spark stream 应用-结合hdfs

本文章主要通过spark streaming 统计hadoop的文件,实现wordcount

import java.util.Arrays;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.streaming.Durations;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaPairDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;

import scala.Tuple2;

/**
 * 基于HDFS文件的实时wordcount程序
 * @author Administrator
 *
 */
public class HDFSWordCount {

   public static void main(String[] args) {
      SparkConf conf = new SparkConf()
            .setMaster("local[2]")
            .setAppName("HDFSWordCount");  
      JavaStreamingContext jssc = new JavaStreamingContext(conf, Durations.seconds(5));
      
      // 首先，使用JavaStreamingContext的textFileStream()方法，针对HDFS目录创建输入数据流
      JavaDStream<String> lines = jssc.textFileStream("hdfs://spark1:9000/wordcount_dir");
      
      // 执行wordcount操作
      JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {

         private static final long serialVersionUID = 1L;

         @Override
         public Iterable<String> call(String line) throws Exception {
            return Arrays.asList(line.split(" "));
         }
         
      });
      
      JavaPairDStream<String, Integer> pairs = words.mapToPair(
            
            new PairFunction<String, String, Integer>() {

               private static final long serialVersionUID = 1L;

               @Override
               public Tuple2<String, Integer> call(String word)
                     throws Exception {
                  return new Tuple2<String, Integer>(word, 1);
               }
               
            });
      
      JavaPairDStream<String, Integer> wordCounts = pairs.reduceByKey(
            
            new Function2<Integer, Integer, Integer>() {

               private static final long serialVersionUID = 1L;

               @Override
               public Integer call(Integer v1, Integer v2) throws Exception {
                  return v1 + v2;
               }
               
            });
      
      wordCounts.print();
      
      jssc.start();
      jssc.awaitTermination();
      jssc.close();
   }
   
}