access to the namenodes listed
+    and Kerberos must be properly configured to be able to access them (either in the same realm
     or in a trusted realm). Spark acquires security tokens for each of the namenodes so that
     the Spark application can access those remote HDFS clusters.
   </td>

yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala

@@ -423,16 +423,71 @@ private[spark] class Client(
     }
 
     /**
-     * Copy the given main resource to the distributed cache if the scheme is not "local".
+     * Add Spark to the cache. There are two settings that control what files to add to the cache:
+     * - if a Spark archive is defined, use the archive. The archive is expected to contain
+     *   jar files at its root directory.
+     * - if a list of jars is provided, filter the non-local ones, resolve globs, and
+     *   add the found files to the cache.
+     *
+     * Note that the archive cannot be a "local" URI. If none of the above settings are found,
+     * then upload all files found in $SPARK_HOME/jars.
+     *
+     * TODO: currently the code looks in $SPARK_HOME/lib while the work to replace assemblies
+     * with a directory full of jars is ongoing.
+     */
+    val sparkArchive = sparkConf.get(SPARK_ARCHIVE)
+    if (sparkArchive.isDefined) {
+      val archive = sparkArchive.get
+      require(!isLocalUri(archive), s"${SPARK_ARCHIVE.key} cannot be a local URI.")
+      distribute(Utils.resolveURI(archive).toString,
+        resType = LocalResourceType.ARCHIVE,
+        destName = Some(LOCALIZED_LIB_DIR))
+    } else {
+      sparkConf.get(SPARK_JARS) match {
+        case Some(jars) =>
+          // Break the list of jars to upload, and resolve globs.
+          val localJars = new ArrayBuffer[String]()
+          jars.foreach { jar =>
+            if (!isLocalUri(jar)) {
+              val path = getQualifiedLocalPath(Utils.resolveURI(jar), hadoopConf)
+              val pathFs = FileSystem.get(path.toUri(), hadoopConf)
+              pathFs.globStatus(path).filter(_.isFile()).foreach { entry =>
+                distribute(entry.getPath().toUri().toString(),
+                  targetDir = Some(LOCALIZED_LIB_DIR))
+              }
+            } else {
+              localJars += jar
+            }
+          }
+
+          // Propagate the local URIs to the containers using the configuration.
+          sparkConf.set(SPARK_JARS, localJars)
+
+        case None =>
+          // No configuration, so fall back to uploading local jar files.
+          logWarning(s"Neither ${SPARK_JARS.key} nor ${SPARK_ARCHIVE.key} is set, falling back " +
+            "to uploading libraries under SPARK_HOME.")
+          val jarsDir = new File(sparkConf.getenv("SPARK_HOME"), "lib")
+          if (jarsDir.isDirectory()) {
+            jarsDir.listFiles().foreach { f =>
+              if (f.isFile() && f.getName().toLowerCase().endsWith(".jar")) {
+                distribute(f.getAbsolutePath(), targetDir = Some(LOCALIZED_LIB_DIR))
+              }
+            }
+          }
+      }
+    }
+
+    /**
+     * Copy a few resources to the distributed cache if their scheme is not "local".
      * Otherwise, set the corresponding key in our SparkConf to handle it downstream.
      * Each resource is represented by a 3-tuple of:
      *   (1) destination resource name,
      *   (2) local path to the resource,
      *   (3) Spark property key to set if the scheme is not local
      */
     List(
-      (SPARK_JAR_NAME, sparkJar(sparkConf), SPARK_JAR.key),
-      (APP_JAR_NAME, args.userJar, APP_JAR.key),
+      (APP_JAR_NAME, args.userJar, APP_JAR),
       ("log4j.properties", oldLog4jConf.orNull, null)
     ).foreach { case (destName, path, confKey) =>
       if (path != null && !path.trim().isEmpty()) {
@@ -1062,8 +1117,7 @@ object Client extends Logging {
     new Client(args, sparkConf).run()
   }
 
-  // Alias for the Spark assembly jar and the user jar
-  val SPARK_JAR_NAME: String = "__spark__.jar"
+  // Alias for the user jar
   val APP_JAR_NAME: String = "__app__.jar"
 
   // URI scheme that identifies local resources
@@ -1072,8 +1126,6 @@ object Client extends Logging {
   // Staging directory for any temporary jars or files
   val SPARK_STAGING: String = ".sparkStaging"
 
-  // Location of any user-defined Spark jars
-  val ENV_SPARK_JAR = "SPARK_JAR"
 
   // Staging directory is private! -> rwx--------
   val STAGING_DIR_PERMISSION: FsPermission =
@@ -1095,28 +1147,8 @@ object Client extends Logging {
   // Subdirectory where the user's python files (not archives) will be placed.
   val LOCALIZED_PYTHON_DIR = "__pyfiles__"
 
-  /**
-   * Find the user-defined Spark jar if configured, or return the jar containing this
-   * class if not.
-   *
-   * This method first looks in the SparkConf object for the spark.yarn.jar key, and in the
-   * user environment if that is not found (for backwards compatibility).
-   */
-  private def sparkJar(conf: SparkConf): String = {
-    conf.get(SPARK_JAR).getOrElse(
-      if (System.getenv(ENV_SPARK_JAR) != null) {
-        logWarning(
-          s"$ENV_SPARK_JAR detected in the system environment. This variable has been deprecated " +
-            s"in favor of the ${SPARK_JAR.key} configuration variable.")
-        System.getenv(ENV_SPARK_JAR)
-      } else {
-        SparkContext.jarOfClass(this.getClass).getOrElse(throw new SparkException("Could not "
-          + "find jar containing Spark classes. The jar can be defined using the "
-          + s"${SPARK_JAR.key} configuration option. If testing Spark, either set that option "
-          + "or make sure SPARK_PREPEND_CLASSES is not set."))
-      }
-    )
-  }
+  // Subdirectory where Spark libraries will be placed.
+  val LOCALIZED_LIB_DIR = "__spark_libs__"
 
   /**
    * Return the path to the given application's staging directory.
@@ -1236,7 +1268,18 @@ object Client extends Logging {
         addFileToClasspath(sparkConf, conf, x, null, env)
       }
     }
-    addFileToClasspath(sparkConf, conf, new URI(sparkJar(sparkConf)), SPARK_JAR_NAME, env)
+
+    // Add the Spark jars to the classpath, depending on how they were distributed.
+    addClasspathEntry(buildPath(YarnSparkHadoopUtil.expandEnvironment(Environment.PWD),
+      LOCALIZED_LIB_DIR, "*"), env)
+    if (!sparkConf.get(SPARK_ARCHIVE).isDefined) {
+      sparkConf.get(SPARK_JARS).foreach { jars =>
+        jars.filter(isLocalUri).foreach { jar =>
+          addClasspathEntry(getClusterPath(sparkConf, jar), env)
+        }
+      }
+    }
+
     populateHadoopClasspath(conf, env)
     sys.env.get(ENV_DIST_CLASSPATH).foreach { cp =>
       addClasspathEntry(getClusterPath(sparkConf, cp), env)
@@ -1392,4 +1435,9 @@ object Client extends Logging {
     components.mkString(Path.SEPARATOR)
   }
 
+  /** Returns whether the URI is a "local:" URI. */
+  def isLocalUri(uri: String): Boolean = {
+    uri.startsWith(s"$LOCAL_SCHEME:")
+  }
+
 }

yarn/src/main/scala/org/apache/spark/deploy/yarn/config.scala

@@ -72,11 +72,17 @@ package object config {
 
   /* File distribution. */
 
-  private[spark] val SPARK_JAR = ConfigBuilder("spark.yarn.jar")
-    .doc("Location of the Spark jar to use.")
+  private[spark] val SPARK_ARCHIVE = ConfigBuilder("spark.yarn.archive")
+    .doc("Location of archive containing jars files with Spark classes.")
     .stringConf
     .optional
 
+  private[spark] val SPARK_JARS = ConfigBuilder("spark.yarn.jars")
+    .doc("Location of jars containing Spark classes.")
+    .stringConf
+    .toSequence
+    .optional
+
   private[spark] val ARCHIVES_TO_DISTRIBUTE = ConfigBuilder("spark.yarn.dist.archives")
     .stringConf
     .optional

yarn/src/test/scala/org/apache/spark/deploy/yarn/BaseYarnClusterSuite.scala

@@ -34,6 +34,7 @@ import org.scalatest.{BeforeAndAfterAll, Matchers}
 import org.scalatest.concurrent.Eventually._
 
 import org.apache.spark._
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.launcher._
 import org.apache.spark.util.Utils
 
@@ -202,7 +203,7 @@ abstract class BaseYarnClusterSuite
       extraClassPath: Seq[String] = Nil,
       extraConf: Map[String, String] = Map()): String = {
     val props = new Properties()
-    props.put("spark.yarn.jar", "local:" + fakeSparkJar.getAbsolutePath())
+    props.put(SPARK_JARS.key, "local:" + fakeSparkJar.getAbsolutePath())
 
     val testClasspath = new TestClasspathBuilder()
       .buildClassPath(