sparkStream---1

1.本地scala版

import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.StreamingContext._

object SparkStreamingDemo {
  def main(args: Array[String]): Unit = {
    //local[n] n > 1
    val conf = new SparkConf().setMaster("local[2]").setAppName("NetworkWordCount")
    //创建Spark流上下文,批次时长是1s
    val ssc = new StreamingContext(conf, Seconds())

    //创建socket文本流
    val lines = ssc.socketTextStream("localhost", )
    //压扁
    val words = lines.flatMap(_.split(" "))
    //变换成对偶
    val pairs = words.map((_,));

    val count = pairs.reduceByKey(_+_) ;
    count.print()

    //启动
    ssc.start()

    //等待结束
    ssc.awaitTermination()
  }
}

2.java版的，本地

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.Optional;
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.Seconds;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaPairDStream;
import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import scala.Some;
import scala.Tuple2;

import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

/**
 * Created by Administrator on 2017/4/3.
 */
public class JavaSparkStreamingWordCountApp {
    public static void main(String[] args) throws Exception {
        SparkConf conf = new SparkConf();
        conf.setAppName("wc");
        conf.setMaster("local[4]");
        //创建Spark流应用上下文
        JavaStreamingContext jsc = new JavaStreamingContext(conf, Seconds.apply());

        jsc.checkpoint("file:///d:/scala/check");
        //创建socket离散流
        JavaReceiverInputDStream sock = jsc.socketTextStream("localhost",);
        //压扁
        JavaDStream<String> wordsDS = sock.flatMap(new FlatMapFunction<String,String>() {
            public Iterator call(String str) throws Exception {
                List<String> list = new ArrayList<String>() ;
                String[] arr = str.split(" ");
                for(String s : arr){
                    list.add(s);
                }
                return list.iterator();
            }
        });

        //映射成元组
        JavaPairDStream<String,Integer> pairDS = wordsDS.mapToPair(new PairFunction<String, String, Integer>() {
            public Tuple2<String, Integer> call(String s) throws Exception {
                return new Tuple2<String,Integer>(s,);
            }
        }) ;

        JavaPairDStream<String,Integer> jps = pairDS.updateStateByKey(new Function2<List<Integer>, Optional<Integer>, Optional<Integer>>() {
            public Optional<Integer> call(List<Integer> v1, Optional<Integer> v2) throws Exception {
                Integer newCount = v2.isPresent() ? v2.get() :   ;

                System.out.println("old value : " + newCount);
                for(Integer i : v1){
                    System.out.println("new value : " + i);
                    newCount = newCount +  i;
                }
                return Optional.of(newCount);
            }
        });

        //聚合
        JavaPairDStream<String,Integer> countDS = jps.reduceByKey(new Function2<Integer, Integer, Integer>() {
            public Integer call(Integer v1, Integer v2) throws Exception {
                return v1 + v2;
            }
        });

        //打印
        countDS.print();

        jsc.start();

        jsc.awaitTermination();

        jsc.stop();
    }
}

3.集群跑。

将文件打成jar包，放到远程机器中

spark-submit --name wcstreaming
                --class com.spark.java.JavaSparkStreamingWordCountApp 
                  //上面是包名加类名
                --master spark://s201:7077
                SparkDemo1-1.0-SNAPSHOT.jar