第一章、Flink wordcount 入门示例

概述

希望通过本示例对flink 有一个轮廓性的认识

本示例实现效果：flink 连接 Socket Server，从Socker Server 中按行读取数据作为数据输入，将输入的数据根据空格切分、分组、求和，最终在控制台输出 各个词组出现的次数

前置条件

• Flink 集群
• 开发工具 Intellij idea
• 开发语言---本示例采用java

示例中采用的版本信息

• Flink 集群 ：flink-1.15.2
• JDK： 11
• spring boot版本：2.7.5

WordCount 程序

引入依赖

• 创建Maven Project，引入依赖
  

  <?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 https://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>2.7.5</version>
        <relativePath/> <!-- lookup parent from repository -->
    </parent>
  
  
    <groupId>com.bbx</groupId>
    <artifactId>flinkdemo2022</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <name>flinkdemo2022</name>
    <description>Demo project for Spring Boot</description>
    <properties>
        <java.version>11</java.version>
        <flink.version>1.15.2</flink.version>
        <scala.version></scala.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
  
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients</artifactId>
            <version>${flink.version}</version>
        </dependency>
    </dependencies>
  
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.1.1</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                    <archive>
                        <manifest>
                            <!--注意此处 是要运行的main 方法 -->
                            <mainClass>com.bbx.flinkdemo2022.wordconut.WcUnBoundStream</mainClass>
                        </manifest>
                    </archive>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
  </project>

创建flink 程序

• Flink 程序整体分为五部分
  
  1. 创建执行环境
  2. 配置输入数据源
  3. 数据加工处理
  4. 数据输出
  5. 启动执行
• WordCount 程序示例
  

  package com.bbx.flinkdemo2022.wordconut;
  import lombok.extern.slf4j.Slf4j;
  import org.apache.flink.api.common.typeinfo.Types;
  import org.apache.flink.api.java.tuple.Tuple2;
  import org.apache.flink.api.java.utils.ParameterTool;
  import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
  import org.apache.flink.util.Collector;
  import java.util.Arrays;
  
  @Slf4j
  public class WcUnBoundStream {
    public static void main(String[] args) throws Exception {
        //获取输入参数
        ParameterTool parameterTool = ParameterTool.fromArgs(args);
        String host = parameterTool.get("host");
        int port = parameterTool.getInt("port");
  
        //创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //获取输入源
        env.socketTextStream(host, port)
                //按照 空格进行分割
                .flatMap((String line, Collector<Tuple2<String, Long>> collector) -> {
                    Arrays.stream(line.split(" ")).forEach(j -> {
                        collector.collect(Tuple2.of(j, 1L));
                    });
                }).returns(Types.TUPLE(Types.STRING,Types.LONG))
                .keyBy(data -> data.f0)
                .sum(1)
                // 输出
                .print();
        // 启动执行
        env.execute("word count");
    }
  }

• 打包程序--将程序进行打包

启动Socket Server

• 在Linux 环境中通过 nc 命令启动
  

  nc -lk 3300      #本示例中执行该命令的主机IP为：192.168.10.131

提交job

Flink UI 端提交

• 访问Flink UI，点击“Submit New Job ”菜单中 “Add New” 按钮 选择程序包（flinkdemo2022-0.0.1-SNAPSHOT-jar-with-dependencies.jar）
  
• 配置必要的信息后提交
  
• 查看运行中job
• 在 Socket Server 端输入信息
  

  aaa bbb
  aaa qwe
  qwe aaa

• 点击 “Task Managers” 菜单选择 taskmanager 查看 Stdout中输出
  
• 取消任务
  

命令提交

• 提交命令
  

  ./bin/flink    run -c com.bbx.flinkdemo2022.wordconut.WcUnBoundStream  -p 2 flinkdemo2022-0.0.1-SNAPSHOT-jar-with-dependencies.jar --host 192.168.10.131 --port 3300

• 查看运行job
  

  ./bin/flink list

• 取消命令
  

  bin/flink cancel  9f4a7fb98ddaae95d3333f4cce46d8a8    # 9f4a7fb98ddaae95d3333f4cce46d8a8 为JobID，可以通过命令

• 命令指南
  

  ./bin/flink  -h

来自为知笔记(Wiz)