spark常见转换算子（transformation）的操作

package com.meng.nan.day717

import org.apache.log4j.{Level, Logger}
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.rdd.RDD

import scala.collection.mutable.ArrayBuffer
//常见转换算子（transformation）的操作例如
//map,flatmap,join，sample等

object flatMapClass {
  def main(args: Array[String]): Unit = {
    Logger.getLogger("org.apache.spark").setLevel(Level.WARN)
    Logger.getLogger("org.apache.hadoop").setLevel(Level.WARN)
    Logger.getLogger("org.spark_project").setLevel(Level.WARN)
val  conf=new SparkConf()
  .setAppName("flatMapClass")
  .setMaster("local[*]");
    val sc=new SparkContext(conf)
    val list=List("safdasd")
    val rdd:RDD[String]=sc.parallelize(list)
   //字符串拆分flatMap（）
    val chrdd:RDD[(Char,Int)]=rdd.flatMap(str=>{
    val ab=ArrayBuffer[(Char,Int)]()
    for (ch<- str){
          ab.append((ch,1))
          }
          ab
          })
//    chrdd.foreach(ch=>println(ch))

    //字符串一一映射map
    val list1=1 to 9
    val lsrdd:RDD[Int]=sc.parallelize(list1)
//        val mapRDD=lsrdd.map(num=>num * 7)
//        println("partitions"+mapRDD.getNumPartitions)
//        mapRDD.foreach(println)
//        val mapRDD=lsrdd.map(num=>(num,1))
//        val mapRDD=lsrdd.map((_,1))
//        for (sc<-mapRDD){
//        println(sc)
//        }
        //filter过滤
//        val flterRdd=lsrdd.filter(fl=>(fl%2==0))
//        flterRdd.foreach(println)
    //union联合操作
      val list2=List(3,1,2,2,11,22,33,44)
      val lr:RDD[Int]=sc.parallelize(list2)
      val unRDD:RDD[Int]=lsrdd.union(lr)
      unRDD.foreach(println)
//      抽样算子sample
//      val smRDD=lsrdd.sample(false,0.2)
//      smRDD.foreach(println)
//      println(smRDD.count())


  }
}

package com.meng.nan.day717

import org.apache.log4j.{Level, Logger}
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.rdd.RDD

object JionClass {
  def main(args: Array[String]): Unit = {
    Logger.getLogger("org.apache.spark").setLevel(Level.WARN)
    Logger.getLogger("org.apache.hadoop").setLevel(Level.WARN)
    Logger.getLogger("org.spark_project").setLevel(Level.WARN)
//转换算子join操作所有的join操作，必须要求的RDD的类型时
    //     * K就是关联字段
val conf=new SparkConf()
      .setMaster("local[*]")
      .setAppName("JionClass")
    val sc=new SparkContext(conf)
jionOps(sc)
  }
  def jionOps(sc:SparkContext): Unit ={
val stu=List(
  "1 刘冯曼娜 22 bd-1901-bj",
  "2 常师 25 bd-1901-bj",
  "3 张熹 24 bd-1901-sz",
  "4 胡盼 18 bd-1901-wh"
)
    val scores = List(
      "1 1 math 82",
      "2 1 english 0",
      "3 2 chinese 85.5",
      "4 3 PE 99",
      "5 10 math 99"
    )



    //将字符串转为RDD形式
    val stuRDD:RDD[String]=sc.parallelize(stu)
    val scoresRDD:RDD[String]=sc.parallelize(scores)
    //查询所有学生信息
    //将学生表转化为map集合
    val stuMapRDD:RDD[(String,String)]=stuRDD.map(stringLine=>{
      val sid=stringLine.substring(0,1)
      val stuInf=stringLine.substring(1).trim
      (sid,stuInf)
    })
   //将成绩表转化为map集合
    val scoresMapRDD:RDD[(String,String)]=scoresRDD.map(scorLine=>{
      val filter=scorLine.split("\\s+")
      val sid=filter(1)
      val scoreInfo=filter(2)+" "+filter(3)
      (sid,scoreInfo)
    })
//    //join操作
    val joinRDD:RDD[(String,(String,String))]=stuMapRDD.join(scoresMapRDD)
joinRDD.foreach{case (sid,(stuInf,scoreInfo))=>{
      println(s"sid:${sid}\tstuInf:${stuInf}\tscoreInfo:${scoreInfo}")

    }}
println("======================")
    //左连接查询
    val leftJoin:RDD[(String,(String,Option[String]))]=stuMapRDD.leftOuterJoin(scoresMapRDD)
   leftJoin.foreach { case (sid, (stuInf, scoreInfo)) => {
     println(s"sid${sid}\tstuInf:${stuInf}\tscoreInfo:${scoreInfo}")
   }
   }
    println("================================")
    //全连接
val fullMapJoin:RDD[(String,(Option[String],Option[String]))]=stuMapRDD.fullOuterJoin(scoresMapRDD)
    fullMapJoin.foreach{case (sid,(stuInf,scoreInfo))=>{
      println(s"sid:${sid}\tstuInfo:${stuInf}\tscoreInfo:${scoreInfo}")
    }}

  }
}