Spark作业提交和DAG调度器生成Task

1. RDD action => SparkContext.runJob(rdd: RDD[T], func: Iterator[T] => U)
2. runJob() => dagScheduler.runJob: 对所有Partitions应用一个函数做变换，返回结果，是所有RDD action的主进入点。
3. DAGScheduler.runJob => submitJob()并返回一个future => eventProcessLoop.post(JobSubmitted) 发布事件并等待完成
4. eventProcessLoop.onReceive(event) => doOnReceive(event) => handleJobSubmitted() => createResultStage(finalRDD, func, partitions, jobId, callSite) => 创建ActiveJob => submitStage(finalStage)
5. submitStage(stage) => 递归提交missing parent stages, 根据RDD的依赖关系构建DAG => submitMissingTasks(stage, jobId.get)
   => taskScheduler.submitTasks(new TaskSet(tasks.toArray, stage.id, stage.latestInfo.attemptId, jobId, properties))
6. submitWaitingChildStages(stage)