flink入门实例-Windows下本地模式跑SocketWordCount

一般情况下,开发大数据处理程序,我们希望能够在本地编写代码并调试通过,能够在本地进行数据测试,然后在生产环境去跑“大”数据。

一、nc工具

配置windows的nc端口,在网上下载nc.exe(https://eternallybored.org/misc/netcat/)

flink入门实例-Windows下本地模式跑SocketWordCount_第1张图片

使用命令开始nc制定端口为9000(nc -L -p 9000 -v) 启动插件

二、idea中配置,代码以及设置参数

flink入门实例-Windows下本地模式跑SocketWordCount_第2张图片

maven配置:

xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0modelVersion>

    <groupId>limsgroupId>
    <artifactId>flink-projectartifactId>
    <version>1.0-SNAPSHOTversion>

    <properties>
        <flink.version>1.7.2flink.version>
    properties>

    <dependencies>
        
        <dependency>
            <groupId>log4jgroupId>
            <artifactId>log4jartifactId>
            <version>1.2.17version>
        dependency>

        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-javaartifactId>
            <version>${flink.version}version>
        dependency>
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-streaming-java_2.11artifactId>
            <version>${flink.version}version>
        dependency>
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-clients_2.11artifactId>
            <version>${flink.version}version>
        dependency>
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-connector-wikiedits_2.11artifactId>
            <version>${flink.version}version>
        dependency>
    dependencies>

project>
WordCount:
package flink;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.Collector;


/**
 * @Description: TODO
 * @Date: 2019/2/25 23:49
 */
public class WordCount {
    public static void main(String[] args) throws Exception {
        //定义socket的端口号
        int port;
        try{
            ParameterTool parameterTool = ParameterTool.fromArgs(args);
            port = parameterTool.getInt("port");
        }catch (Exception e){
            System.err.println("没有指定port参数,使用默认值9000");
            port = 9000;
        }

        //获取运行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        //连接socket获取输入的数据
        DataStreamSource text = env.socketTextStream("127.0.0.1", port, "\n");

        //计算数据
        DataStream windowCount = text.flatMap(new FlatMapFunction() {
            public void flatMap(String value, Collector out) throws Exception {
                String[] splits = value.split("\\s");
                for (String word:splits) {
                    out.collect(new WordWithCount(word,1L));
                }
            }
        })//打平操作,把每行的单词转为类型的数据
                .keyBy("word")//针对相同的word数据进行分组
                .timeWindow(Time.seconds(2),Time.seconds(1))//指定计算数据的窗口大小和滑动窗口大小
                .sum("count");

        //把数据打印到控制台
        windowCount.print()
                .setParallelism(1);//使用一个并行度
        //注意:因为flink是懒加载的,所以必须调用execute方法,上面的代码才会执行
        env.execute("streaming word count");

    }

    /**
     * 主要为了存储单词以及单词出现的次数
     */
    public static class WordWithCount{
        public String word;
        public long count;
        public WordWithCount(){}
        public WordWithCount(String word, long count) {
            this.word = word;
            this.count = count;
        }

        @Override
        public String toString() {
            return "WordWithCount{" +
                    "word='" + word + '\'' +
                    ", count=" + count +
                    '}';
        }
    }
}

三、运行结果

cmd中输入单词,空格分割,并换行,在idea的控制台中观察输出

flink入门实例-Windows下本地模式跑SocketWordCount_第3张图片

flink入门实例-Windows下本地模式跑SocketWordCount_第4张图片

 

本地开发调试实例完成

转载于:https://www.cnblogs.com/limaosheng/p/10434848.html

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