package spark; 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 org.apache.spark.sql.SparkSession; import scala.Tuple2; import java.util.Arrays; import java.util.List; /** * Created by kkxwz on 2018/5/24 */ public class WordCountApp { public static void main(String[] args) { // //spark 2.0版本之前 // SparkConf sparkConf = new SparkConf().setAppName("WordCountApp").setMaster("local[2]"); // JavaSparkContext spark = new JavaSparkContext(sparkConf); // JavaRDD<String> lines= spark.textFile("/Users/zl/data/sparksqldata/hello.txt"); // spark 2.0版本之后(建议) SparkSession spark = SparkSession.builder() .master("local[2]") .appName("WordCountApp") .getOrCreate(); JavaRDD<String> lines= spark.read().textFile("/Users/zl/data/sparksqldata/hello.txt").javaRDD(); JavaRDD<String> words = lines.flatMap(line -> Arrays.asList(line.split(" ")).iterator()); JavaPairRDD<String, Integer> counts = words .mapToPair(word -> new Tuple2<String, Integer>(word, 1)) .reduceByKey((x, y)-> x+y); //第一种输出方式: counts.foreach(count -> System.out.println(count._1() + ":" + count._2())); //第二种输出方式: // List<Tuple2<String, Integer>> output = counts.collect(); // // for(Tuple2<String, Integer> tuple : output){ // System.out.println(tuple._1() + ":" + tuple._2()); // } spark.stop(); } } // PS: // 1、jdk版本至少为1.8 // 2、最好关联源码,查看返回类型学习!!!