java实现spark常用算子之cogroup

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.VoidFunction;
import scala.Tuple2;
import java.util.Arrays;
import java.util.List;

/**
 *  cogroup(otherDataSet,[numTasks]) 算子：
 *  将两个RDD中的数据按照key进行汇总：
 *      第一个RDD按照key进行汇总，结果放在iterable中。
 *      第二个RDD同样按照key进行汇总，结果放在另一个iterable中。
 *      最后得到一个key和两个iterable的数据。
 */
public class CogroupOperator {
    public static void main(String[] args) {
        SparkConf conf = new SparkConf().setMaster("local").setAppName("cogroup");
        JavaSparkContext sc = new JavaSparkContext(conf);
        List<Tuple2<String,String>> stus = Arrays.asList(
                new Tuple2<>("w1","z1"),
                new Tuple2<>("w2","z2"),
                new Tuple2<>("w3","z3"),
                new Tuple2<>("w2","z2"),
                new Tuple2<>("w1","z1")
        );
        List<Tuple2<String,String>> scores = Arrays.asList(
                new Tuple2<>("w1","100"),
                new Tuple2<>("w2","10"),
                new Tuple2<>("w3","1"),
                new Tuple2<>("w2","90"),
                new Tuple2<>("w1","900")
        );
        JavaPairRDD<String,String> stusrdd = sc.parallelizePairs(stus);
        JavaPairRDD<String,String> scorerdd = sc.parallelizePairs(scores);

        JavaPairRDD<String,Tuple2<Iterable<String>,Iterable<String>>> result = stusrdd.cogroup(scorerdd,2);


        result.foreach(new VoidFunction<Tuple2<String, Tuple2<Iterable<String>, Iterable<String>>>>() {
            @Override
            public void call(Tuple2<String, Tuple2<Iterable<String>, Iterable<String>>> tuple) throws Exception {
                System.err.println("key:"+tuple._1+",另外两个iterable中的数据:"+tuple._2);
            }
        });
    }
}

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