wordCount1 (groupByKey)

package com.atguigu

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

object Trans {
  def main(args: Array[String]): Unit = {

    val conf: SparkConf = new SparkConf().setMaster("local[*]").setAppName("Spark01_Partition")
    //构建spark上下文对象
    val sc = new SparkContext(conf)

   val rdd: RDD[(String, Int)] = sc.makeRDD(Array(("aaa",1),("cc",2),("b",4),("b",1),("b",1)))
    val rdd2: RDD[(String, Iterable[Int])] = rdd.groupByKey()
    val rdd3: RDD[(String, Int)] = rdd2.map {
      case (key, items) => {
        (key, items.sum)
      }
    }
    rdd3.collect().foreach(println)
    sc.stop()
  }
}

(cc,2)
(aaa,1)
(b,6)

不使用模式匹配

package com.atguigu

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

object Trans {
  def main(args: Array[String]): Unit = {

    val conf: SparkConf = new SparkConf().setMaster("local[*]").setAppName("Spark01_Partition")
    //构建spark上下文对象
    val sc = new SparkContext(conf)

   val rdd: RDD[(String, Int)] = sc.makeRDD(Array(("aaa",1),("cc",2),("b",4),("b",1),("b",1)))
    val rdd2: RDD[(String, Iterable[Int])] = rdd.groupByKey()
    val rdd3: RDD[(String, Int)] = rdd2.map {
      t => {
        (t._1, t._2.sum)
      }
    }

    rdd3.collect().foreach(println)
    sc.stop()
  }
}

(cc,2)
(aaa,1)
(b,6)