Spark提交任务入口源码分析

/data/opt/spark-2.3.1-bin-hadoop2.7/bin/spark-submit \
    --class com.tencent.th.dwd.t_dwd_evt_user_action_log_s \
    --total-executor-cores 300 --conf spark.sql.shuffle.partitions=500 \
    SparkV2-1.0.1.jar repartition_num=300

cat /data/opt/spark-2.3.1-bin-hadoop2.7/bin/spark-submit
if [ -z "${SPARK_HOME}" ]; then
  source "$(dirname "$0")"/find-spark-home
# disable randomized hash for string in Python 3.3+
export PYTHONHASHSEED=0
export SPARK_HOME=/data/opt/spark-2.3.1-bin-hadoop2.7/
exec "${SPARK_HOME}"/bin/spark-class org.apache.spark.deploy.SparkSubmit "$@"

def main(args: Array[String]): Unit = {
  //这里将传入的args参数进行初始化
  val appArgs = new SparkSubmitArguments(args)
  //判断参数是否有效合法
  if (appArgs.verbose) {
    // scalastyle:off println
    printStream.println(appArgs)
    // scalastyle:on println
  //判断执行类别
  appArgs.action match {
    case SparkSubmitAction.SUBMIT => submit(appArgs)
    case SparkSubmitAction.KILL => kill(appArgs)
    case SparkSubmitAction.REQUEST_STATUS => requestStatus(appArgs)
}

/**
 * Submit the application using the provided parameters.
 * This runs in two steps. First, we prepare the launch environment by setting up
 * the appropriate classpath, system properties, and application arguments for
 * running the child main class based on the cluster manager and the deploy mode.
 * Second, we use this launch environment to invoke the main method of the child
 * main class.
@tailrec
private def submit(args: SparkSubmitArguments): Unit = {
  /**准备执行环境，这里主要得到了以下4个参数:
      (1)childArgs: 子进程的参数
      (2)childClasspath: 子进程的执行环境
      (3)sysProps:系统参数
      (4)childMainClass:子类名  
  val (childArgs, childClasspath, sysProps, childMainClass) = prepareSubmitEnvironment(args)
  //开始执行Spark任务
  def doRunMain(): Unit = {
    //是否需要创建代理用户
    if (args.proxyUser != null) {
      val proxyUser = UserGroupInformation.createProxyUser(args.proxyUser,
        UserGroupInformation.getCurrentUser())
      try {
        proxyUser.doAs(new PrivilegedExceptionAction[Unit]() {
          override def run(): Unit = {
            runMain(childArgs, childClasspath, sysProps, childMainClass, args.verbose)
      } catch {
        case e: Exception =>
          // Hadoop's AuthorizationException suppresses the exception's stack trace, which
          // makes the message printed to the output by the JVM not very helpful. Instead,
          // detect exceptions with empty stack traces here, and treat them differently.
          if (e.getStackTrace().length == 0) {
            // scalastyle:off println
            printStream.println(s"ERROR: ${e.getClass().getName()}: ${e.getMessage()}")
            // scalastyle:on println
            exitFn(1)
          } else {
            throw e
    } else {
      runMain(childArgs, childClasspath, sysProps, childMainClass, args.verbose)
  }

for (jar <- childClasspath) {
  addJarToClasspath(jar, loader)
}

mainClass = Utils.classForName(childMainClass)

val mainMethod = mainClass.getMethod("main", new Array[String](0).getClass)

mainMethod.invoke(null, childArgs.toArray)