JavaWeb提交spark任务到yarn

最近项目准备把hadoop的MR转换为Spark，之前的MR是能够直接提交java文件到集群服务器中，但Spark我没有找到相应的方式(有大神知道如何处理但愿能够告之下)，我这边使用了SparkAppHandle的方式来进行处理.

CountDownLatch cdl= new CountDownLatch(1);
		SparkAppHandle handle = new SparkLauncher().setSparkHome("/usr/local/spark-2.2.0")
				.setAppResource("/usr/local/spark-2.2.0/lib/spark.jar")
				.setMainClass("run.aaa.spark.SimpleApp")
				.setMaster("yarn").setDeployMode("client")
				.setAppName("test yarn client")
				.setConf("spark.yarn.jars", "hdfs://master:9000/tmp/spark-jars/*")
				.setConf("spark.driver.allowMultipleContexts", "true")
				.setConf("spark.executor.cores", "2")
				.setConf("spark.executor.instances", "2") 
				.addAppArgs("/README.md")
				.setVerbose(true)
				.startApplication(new SparkAppHandle.Listener() {
					// 这里监放任务状态，当任务结束时（不论是什么缘由结束）,isFinal方法会返回true,不然返回false
					@Override
					public void stateChanged(SparkAppHandle sparkAppHandle) {
						if (sparkAppHandle.getState().isFinal()) {
							cdl.countDown();
						}
						System.out.println("state:" + sparkAppHandle.getState().toString());
					}

					@Override
					public void infoChanged(SparkAppHandle sparkAppHandle) {
						System.out.println("Info:" + sparkAppHandle.getState().toString());
					}
				});
		System.out.println("The task is executing, please wait ....");
		// 线程等待任务结束
		cdl.await();
		System.out.println("The task is finished!");