Operator_countByValue
package com.bjsxt.spark.actions;
import java.util.Arrays;
import java.util.Map;
import java.util.Map.Entry;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import scala.Tuple2;
/**
* countByValue
* 根据数据集每个元素相同的内容来计数。返回相同内容的元素对应的条数。
*
* @author root
*
*/
public class Operator_countByValue {
public static void main(String[] args) {
SparkConf conf = new SparkConf();
conf.setMaster("local").setAppName("countByKey");
JavaSparkContext sc = new JavaSparkContext(conf);
JavaPairRDD<Integer, String> parallelizePairs = sc.parallelizePairs(Arrays.asList(
new Tuple2<Integer,String>(1,"a"),
new Tuple2<Integer,String>(2,"b"),
new Tuple2<Integer,String>(2,"c"),
new Tuple2<Integer,String>(3,"c"),
new Tuple2<Integer,String>(4,"d"),
new Tuple2<Integer,String>(4,"d")
));
Map<Tuple2<Integer, String>, Long> countByValue = parallelizePairs.countByValue();
for(Entry<Tuple2<Integer, String>, Long> entry : countByValue.entrySet()){
System.out.println("key:"+entry.getKey()+",value:"+entry.getValue());
}
}
}