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/*
* 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.
*/
/**
* Library for launching Spark applications programmatically.
*
*
* There are two ways to start applications with this library: as a child process, using
* {@link org.apache.spark.launcher.SparkLauncher}, or in-process, using
* {@link org.apache.spark.launcher.InProcessLauncher}.
*
*
*
* The {@link org.apache.spark.launcher.AbstractLauncher#startApplication(
* org.apache.spark.launcher.SparkAppHandle.Listener...)} method can be used to start Spark and
* provide a handle to monitor and control the running application:
*
*
*
* {@code
* import org.apache.spark.launcher.SparkAppHandle;
* import org.apache.spark.launcher.SparkLauncher;
*
* public class MyLauncher {
* public static void main(String[] args) throws Exception {
* SparkAppHandle handle = new SparkLauncher()
* .setAppResource("/my/app.jar")
* .setMainClass("my.spark.app.Main")
* .setMaster("local")
* .setConf(SparkLauncher.DRIVER_MEMORY, "2g")
* .startApplication();
* // Use handle API to monitor / control application.
* }
* }
* }
*
*
*
* Launching applications as a child process requires a full Spark installation. The installation
* directory can be provided to the launcher explicitly in the launcher's configuration, or by
* setting the SPARK_HOME environment variable.
*
*
*
* Launching applications in-process is only recommended in cluster mode, since Spark cannot run
* multiple client-mode applications concurrently in the same process. The in-process launcher
* requires the necessary Spark dependencies (such as spark-core and cluster manager-specific
* modules) to be present in the caller thread's class loader.
*
*
*
* It's also possible to launch a raw child process, without the extra monitoring, using the
* {@link org.apache.spark.launcher.SparkLauncher#launch()} method:
*
*
*
* {@code
* import org.apache.spark.launcher.SparkLauncher;
*
* public class MyLauncher {
* public static void main(String[] args) throws Exception {
* Process spark = new SparkLauncher()
* .setAppResource("/my/app.jar")
* .setMainClass("my.spark.app.Main")
* .setMaster("local")
* .setConf(SparkLauncher.DRIVER_MEMORY, "2g")
* .launch();
* spark.waitFor();
* }
* }
* }
*
*
* This method requires the calling code to manually manage the child process, including its
* output streams (to avoid possible deadlocks). It's recommended that
* {@link org.apache.spark.launcher.SparkLauncher#startApplication(
* org.apache.spark.launcher.SparkAppHandle.Listener...)} be used instead.
*/
package org.apache.spark.launcher;