4、Flink流处理案例实现-Java

在Flink项目里面创建一个包，同时新建一个wordcount类

package com.gong.stream;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.util.Collector;

public class WordCount {
    public static void main(String[] args) throws Exception{
        //解析命令行传过来的参数args
        ParameterTool params=ParameterTool.fromArgs(args);

        //获取一个flink的执行环境
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

        DataStream<String> dataStream = null;
        if(params.has("input")) {//判断参数是否带有input
             dataStream=env.readTextFile(params.get("input"));
        }else {
            System.out.println("数据不存在");
        }
        //数据统计单词词频
        DataStream<Tuple2<String,Integer>> counts=  dataStream.flatMap(new Tokenizer())
                .keyBy(0)
                .sum(1);

        if(params.has("output")){
            counts.writeAsText(params.get("output"));
        }else {
            counts.print();
        }
        env.execute("Streaming wordcount ");

    }

    public static final class Tokenizer implements FlatMapFunction<String, Tuple2<String,Integer>> {
        @Override
        public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {
            String[] tokens =value.toLowerCase().split("\W+");
            for (String token:tokens){
                out.collect(new Tuple2<>(token,1));
            }
        }
    }
}