spark考察线程和任务的对应关系

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

    /**
      * RDD再分区
      */
    object RDDRepartition {
        def main(args: Array[String]): Unit = {
            val conf = new SparkConf()
            conf.setAppName("rdddemo")
            conf.setMaster("local[3]")

            val sc = new SparkContext(conf)
            val rdd1 = sc.makeRDD((1 to 10) , 5)
            println("rdd1'pars : " + rdd1.partitions.length)
            val rdd2 = rdd1.map(e=>{
                val tid = Thread.currentThread().getId
                val tname = Thread.currentThread().getName
                printf("%d/%s : %d\r\n" , tid , tname , e)
                e
            })
            println("rdd2'pars : " + rdd2.partitions.length)
            rdd2.collect()
            while(true){
                Thread.sleep(1000)
            }
        }
    }

    //执行结果
    46/Executor task launch worker for task 0 : 1
    46/Executor task launch worker for task 0 : 2
    46/Executor task launch worker for task 3 : 7
    46/Executor task launch worker for task 3 : 8

    47/Executor task launch worker for task 1 : 3
    47/Executor task launch worker for task 1 : 4
    47/Executor task launch worker for task 4 : 9
    47/Executor task launch worker for task 4 : 10

    48/Executor task launch worker for task 2 : 5
    48/Executor task launch worker for task 2 : 6