针对 K,V 格式的 RDD,该函数对 K,V 格式 RDD 中的 value 做操作，返回是 K,V 格式的 RDD.

1. java

package transformations;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import scala.Tuple2;

import java.util.Arrays;

/**
 * @Author yqq
 * @Date 2021/12/10 00:25
 * @Version 1.0
 */
public class MapValueTest {
    public static void main(String[] args) {
        JavaSparkContext context = new JavaSparkContext(
                new SparkConf()
                        .setMaster("local")
                        .setAppName("mapValue")
        );
        context.setLogLevel("Error");
        context.parallelizePairs(Arrays.asList(
                new Tuple2<>("科比",10),
                new Tuple2<>("詹姆斯",11),
                new Tuple2<>("乔丹",12),
                new Tuple2<>("保罗",13),
                new Tuple2<>("威斯布鲁克",14)
        )).mapValues(e->e+100).foreach(e-> System.out.println(e));
    }
}

2. scala

package transformation

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

/**
 * @Author yqq
 * @Date 2021/12/10 00:35
 * @Version 1.0
 */
object MapValueTest {
  def main(args: Array[String]): Unit = {
    val context = new SparkContext(
      new SparkConf()
        .setAppName("MapValue")
        .setMaster("local")
    )
    context.setLogLevel("Error")
    context.parallelize(Array[(String,Int)](
      ("科比",10),
      ("詹姆斯",11),
      ("乔丹",12),
      ("保罗",13),
      ("威斯布鲁克",14)
    )).mapValues(e=>e+"NBA").foreach(println)
  }
}