Ubuntu20.04安装配置zookeeper和kafka，并使用flink读取kafka流数据存入MySQL

由于业务需求，最近开始学习大数据，主要是kafka和flink操作，在前期环境搭建过程中走了很多弯路，踩了很多坑，这里把自己遇到的所有问题都罗列出来，并将从环境搭建到demo运行成功的整个过程记录下来，方便自己以后查看，也希望能给网友们一些参考。

开发环境

系统： Ubuntu 20.04

软件架构：JDK 15.0.2 + zookeeper 3.6.2 + kafka 2.7.0 + flink 1.12.2 + mysql 8 + Maven 3.6.3

IDE：IDEA + navicat

1. 安装JDK

从官网下载jdk工具包jdk工具包。
选择最新的15就行，

选择bin.tar版本，下载完后保存在/opt目录下并解压，然后设置环境变量。

tar -xvf jdk-15.0.2_linux-x64_bin.tar.gz
vim /etc/profile
export JAVA_HOME=/opt/jdk-15.0.2
export CLASSPATH=.
export PATH=$JAVA_HOME/bin:$PATH
source /etc/profile

可以输入 java -version查看是否配置成功。

这里最好重启一下，不然后面输入命令可能会找不到。

2. 安装zookeeper

解压下载好的tar.gz安装包到某个目录下，我直接解压到了/home目录，可使用命令

tar -xvf apache-zookeeper-3.6.2-bin

进入解压目录的conf目录，复制配置文件zoo_sample.cfg并命名为zoo.cfg，
只需要改数据存储目录和日志文件目录，新建data和logs文件夹。

# 增加dataDir和dataLogDir目录，目录自己创建并指定，用作数据存储目录和日志文件目录
dataDir=/home/superlinc/zookeeper/data
dataLogDir=/home/superlinc/zookeeper/logs

配置系统环境变量

sudo vim /etc/profile

添加

export ZOOKEEPER_HOME=/home/superlinc/zookeeper
PATH=$ZOOKEEPER_HOME/bin:$PATH

source /etc/profile

这样就安装配置好啦。

启动

sudo ./bin/zkServer.sh start

如果想看具体的信息，可以

sudo ./bin/zkServer.sh start-foreground

如果你已经启动了一次，以后再启动或者端口2181被占用就会出现“地址已在使用”错误，

Caused by: java.net.BindException: 地址已在使用

可以查看占用该端口的进程并杀掉该进程

sudo netstat -ap | grep 2181

sudo kill 11051

重新启动就OK啦。

3. 安装kafka

安装kafka就很简单了，同样解压到/home下。

tar -xvf kafka_2.12-2.7.0.tgz

进入config目录，只要修改server.properties一句。

log.dirs=/home/superlinc/kafka/logs

由于我们已经启动了zookeeper，直接输入以下命令就行，

sudo ./bin/kafka-server-start.sh config/server.properties

当强行关闭kafka集群或zookeeper集群时，重新启动时经常会出现异常 kafka.common.InconsistentClusterIdException

直接删除zookeeper下的data和logs目录以及kafka下的logs目录，然后重新启动zookeeper和kafka。

• 删除日志目录logs下的meta.properties文件
• 重启Kafka

4. 安装flink

同样解压到/home下。

tar -xvf flink-1.12.2-bin-scala_2.11.tgz
sudo ./bin/start-cluster.sh

启动好了之后访问 http://localhost:8081

5. 安装MySQL

可以参考这篇博客
添加链接描述
主要问题是如何实现远程连接。

6. 编写第一个flink+kafka程序

maven 依赖

<properties>
        <maven.compiler.source>15maven.compiler.source>
        <maven.compiler.target>15maven.compiler.target>
        <flink.version>1.11.0flink.version>
        <java.version>1.15java.version>
        <scala.binary.version>2.11scala.binary.version>
    properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-javaartifactId>
            <version>${flink.version}version>
            <scope>providedscope>
        dependency>
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-streaming-java_${scala.binary.version}artifactId>
            <version>${flink.version}version>
            <scope>providedscope>
        dependency>
        
        <dependency>
            <groupId>org.slf4jgroupId>
            <artifactId>slf4j-log4j12artifactId>
            <version>1.7.30version>
            <scope>runtimescope>
        dependency>
        <dependency>
            <groupId>log4jgroupId>
            <artifactId>log4jartifactId>
            <version>1.2.17version>
            <scope>runtimescope>
        dependency>
        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-connector-kafka-0.11_${scala.binary.version}artifactId>
            <version>${flink.version}version>
        dependency>
        
        <dependency>
            <groupId>com.alibabagroupId>
            <artifactId>fastjsonartifactId>
            <version>1.2.51version>
        dependency>
        <dependency>
            <groupId>mysqlgroupId>
            <artifactId>mysql-connector-javaartifactId>
            <version>8.0.22version>
        dependency>
    dependencies>

首先用Navicat连接MySQL，然后创建一张表"student"，

DROP TABLE IF EXISTS `student`;
CREATE TABLE `student` (
  `id` int(11) unsigned NOT NULL AUTO_INCREMENT,
  `name` varchar(25) COLLATE utf8_bin DEFAULT NULL,
  `password` varchar(25) COLLATE utf8_bin DEFAULT NULL,
  `age` int(10) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=utf8 COLLATE=utf8_bin;

创建学生类

package com.linc.flink;

public class Student {
    public int id;
    public String name;
    public String password;
    public int age;

    public Student() {
    }

    public Student(int id, String name, String password, int age) {
        this.id = id;
        this.name = name;
        this.password = password;
        this.age = age;
    }

    @Override
    public String toString() {
        return "Student{" +
                "id=" + id +
                ", name='" + name + '\'' +
                ", password='" + password + '\'' +
                ", age=" + age +
                '}';
    }

    public int getId() {
        return id;
    }

    public void setId(int id) {
        this.id = id;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public String getPassword() {
        return password;
    }

    public void setPassword(String password) {
        this.password = password;
    }

    public int getAge() {
        return age;
    }

    public void setAge(int age) {
        this.age = age;
    }
}

创建kafka类

package com.linc.flink;

import com.alibaba.fastjson.JSON;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;

import java.util.HashMap;
import java.util.Map;
import java.util.Properties;

public class KafkaUtils {
    public static final String broker_list = "localhost:9092";
    public static final String topic = "student";  //kafka topic 需要和 flink 程序用同一个 topic

    public static void writeToKafka() throws InterruptedException {
        Properties props = new Properties();
        props.put("bootstrap.servers", broker_list);
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        KafkaProducer producer = new KafkaProducer<String, String>(props);

        for (int i = 1; i <= 100; i++) {
            Student student = new Student(i, "linc" + i, "password" + i, 18 + i);
            ProducerRecord record = new ProducerRecord<String, String>(topic, null, null, JSON.toJSONString(student));
            producer.send(record);
            System.out.println("发送数据: " + JSON.toJSONString(student));
        }
        producer.flush();
    }

    public static void main(String[] args) throws InterruptedException {
        writeToKafka();
    }
}

SinkToMySQL

package com.linc.flink;

import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;

public class SinkToMySQL extends RichSinkFunction<Student> {
    PreparedStatement ps;
    private Connection connection;

    /**
     * open() 方法中建立连接，这样不用每次 invoke 的时候都要建立连接和释放连接
     *
     * @param parameters
     * @throws Exception
     */
    @Override
    public void open(Configuration parameters) throws Exception {
        super.open(parameters);
        connection = getConnection();
        String sql = "insert into student(id, name, password, age) values(?, ?, ?, ?);";
        ps = this.connection.prepareStatement(sql);
    }

    @Override
    public void close() throws Exception {
        super.close();
        //关闭连接和释放资源
        if (connection != null) {
            connection.close();
        }
        if (ps != null) {
            ps.close();
        }
    }

    /**
     * 每条数据的插入都要调用一次 invoke() 方法
     *
     * @param value
     * @param context
     * @throws Exception
     */
    @Override
    public void invoke(Student value, Context context) throws Exception {
        //组装数据，执行插入操作
        ps.setInt(1, value.getId());
        ps.setString(2, value.getName());
        ps.setString(3, value.getPassword());
        ps.setInt(4, value.getAge());
        ps.executeUpdate();
    }

    private static Connection getConnection() {
        Connection con = null;
        try {
            Class.forName("com.mysql.cj.jdbc.Driver");
            con = DriverManager.getConnection("jdbc:mysql://localhost:3306/mysql?useUnicode=true&characterEncoding=UTF-8", "root", "root");
        } catch (Exception e) {
            System.out.println("-----------mysql get connection has exception , msg = "+ e.getMessage());
        }
        return con;
    }
}

flink主程序

package com.linc.flink;

import com.alibaba.fastjson.JSON;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.sink.PrintSinkFunction;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011;

import java.util.Properties;

public class Main {
    public static void main(String[] args) throws Exception {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        Properties props = new Properties();
        props.put("bootstrap.servers", "localhost:9092");
        props.put("zookeeper.connect", "localhost:2181");
        props.put("group.id", "metric-group");
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("auto.offset.reset", "latest");

        SingleOutputStreamOperator<Student> student = env.addSource(new FlinkKafkaConsumer011<>(
                "student",   //这个 kafka topic 需要和上面的工具类的 topic 一致
                new SimpleStringSchema(),
                props)).setParallelism(1)
                .map(string -> JSON.parseObject(string, Student.class)); //Fastjson 解析字符串成 student 对象

        student.addSink(new SinkToMySQL()); //数据 sink 到 mysql

        env.execute("Flink add sink");
    }
}

结果

运行 Flink 主程序，然后再运行 KafkaUtils.java 工具类
如果出现以下错误，
java.lang.NoClassDefFoundError: org/apache/flink/api/common/serialization/DeserializationSchema，
导入flink中lib下的jar包即可。

运行结果：

MySQL结果：