实战：Flink1.12异步IO访问外部数据-Mysql

大数据开发运维架构 2021-08-18

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本文结合官网和网络资料，讲解 Flink 用于访问外部数据存储的异步 I/O API。对于不熟悉异步或者事件驱动编程的用户，建议先储备一些关于 Future 和事件驱动编程的知识。

Flink异步IO官方文档地址：

https://ci.apache.org/projects/flink/flink-docs-release-1.13/zh/docs/dev/datastream/operators/asyncio/
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我程序大体流程是，从socket流接收用户数据user（id,userNum,age三个字段），利用记录数据中的userNum字段，查询Mysql数据库用户姓名字典表userCode中的userName用户名，将查询出的userName字段，回填到user中，最后将回填的数据存到Mysql数据库的userInfo表中。

1.建表语句：

userCode（字典表）和userInfo表（目标表）对应DDL语句：

CREATE TABLE `userInfo` (
  `id` int(11) NOT NULL,
  `userNum` int(11) DEFAULT NULL,
  `userName` varchar(64) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  `age` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
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CREATE TABLE `userCode` (
  `id` int(11) NOT NULL,
  `name` varchar(50) COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci
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2.pom.xml文件,这里引入了阿里巴巴的druid

<dependencies>
    <dependency>
      <groupId>org.apache.flink</groupId>
      <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
      <version>${flink.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.flink</groupId>
      <artifactId>flink-java</artifactId>
      <version>${flink.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.flink</groupId>
      <artifactId>flink-clients_${scala.binary.version}</artifactId>
      <version>${flink.version}</version>
    </dependency>
    <dependency>
      <groupId>org.apache.flink</groupId>
      <artifactId>flink-connector-kafka_${scala.binary.version}</artifactId>
      <version>${flink.version}</version>
    </dependency>
    <dependency>
      <groupId>mysql</groupId>
      <artifactId>mysql-connector-java</artifactId>
      <version>5.1.44</version>
    </dependency>
    <dependency>
      <groupId>com.alibaba</groupId>
      <artifactId>druid</artifactId>
      <version>1.1.20</version>
    </dependency>
  </dependencies>
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3.代码整体结构如下：

主函数：FlinkMysqlAsyncIOMain

异步IO处理类，主要用于查询mysql:MysqlAsyncRichMapFunction

Sink端，将结果输出到mysql中：MysqlSinkFunction

数据库工具类：DBUtils

用户实体类：User

package com.hadoop.ljs.flink112.study.asyncIO;

import org.apache.flink.streaming.api.datastream.AsyncDataStream;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import java.util.concurrent.TimeUnit;
/**
 * @author: Created By lujisen
 * @company China JiNan
 * @date: 2021-08-18 14:50
 * @version: v1.0
 * @description: com.hadoop.ljs.flink112.study.asyncIO
 */
public class FlinkMysqlAsyncIOMain {
    public static void main(String[] args) throws Exception {

        int maxIORequestCount = 20; /*最大的异步请求数量*/
        StreamExecutionEnvironment senv = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStream<String> socketDataStream = senv.socketTextStream("192.168.0.111", 9999);

        DataStream<User> userDataStream = AsyncDataStream.orderedWait(
                socketDataStream,
                new MysqlAsyncRichMapFunction(),   //自定义的Mysql异步处理类
                500000,                      //异步超时时间
                TimeUnit.MILLISECONDS,             //时间单位
                maxIORequestCount                  //最大异步并发请求数量
        );
        userDataStream.print();
        userDataStream.addSink(new MysqlSinkFunction<User>());
       /* userDataStream.print();*/
        senv.execute("FlinkMysqlAsyncIOMain");
    }
}
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package com.hadoop.ljs.flink112.study.asyncIO;
import com.alibaba.druid.pool.DruidDataSource;
import java.sql.Connection;
import java.sql.PreparedStatement;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.async.ResultFuture;
import org.apache.flink.streaming.api.functions.async.RichAsyncFunction;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.Collections;
import java.util.concurrent.*;
import java.util.function.Supplier;
/**
 * @author: Created By lujisen
 * @company China JiNan
 * @date: 2021-08-18 10:25
 * @version: v1.0
 * @description: com.hadoop.ljs.flink112.study.asyncIO
 */
public class MysqlAsyncRichMapFunction extends RichAsyncFunction<String,User> {
    /** 能够利用回调函数并发发送请求的数据库客户端,加上transient，不让其序列化 */
    /** 创建线程池、Mysql连接池 */
    @Override
    public void open(Configuration parameters) throws Exception {
       super.open(parameters);
    }

    @Override
    public void asyncInvoke(String line, ResultFuture<User> resultFuture) throws Exception {
        String[] split = line.split(",");
        User user = new User();
        user.setId(Integer.valueOf(split[0]));
        user.setUserNum(Integer.valueOf(split[1]));
        user.setAge(Integer.valueOf(split[2]));

        Future<String> dbResult = DBUtils.executorService.submit(new Callable<String>() {
            @Override
            public String call() throws Exception {
                ResultSet resultSet=null;
                PreparedStatement statement=null;
                String sql = "SELECT id, name FROM userCode WHERE id = ?";
                String userName=null;
                if(user.getUserNum()==1001){
                    System.out.println("当前getUserNum："+user.getUserNum()+"开始睡眠30秒!!!");
                    Thread.sleep(30000);
                }

                try {
                    statement = DBUtils.getConnection().prepareStatement(sql);
                    statement.setInt(1,user.getUserNum());

                    resultSet = statement.executeQuery();
                    while (resultSet.next()) {
                        userName= resultSet.getString("name");
                    }
                } finally {
                    if (resultSet != null) {
                        resultSet.close();
                    }
                    if (statement != null) {
                        statement.close();
                    }
                }
                return userName;
            }
        });
        CompletableFuture.supplyAsync(new Supplier<String>() {
            @Override
            public String get() {
                try {
                    return dbResult.get();
                } catch (InterruptedException | ExecutionException e) {
                    // 显示地处理异常。
                    return null;
                }
            }
        }).thenAccept( (String userName) -> {
            user.setUserName(userName);
            resultFuture.complete(Collections.singleton(user));
        });
    }

    @Override
    public void close() throws Exception {
        super.close();
    }
}
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package com.hadoop.ljs.flink112.study.asyncIO;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import java.sql.PreparedStatement;
/**
 * @author: Created By lujisen
 * @company China JiNan
 * @date: 2021-08-18 15:02
 * @version: v1.0
 * @description: com.hadoop.ljs.flink112.study.asyncIO
 */
public class MysqlSinkFunction<U> extends RichSinkFunction<User> {
    private static final String UPSERT_CASE = "INSERT INTO userInfo(id,userNum,userName,age) VALUES (?, ?,?,?)";
    private PreparedStatement statement=null;
    @Override
    public void open(Configuration parameters) throws Exception {
        super.open(parameters);
        statement = DBUtils.getConnection().prepareStatement(UPSERT_CASE);
    }
        @Override
    public void invoke(User user, Context context) throws Exception {
        statement.setInt(1,user.getId());
        statement.setInt(2, user.userNum);
        statement.setString(3, user.getUserName());
        statement.setInt(4, user.getAge());
        statement.addBatch();
        statement.executeBatch();
    }

    @Override
    public void close() throws Exception {
        super.close();
        if(statement!=null){
            statement.close();
        }
    }
}

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package com.hadoop.ljs.flink112.study.asyncIO;

import com.alibaba.druid.pool.DruidDataSource;
import java.sql.Connection;
import java.sql.SQLException;
import java.util.concurrent.ExecutorService;
import static java.util.concurrent.Executors.newFixedThreadPool;
/**
 * @author: Created By lujisen
 * @company China JiNan
 * @date: 2021-08-18 15:19
 * @version: v1.0
 * @description: com.hadoop.ljs.flink112.study.asyncIO
 */
public class DBUtils {

    private static String jdbcUrl = "jdbc:mysql://192.168.0.111:3306/lujisen?characterEncoding=utf8";
    private static String username = "root";
    private static String password = "123456a?";
    private static String driverName = "com.mysql.jdbc.Driver";
    public static Connection connection=null;
    public static transient ExecutorService executorService = null;
    public static transient DruidDataSource dataSource = null;
    /*连接池最大线程数*/
    private static int maxPoolConn=20;
    /*静态初始化*/
    static {
        //创建线程池
        executorService = newFixedThreadPool(maxPoolConn);
        dataSource=new DruidDataSource();

        dataSource.setDriverClassName(driverName);
        dataSource.setUsername(username);
        dataSource.setPassword(password);
        dataSource.setUrl(jdbcUrl);
        dataSource.setMaxActive(maxPoolConn);
    }

    public static Connection getConnection() throws SQLException {
        if(connection==null){
            connection= dataSource.getConnection();
        }
        return connection;
    }
}
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package com.hadoop.ljs.flink112.study.asyncIO;/** * @author: Created By lujisen * @company China JiNan * @date: 2021-08-18 10:13 * @version: v1.0 * @description: com.hadoop.ljs.flink112.study.asyncIO */public class User {    int id;    int userNum;    String userName;    int age;    public User() {    }    public User(int id, int userNum, String userName, int age) {        this.id = id;        this.userNum = userNum;        this.userName = userName;        this.age = age;    }    public int getId() {        return id;    }    public void setId(int id) {        this.id = id;    }    public int getUserNum() {        return userNum;    }    public void setUserNum(int userNum) {        this.userNum = userNum;    }    public String getUserName() {        return userName;    }    public void setUserName(String userName) {        this.userName = userName;    }    public int getAge() {        return age;    }    public void setAge(int age) {        this.age = age;    }    @Override    public String toString() {        return "User{" +                "id=" + id +                ", userNum=" + userNum +                ", userName='" + userName + '\'' +                ", age=" + age +                '}';    }}复制

说明：这里可忽略上面的多表数据，只发送后面的2条数据即可，Main函数中设置Flink异步IO超时时间是50s,而MysqlAsyncRichMapFunction文件asyncInvoke函数处理逻辑，当数据id为1时，进程休眠30秒，第一条数据阻塞执行，收到第二条数据不阻塞，直接处理第二条写入mysql数据库，30秒后，程序继续处理第一条数据，可观察Mysql数据表userInfo，看到第二条数据先入库，第一条数据30秒之后入库。

1,1001,23  第一条数据
2,1002,24  第二条数据
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实战：Flink1.12异步IO访问外部数据-Mysql

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