Route bin/pyspark through Spark submit

The bin/pyspark script takes two pathways, depending on the application.

If the application is a python file, bin/pyspark passes the python file
directly to Spark submit, which launches the python application as a
sub-process within the JVM.

If the application is the pyspark shell, however, bin/pyspark starts
the python REPL as the parent process, which launches the JVM as a
sub-process. A significant benefit here is that all keyboard signals
are propagated first to the Python interpreter properly. The existing
code already provided a code path to do this; all we need to change
is to use spark-submit instead of spark-class to launch the JVM. This
requires modifications to Spark submit to handle the pyspark shell
as a special case.

This has been tested locally (OSX) for both cases, and using IPython.

bin/pyspark

@@ -51,14 +51,20 @@ export PYTHONPATH=$SPARK_HOME/python/lib/py4j-0.8.1-src.zip:$PYTHONPATH
 # Load the PySpark shell.py script when ./pyspark is used interactively:
 export OLD_PYTHONSTARTUP=$PYTHONSTARTUP
 export PYTHONSTARTUP=$FWDIR/python/pyspark/shell.py
+export PYSPARK_SUBMIT_ARGS="$@"
 
 if [ -n "$IPYTHON_OPTS" ]; then
   IPYTHON=1
 fi
 
-# Only use ipython if no command line arguments were provided [SPARK-1134]
-if [[ "$IPYTHON" = "1" && $# = 0 ]] ; then
-  exec ipython $IPYTHON_OPTS
+# If a python file is provided, directly run spark-submit
+if [[ "$1" =~ \.py$ ]]; then
+  exec $FWDIR/bin/spark-submit $PYSPARK_SUBMIT_ARGS
 else
-  exec "$PYSPARK_PYTHON" "$@"
+  # Only use ipython if no command line arguments were provided [SPARK-1134]
+  if [[ "$IPYTHON" = "1" ]]; then
+    exec ipython $IPYTHON_OPTS
+  else
+    exec "$PYSPARK_PYTHON"
+  fi
 fi

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

@@ -42,7 +42,7 @@ object PythonRunner {
     // Build up a PYTHONPATH that includes the Spark assembly JAR (where this class is), the
     // python directories in SPARK_HOME (if set), and any files in the pyFiles argument
     val pathElements = new ArrayBuffer[String]
-    pathElements ++= pyFiles.split(",")
+    pathElements ++= Option(pyFiles).getOrElse("").split(",")
     pathElements += PythonUtils.sparkPythonPath
     pathElements += sys.env.getOrElse("PYTHONPATH", "")
     val pythonPath = PythonUtils.mergePythonPaths(pathElements: _*)

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

@@ -41,10 +41,10 @@ object SparkSubmit {
   private var clusterManager: Int = LOCAL
 
   /**
-   * A special jar name that indicates the class being run is inside of Spark itself,
-   * and therefore no user jar is needed.
+   * Special primary resource names that represent shells rather than application jars.
    */
-  private val RESERVED_JAR_NAME = "spark-internal"
+  private val SPARK_SHELL = "spark-shell"
+  private val PYSPARK_SHELL = "pyspark-shell"
 
   def main(args: Array[String]) {
     val appArgs = new SparkSubmitArguments(args)
@@ -71,8 +71,8 @@ object SparkSubmit {
    *         entries for the child, a list of system properties, a list of env vars
    *         and the main class for the child
    */
-  private[spark] def createLaunchEnv(args: SparkSubmitArguments): (ArrayBuffer[String],
-      ArrayBuffer[String], Map[String, String], String) = {
+  private[spark] def createLaunchEnv(args: SparkSubmitArguments)
+      : (ArrayBuffer[String], ArrayBuffer[String], Map[String, String], String) = {
     if (args.master.startsWith("local")) {
       clusterManager = LOCAL
     } else if (args.master.startsWith("yarn")) {
@@ -121,24 +121,30 @@ object SparkSubmit {
       printErrorAndExit("Cannot currently run driver on the cluster in Mesos")
     }
 
-    // If we're running a Python app, set the Java class to run to be our PythonRunner, add
-    // Python files to deployment list, and pass the main file and Python path to PythonRunner
+    // If we're running a python app, set the main class to our specific python runner
     if (isPython) {
       if (deployOnCluster) {
         printErrorAndExit("Cannot currently run Python driver programs on cluster")
       }
-      args.mainClass = "org.apache.spark.deploy.PythonRunner"
-      args.files = mergeFileLists(args.files, args.pyFiles, args.primaryResource)
+      if (args.primaryResource == PYSPARK_SHELL) {
+        args.mainClass = "py4j.GatewayServer"
+        args.childArgs ++= ArrayBuffer("--die-on-broken-pipe", "0")
+      } else {
+        // If a python file is provided, add it to the child arguments and list of files to deploy.
+        // Usage: PythonAppRunner <main python file> <extra python files> [app arguments]
+        args.mainClass = "org.apache.spark.deploy.PythonRunner"
+        args.childArgs = ArrayBuffer(args.primaryResource, args.pyFiles) ++ args.childArgs
+        args.files = Utils.mergeFileLists(args.files, args.primaryResource)
+      }
       val pyFiles = Option(args.pyFiles).getOrElse("")
-      args.childArgs = ArrayBuffer(args.primaryResource, pyFiles) ++ args.childArgs
-      args.primaryResource = RESERVED_JAR_NAME
+      args.files = Utils.mergeFileLists(args.files, pyFiles)
       sysProps("spark.submit.pyFiles") = pyFiles
     }
 
     // If we're deploying into YARN, use yarn.Client as a wrapper around the user class
     if (!deployOnCluster) {
       childMainClass = args.mainClass
-      if (args.primaryResource != RESERVED_JAR_NAME) {
+      if (isUserJar(args.primaryResource)) {
         childClasspath += args.primaryResource
       }
     } else if (clusterManager == YARN) {
@@ -219,7 +225,7 @@ object SparkSubmit {
     // For python files, the primary resource is already distributed as a regular file
     if (!isYarnCluster && !isPython) {
       var jars = sysProps.get("spark.jars").map(x => x.split(",").toSeq).getOrElse(Seq())
-      if (args.primaryResource != RESERVED_JAR_NAME) {
+      if (isUserJar(args.primaryResource)) {
         jars = jars ++ Seq(args.primaryResource)
       }
       sysProps.put("spark.jars", jars.mkString(","))
@@ -293,8 +299,8 @@ object SparkSubmit {
   }
 
   private def addJarToClasspath(localJar: String, loader: ExecutorURLClassLoader) {
-    val localJarFile = new File(new URI(localJar).getPath())
-    if (!localJarFile.exists()) {
+    val localJarFile = new File(new URI(localJar).getPath)
+    if (!localJarFile.exists) {
       printWarning(s"Jar $localJar does not exist, skipping.")
     }
 
@@ -303,14 +309,24 @@ object SparkSubmit {
   }
 
   /**
-   * Merge a sequence of comma-separated file lists, some of which may be null to indicate
-   * no files, into a single comma-separated string.
+   * Return whether the given primary resource represents a user jar.
+   */
+  private def isUserJar(primaryResource: String): Boolean = {
+    !isShell(primaryResource) && !isPython(primaryResource)
+  }
+
+  /**
+   * Return whether the given primary resource represents a shell.
+   */
+  private def isShell(primaryResource: String): Boolean = {
+    primaryResource == SPARK_SHELL || primaryResource == PYSPARK_SHELL
+  }
+
+  /**
+   * Return whether the given primary resource requires running python.
    */
-  private[spark] def mergeFileLists(lists: String*): String = {
-    val merged = lists.filter(_ != null)
-                      .flatMap(_.split(","))
-                      .mkString(",")
-    if (merged == "") null else merged
+  private[spark] def isPython(primaryResource: String): Boolean = {
+    primaryResource.endsWith(".py") || primaryResource == PYSPARK_SHELL
   }
 }
 

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

@@ -298,7 +298,7 @@ private[spark] class SparkSubmitArguments(args: Seq[String]) {
             case v =>
               primaryResource = v
               inSparkOpts = false
-              isPython = v.endsWith(".py")
+              isPython = SparkSubmit.isPython(v)
               parse(tail)
           }
         } else {

core/src/main/scala/org/apache/spark/util/Utils.scala

@@ -1166,4 +1166,16 @@ private[spark] object Utils extends Logging {
         true
     }
   }
+
+  /**
+   * Merge a sequence of comma-separated file lists into a single comma-separated string.
+   * The provided strings may be null or empty to indicate no files.
+   */
+  def mergeFileLists(lists: String*): String = {
+    lists
+      .filter(_ != null)
+      .filter(_ != "")
+      .flatMap(_.split(","))
+      .mkString(",")
+  }
 }

python/pyspark/java_gateway.py

@@ -34,9 +34,13 @@ def launch_gateway():
         # Launch the Py4j gateway using Spark's run command so that we pick up the
         # proper classpath and settings from spark-env.sh
         on_windows = platform.system() == "Windows"
-        script = "./bin/spark-class.cmd" if on_windows else "./bin/spark-class"
-        command = [os.path.join(SPARK_HOME, script), "py4j.GatewayServer",
-                   "--die-on-broken-pipe", "0"]
+        script = "./bin/spark-submit.cmd" if on_windows else "./bin/spark-submit"
+        submit_args = os.environ.get("PYSPARK_SUBMIT_ARGS")
+        if submit_args is not None:
+          submit_args = submit_args.split(" ")
+        else:
+          submit_args = []
+        command = [os.path.join(SPARK_HOME, script), "pyspark-shell"] + submit_args
         if not on_windows:
             # Don't send ctrl-c / SIGINT to the Java gateway:
             def preexec_func():

python/pyspark/shell.py

@@ -40,7 +40,7 @@
 if os.environ.get("SPARK_EXECUTOR_URI"):
     SparkContext.setSystemProperty("spark.executor.uri", os.environ["SPARK_EXECUTOR_URI"])
 
-sc = SparkContext(os.environ.get("MASTER", "local[*]"), "PySparkShell", pyFiles=add_files)
+sc = SparkContext(appName="PySparkShell", pyFiles=add_files)
 
 print("""Welcome to
       ____              __