Adapt REPL to Scala 2.13

repl/src/main/scala-2.13/org/apache/spark/repl/Main.scala

@@ -0,0 +1,138 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.repl
+
+import java.io.File
+import java.net.URI
+import java.util.Locale
+
+import scala.tools.nsc.GenericRunnerSettings
+
+import org.apache.spark._
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.internal.StaticSQLConf.CATALOG_IMPLEMENTATION
+import org.apache.spark.util.Utils
+
+object Main extends Logging {
+
+  initializeLogIfNecessary(true)
+  Signaling.cancelOnInterrupt()
+
+  val conf = new SparkConf()
+  val rootDir =
+    conf.getOption("spark.repl.classdir").getOrElse(Utils.getLocalDir(conf))
+  val outputDir = Utils.createTempDir(root = rootDir, namePrefix = "repl")
+
+  var sparkContext: SparkContext = _
+  var sparkSession: SparkSession = _
+  // this is a public var because tests reset it.
+  var interp: SparkILoop = _
+
+  private var hasErrors = false
+  private var isShellSession = false
+
+  private def scalaOptionError(msg: String): Unit = {
+    hasErrors = true
+    // scalastyle:off println
+    Console.err.println(msg)
+    // scalastyle:on println
+  }
+
+  def main(args: Array[String]): Unit = {
+    isShellSession = true
+    doMain(args, new SparkILoop)
+  }
+
+  // Visible for testing
+  private[repl] def doMain(args: Array[String], _interp: SparkILoop): Unit = {
+    interp = _interp
+    val jars = Utils
+      .getLocalUserJarsForShell(conf)
+      // Remove file:///, file:// or file:/ scheme if exists for each jar
+      .map { x =>
+        if (x.startsWith("file:")) new File(new URI(x)).getPath else x
+      }
+      .mkString(File.pathSeparator)
+    val interpArguments = List(
+      "-Yrepl-class-based",
+      "-Yrepl-outdir",
+      s"${outputDir.getAbsolutePath}",
+      "-classpath",
+      jars
+    ) ++ args.toList
+
+    val settings = new GenericRunnerSettings(scalaOptionError)
+    settings.processArguments(interpArguments, true)
+
+    if (!hasErrors) {
+      interp.run(settings) // Repl starts and goes in loop of R.E.P.L
+      Option(sparkContext).foreach(_.stop)
+    }
+  }
+
+  def createSparkSession(): SparkSession = {
+    try {
+      val execUri = System.getenv("SPARK_EXECUTOR_URI")
+      conf.setIfMissing("spark.app.name", "Spark shell")
+      // SparkContext will detect this configuration and register it with the RpcEnv's
+      // file server, setting spark.repl.class.uri to the actual URI for executors to
+      // use. This is sort of ugly but since executors are started as part of SparkContext
+      // initialization in certain cases, there's an initialization order issue that prevents
+      // this from being set after SparkContext is instantiated.
+      conf.set("spark.repl.class.outputDir", outputDir.getAbsolutePath())
+      if (execUri != null) {
+        conf.set("spark.executor.uri", execUri)
+      }
+      if (System.getenv("SPARK_HOME") != null) {
+        conf.setSparkHome(System.getenv("SPARK_HOME"))
+      }
+
+      val builder = SparkSession.builder.config(conf)
+      if (conf
+            .get(CATALOG_IMPLEMENTATION.key, "hive")
+            .toLowerCase(Locale.ROOT) == "hive") {
+        if (SparkSession.hiveClassesArePresent) {
+          // In the case that the property is not set at all, builder's config
+          // does not have this value set to 'hive' yet. The original default
+          // behavior is that when there are hive classes, we use hive catalog.
+          sparkSession = builder.enableHiveSupport().getOrCreate()
+          logInfo("Created Spark session with Hive support")
+        } else {
+          // Need to change it back to 'in-memory' if no hive classes are found
+          // in the case that the property is set to hive in spark-defaults.conf
+          builder.config(CATALOG_IMPLEMENTATION.key, "in-memory")
+          sparkSession = builder.getOrCreate()
+          logInfo("Created Spark session")
+        }
+      } else {
+        // In the case that the property is set but not to 'hive', the internal
+        // default is 'in-memory'. So the sparkSession will use in-memory catalog.
+        sparkSession = builder.getOrCreate()
+        logInfo("Created Spark session")
+      }
+      sparkContext = sparkSession.sparkContext
+      sparkSession
+    } catch {
+      case e: Exception if isShellSession =>
+        logError("Failed to initialize Spark session.", e)
+        sys.exit(1)
+    }
+  }
+
+}

repl/src/main/scala-2.13/org/apache/spark/repl/SparkILoop.scala

@@ -0,0 +1,149 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.repl
+
+import java.io.{BufferedReader, PrintWriter}
+
+// scalastyle:off println
+import scala.Predef.{println => _, _}
+import scala.tools.nsc.GenericRunnerSettings
+import scala.tools.nsc.Settings
+import scala.tools.nsc.interpreter.shell.{ILoop, ShellConfig}
+import scala.tools.nsc.util.stringFromStream
+import scala.util.Properties.{javaVersion, javaVmName, versionString}
+// scalastyle:on println
+
+/**
+ *  A Spark-specific interactive shell.
+ */
+class SparkILoop(in0: BufferedReader, out: PrintWriter)
+  extends ILoop(ShellConfig(new GenericRunnerSettings(_ => ())), in0, out) {
+  def this() = this(null, new PrintWriter(Console.out, true))
+
+  val initializationCommands: Seq[String] = Seq(
+    """
+    @transient val spark = if (org.apache.spark.repl.Main.sparkSession != null) {
+        org.apache.spark.repl.Main.sparkSession
+      } else {
+        org.apache.spark.repl.Main.createSparkSession()
+      }
+    @transient val sc = {
+      val _sc = spark.sparkContext
+      if (_sc.getConf.getBoolean("spark.ui.reverseProxy", false)) {
+        val proxyUrl = _sc.getConf.get("spark.ui.reverseProxyUrl", null)
+        if (proxyUrl != null) {
+          println(
+            s"Spark Context Web UI is available at ${proxyUrl}/proxy/${_sc.applicationId}")
+        } else {
+          println(s"Spark Context Web UI is available at Spark Master Public URL")
+        }
+      } else {
+        _sc.uiWebUrl.foreach {
+          webUrl => println(s"Spark context Web UI available at ${webUrl}")
+        }
+      }
+      println("Spark context available as 'sc' " +
+        s"(master = ${_sc.master}, app id = ${_sc.applicationId}).")
+      println("Spark session available as 'spark'.")
+      _sc
+    }
+    """,
+    "import org.apache.spark.SparkContext._",
+    "import spark.implicits._",
+    "import spark.sql",
+    "import org.apache.spark.sql.functions._"
+  )
+
+  override protected def internalReplAutorunCode(): Seq[String] =
+    initializationCommands
+
+  def initializeSpark(): Unit = {
+    if (!intp.reporter.hasErrors) {
+      // `savingReplayStack` removes the commands from session history.
+      savingReplayStack {
+        initializationCommands.foreach(intp quietRun _)
+      }
+    } else {
+      throw new RuntimeException(
+        s"Scala $versionString interpreter encountered " +
+          "errors during initialization"
+      )
+    }
+  }
+
+  /** Print a welcome message */
+  override def printWelcome(): Unit = {
+    import org.apache.spark.SPARK_VERSION
+    echo("""Welcome to
+      ____              __
+     / __/__  ___ _____/ /__
+    _\ \/ _ \/ _ `/ __/  '_/
+   /___/ .__/\_,_/_/ /_/\_\   version %s
+      /_/
+         """.format(SPARK_VERSION))
+    val welcomeMsg = "Using Scala %s (%s, Java %s)".format(
+      versionString,
+      javaVmName,
+      javaVersion
+    )
+    echo(welcomeMsg)
+    echo("Type in expressions to have them evaluated.")
+    echo("Type :help for more information.")
+  }
+
+  /** Available commands */
+  override def commands: List[LoopCommand] = standardCommands
+
+  override def resetCommand(line: String): Unit = {
+    super.resetCommand(line)
+    initializeSpark()
+    echo(
+      "Note that after :reset, state of SparkSession and SparkContext is unchanged."
+    )
+  }
+
+  override def replay(): Unit = {
+    initializeSpark()
+    super.replay()
+  }
+}
+
+object SparkILoop {
+
+  /**
+   * Creates an interpreter loop with default settings and feeds
+   * the given code to it as input.
+   */
+  def run(code: String, sets: Settings = new Settings): String = {
+    import java.io.{BufferedReader, StringReader, OutputStreamWriter}
+
+    stringFromStream { ostream =>
+      Console.withOut(ostream) {
+        val input = new BufferedReader(new StringReader(code))
+        val output = new PrintWriter(new OutputStreamWriter(ostream), true)
+        val repl = new SparkILoop(input, output)
+
+        if (sets.classpath.isDefault) {
+          sets.classpath.value = sys.props("java.class.path")
+        }
+        repl.run(sets)
+      }
+    }
+  }
+  def run(lines: List[String]): String = run(lines.map(_ + "\n").mkString)
+}

repl/src/test/scala-2.12/org/apache/spark/repl/Repl2Suite.scala

@@ -0,0 +1,58 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.repl
+
+import java.io._
+import java.nio.file.Files
+
+import scala.tools.nsc.interpreter.SimpleReader
+
+import org.apache.log4j.{Level, LogManager, PropertyConfigurator}
+import org.scalatest.BeforeAndAfterAll
+
+import org.apache.spark.{SparkContext, SparkFunSuite}
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.internal.StaticSQLConf.CATALOG_IMPLEMENTATION
+
+class Repl2Suite extends SparkFunSuite with BeforeAndAfterAll {
+  test("propagation of local properties") {
+    // A mock ILoop that doesn't install the SIGINT handler.
+    class ILoop(out: PrintWriter) extends SparkILoop(None, out) {
+      settings = new scala.tools.nsc.Settings
+      settings.usejavacp.value = true
+      org.apache.spark.repl.Main.interp = this
+      in = SimpleReader()
+    }
+
+    val out = new StringWriter()
+    Main.interp = new ILoop(new PrintWriter(out))
+    Main.sparkContext = new SparkContext("local", "repl-test")
+    Main.interp.createInterpreter()
+
+    Main.sparkContext.setLocalProperty("someKey", "someValue")
+
+    // Make sure the value we set in the caller to interpret is propagated in the thread that
+    // interprets the command.
+    Main.interp.interpret("org.apache.spark.repl.Main.sparkContext.getLocalProperty(\"someKey\")")
+    assert(out.toString.contains("someValue"))
+
+    Main.sparkContext.stop()
+    System.clearProperty("spark.driver.port")
+  }
+}