aggregateByKey.java

import java.util.*;
import scala.Tuple2;
import scala.Tuple3;
import org.apache.spark.util.StatCounter;
import org.apache.spark.api.java.*;
import org.apache.spark.SparkConf;

public class App {
    public static void main(String[] args) {
        SparkConf conf = new SparkConf().set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
        JavaSparkContext sc = new JavaSparkContext(conf);

        List myList = Arrays.asList(
                new Tuple2<>("A", 8),
                new Tuple2<>("B", 3),
                new Tuple2<>("C", 5),
                new Tuple2<>("A", 2),
                new Tuple2<>("B", 8));

        JavaPairRDD<String, Integer>  pairs = sc.parallelizePairs(myList);
        System.out.println(
            pairs
                .aggregateByKey(new StatCounter(), (acc, x) -> acc.merge(x), (acc1, acc2) -> acc1.merge(acc2))
                .map(x -> new Tuple3<>(x._1, x._2.mean(), x._2.stdev()))
                .collect()
        );
    }
}