java 任务嵌入spark启动类

依赖类 org.apache.spark.launcher.SparkLauncher

启动类：

import org.apache.spark.launcher.{SparkAppHandle, SparkLauncher}

object SparkLuncherTest {
  def main(args: Array[String]): Unit = {
    val launcher = new SparkLauncher()
    .setAppName("myTest")
    .setSparkHome("C:\\spark-2.4.7-bin-3.0.0\\")
    .setMaster("local")
    .setAppResource("D:\\workspace\\data_analysis\\offlineJob\\target\\offlineJob.jar")
    .setMainClass("com.test.ValidationSet.SparkTest")
//    .setDeployMode("cluster")
      .startApplication(new SparkAppHandle.Listener {
        override def stateChanged(sparkAppHandle: SparkAppHandle): Unit = {
          println("state change")
        }

        override def infoChanged(sparkAppHandle: SparkAppHandle): Unit = {
          println("info change")
        }
      })

    while(!"FINISHED".equalsIgnoreCase(launcher.getState.toString)&& !"FAILED".equalsIgnoreCase(launcher.getState.toString)){
      println(launcher.getState.toString)
      Thread.sleep(1000*200L)
    }

    println(launcher.getState.toString)
  }

}

逻辑执行代码：

 

import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

object SparkTest {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf()
//      .setAppName("aaa")
//      .setMaster("local")

    val sc = new SparkContext(conf)
    sc.setLogLevel("WARN")
    val value: RDD[String] = sc.parallelize(Seq("aaa","bbb"))
    println("mt："+value.collect().toBuffer)
    sc.stop()
  }
}

 

开始执行：执行命令

java -cp D:\workspace\data_analysis\offlineJob\target\offlineJob.jar com.sobot.ValidationSet.SparkLuncherTest

打印日志：

如下打印了SparkTest类的println