Spark groupByKey、sortByKey、reduceByKey Java实现

本文通过一个具体的示例详细介绍了如何使用Apache Spark进行数据处理,包括创建JavaPairRDD、执行groupByKey、sortByKey、reduceByKey等操作,并展示了每一步操作后的结果。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.VoidFunction;
import scala.Tuple2;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

/**
 * Created by Knuth on 2018/2/2.
 */
public class TestGroupByKey {
    public static void main(String[] args) {
        //1.SparkConf
        SparkConf conf = new SparkConf().setAppName("TestSortByKey").setMaster("local");
        //2.JavaSparkContext
        JavaSparkContext jsc = new JavaSparkContext(conf);
        //3.JavaPairRDD
        List<Tuple2<String,Integer>> list = Arrays.asList(
                new Tuple2<String,Integer>("lmx",99),
                new Tuple2<String,Integer>("lt",98),
                new Tuple2<String,Integer>("lt",96),
                new Tuple2<String,Integer>("lmx",100),
                new Tuple2<String,Integer>("lmx",100),
                new Tuple2<String,Integer>("lt",99),
                new Tuple2<String,Integer>("lyx",100)
                );
        //4.JavaPairRDD
        JavaPairRDD<String,Integer> javaPairRDD = jsc.parallelizePairs(list);

        //5.groupByKey
        JavaPairRDD<String,Iterable<Integer>> groupRDD = javaPairRDD.groupByKey();

        //6.print
        groupRDD.foreach(new VoidFunction<Tuple2<String, Iterable<Integer>>>() {
            @Override
            public void call(Tuple2<String, Iterable<Integer>> tp) throws Exception {
                System.out.println(tp._1+":"+tp._2);
            }
        });

        //7.sortByKey
        JavaPairRDD<String,Integer> sortRDD = javaPairRDD.sortByKey();

        //8.print
        sortRDD.foreach(new VoidFunction<Tuple2<String, Integer>>() {
            @Override
            public void call(Tuple2<String, Integer> tp) throws Exception {
                System.out.println(tp._1+":"+tp._2);
            }
        });

        //9.reduceByKey
        JavaPairRDD<String,Integer> reduceRDD = javaPairRDD.reduceByKey(new Function2<Integer, Integer, Integer>() {
            @Override
            public Integer call(Integer a, Integer b) throws Exception {
                return a + b;
            }
        });

        //10.print
        reduceRDD.foreach(new VoidFunction<Tuple2<String, Integer>>() {
            @Override
            public void call(Tuple2<String, Integer> tp) throws Exception {
                System.out.println(tp._1+":"+tp._2);
            }
        });
        
    }
}
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值