flink本地开发环境安装与部署（单机）

一、安装

1、下载地址

https://archive.apache.org/dist/flink/ 
本文选择的版本是：flink-1.13.0-bin-scala_2.12.tgz

2、解压文件

tar -zxvf flink-1.13.0-bin-scala_2.12.tgz -C /usr/local/myroom/

3、配置环境变量，在最后一行新增两个export

vi /etc/profile

export FLINK_HOME=/usr/local/myroom/flink-1.13.0
export PATH=$PATH:$FLINK_HOME/bin

4、重新加载，使配置立即生效

source /etc/profile

5、验证安装是否成功

flink --version

6、启动flink

start-cluster.sh
备注，停止命令是：stop-cluster.sh

7、查看相关进程是否启动

[root@single myroom]# jps
16931 TaskManagerRunner
16662 StandaloneSessionClusterEntrypoint
16952 Jps

8、页面访问

http://192.168.23.190:8081/

 二、部署

1、启动flink，如上面的第6步

2、准备程序，如下

package com.leiyuke.flink.datastream.demo.deploy;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

public class WordCount {

    public static void main(String[] args) throws Exception{

        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStream<String> dataStream = env.socketTextStream("192.168.23.190",9000,"\n");

        DataStream<Tuple2<String,Integer>> countData = dataStream
                .flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {

                String[] words = value.toLowerCase().split("\\W+");
                for(String word :words){
                    if(word.length() > 0){
                        out.collect(new Tuple2<>(word,1));
                    }
                }
            }
        }).keyBy(value -> value.f0)
                .sum(1);
        countData.print();
        env.execute("CountSocketWord");
    }
}

备注：pom.xml中与flink相关的依赖，scope设置为provided，因为服务器上lib中已经存在了

3、开启nc

nc -lk 9000

4、将程序打包上传，运行jar

1）方法1，界面操作

 2）方法2，执行命令

flink run -c com.leiyuke.flink.datastream.demo.deploy.WordCount lyk-flink-datastream-1.0-SNAPSHOT.jar

5、测试如下：

 6、停止任务

1）方法1，Jobs -> Running Jobs -> 点击Job Name列表对应的名字 -> 点击Cancel Job

 2）方法2，执行命令

flink cancel cbe33cb8315ca24884a0811a416894fe　　（这一串数字是上图的JobId）