数据处理案例一之"求同存异"

1. 数据
   a.txt:
   u1 12 zs
   u2 15 xx
   u3 18 aaa
   u4 20 xa1
   u5 22 xa2

b.txt
u1 2016 9 m1
u2 2017 12 m2
u3 2017 1 m3
u3 2014 2 m4
u3 2012 3 m5
2. 需求
两个数据集：
数据集A id,age,name
数据集B id,year,month,movie
数据集都是使用空格来分割的

要求，输出：id,age,name,year,month,movie(同一个用户，按year升序，没有数据B的id，用null补

1. 逻辑

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

import scala.collection.mutable

object DealDataExample1_3 {
  def main(args: Array[String]): Unit = {
    if (args.length!=3){
      println("cn.edu360.Example.DealDataExample1 
")
      sys.exit()
    }
    //输入参数
    val Array(input1,input2,output)=args
    val conf = new SparkConf()
    conf.setMaster("local")
    conf.setAppName(DealDataExample1_1.getClass.getSimpleName)
    val sc = new SparkContext(conf)
    //获取数据
    val data1: RDD[String] = sc.textFile(input1)
    val data2: RDD[String] = sc.textFile(input2)
    //切割数据
    val cutRes1: RDD[(String, String)] = data1.map({
      t =>
        val res = t.split(" ", 2)
        val id: String = res(0)
        val values: String = res(1)
        //println(s"id=${id},values=${values}")
        (id, values)
    })
    val cutRes2: RDD[(String, String)] = data2.map({
      t =>
        val res = t.split(" ", 2)
        val id: String = res(0)
        val values: String = res(1)
        //println(s"id=${id},values=${values}")
        (id, values)
    })
    //println(cutRes2.collect().toBuffer)
    //组合数据
    val combyRes: RDD[(String, (Iterable[String], Iterable[String]))] = cutRes1.cogroup(cutRes2)
    //println(combyRes.collect().toBuffer)
    //(u4,(CompactBuffer(20 xa1),CompactBuffer()))
    //数据预处理
    val dealRes: RDD[(String, String)] = combyRes.map({
      t =>
      (t._1, t._2._1.toString().concat(",").concat(t._2._2.toString()))
    })
    //println(dealRes.collect().toBuffer)
    //以key分组
    val groupRes: RDD[(String, Iterable[String])] = dealRes.groupByKey(1)
    val selectRes: RDD[(String, String)] = groupRes.mapValues({
      t =>
        val userMsg = t.head
        val movieMsg = t.tail
        val movieData: String = if (movieMsg.isEmpty) {
          "null,null,null"
        } else {
          movieMsg.toList.sortBy(_.split(" ")(0)).mkString(" ")
        }
        userMsg.concat(",").concat(movieData)
    })
    println(selectRes.collect().toBuffer)
    sc.stop()
  }
}

1. 结果
   u1 12 zs,2016 9 m1
   u2 15 xx,2017 12 m2
   u3 18 aaa,2012 3 m5 2014 2 m4 2017 1 m3
   u4 20 xa1,null,null,null
   u5 22 xa2,null,null,null