使用Flink实现MySQL到Kafka的数据流转换

本篇博客将介绍如何使用Flink将数据从MySQL数据库实时传输到Kafka，这是一个常见的用例，适用于需要实时数据connector的场景。

环境准备

在开始之前，确保你的环境中已经安装了以下软件：

Apache Flink 准备相关pom依赖

xml 复制代码

<?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>4.0.0</modelVersion>

    <groupId>org.example</groupId>
    <artifactId>EastMoney</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.11</artifactId>
            <version>1.14.0</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-scala-bridge_2.11</artifactId>
            <version>1.14.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner_2.11</artifactId>
            <version>1.14.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-scala_2.11</artifactId>
            <version>1.14.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_2.11</artifactId>
            <version>1.14.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-csv</artifactId>
            <version>1.14.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.11</artifactId>
            <version>1.14.0</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>8.0.25</version>
        </dependency>
    </dependencies>

</project>

MySQL数据库，初始化mysql表

sql 复制代码

CREATE TABLE `t_stock_code_price` (
  `id` bigint NOT NULL AUTO_INCREMENT,
  `code` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL COMMENT '股票代码',
  `name` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL COMMENT '股票名称',
  `close` double DEFAULT NULL COMMENT '最新价',
  `change_percent` double DEFAULT NULL COMMENT '涨跌幅',
  `change` double DEFAULT NULL COMMENT '涨跌额',
  `volume` double DEFAULT NULL COMMENT '成交量（手）',
  `amount` double DEFAULT NULL COMMENT '成交额',
  `amplitude` double DEFAULT NULL COMMENT '振幅',
  `turnover_rate` double DEFAULT NULL COMMENT '换手率',
  `peration` double DEFAULT NULL COMMENT '市盈率',
  `volume_rate` double DEFAULT NULL COMMENT '量比',
  `hign` double DEFAULT NULL COMMENT '最高',
  `low` double DEFAULT NULL COMMENT '最低',
  `open` double DEFAULT NULL COMMENT '今开',
  `previous_close` double DEFAULT NULL COMMENT '昨收',
  `pb` double DEFAULT NULL COMMENT '市净率',
  `create_time` varchar(64) NOT NULL COMMENT '写入时间',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=5605 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci

Kafka消息队列

powershell 复制代码

1. 启动zookeeper
 zkServer start
2. 启动kafka服务
 kafka-server-start /opt/homebrew/etc/kafka/server.properties
3. 创建topic
 kafka-topics --create --bootstrap-server 127.0.0.1:9092 --replication-factor 1 --partitions 1 --topic east_money
4. 消费数据
 kafka-console-consumer --bootstrap-server 127.0.0.1:9092 --topic east_money --from-beginning

步骤解释

获取流执行环境：首先，我们通过StreamExecutionEnvironment.getExecutionEnvironment获取Flink的流执行环境，并设置其运行模式为流处理模式。

创建流表环境：接着，我们通过StreamTableEnvironment.create创建一个流表环境，这个环境允许我们使用SQL语句来操作数据流。

scala 复制代码

val senv = StreamExecutionEnvironment.getExecutionEnvironment
      .setRuntimeMode(RuntimeExecutionMode.STREAMING)
    val tEnv = StreamTableEnvironment.create(senv)

定义MySQL数据源表：我们使用一个SQL语句创建了一个临时表t_stock_code_price，这个表代表了我们要从MySQL读取的数据结构和连接信息。

scala 复制代码

val source_table =
      """
        |CREATE TEMPORARY TABLE t_stock_code_price (
        |  id BIGINT NOT NULL,
        |  code STRING NOT NULL,
        |  name STRING NOT NULL,
        |  `close` DOUBLE,
        |  change_percent DOUBLE,
        |  change DOUBLE,
        |  volume DOUBLE,
        |  amount DOUBLE,
        |  amplitude DOUBLE,
        |  turnover_rate DOUBLE,
        |  peration DOUBLE,
        |  volume_rate DOUBLE,
        |  hign DOUBLE,
        |  low DOUBLE,
        |  `open` DOUBLE,
        |  previous_close DOUBLE,
        |  pb DOUBLE,
        |  create_time STRING NOT NULL,
        |  PRIMARY KEY (id) NOT ENFORCED
        |) WITH (
        |   'connector' = 'jdbc',
        |   'url' = 'jdbc:mysql://localhost:3306/mydb',
        |   'driver' = 'com.mysql.cj.jdbc.Driver',
        |   'table-name' = 't_stock_code_price',
        |   'username' = 'root',
        |   'password' = '12345678'
        |)
        |""".stripMargin

    tEnv.executeSql(source_table)

定义Kafka目标表：然后，我们定义了一个Kafka表re_stock_code_price_kafka，指定了Kafka的连接参数和表结构。

scala 复制代码

tEnv.executeSql(
      "CREATE TABLE re_stock_code_price_kafka (" +
        "`id` BIGINT," +
        "`code` STRING," +
        "`name` STRING," +
        "`close` DOUBLE," +
        "`change_percent` DOUBLE," +
        "`change` DOUBLE," +
        "`volume` DOUBLE," +
        "`amount` DOUBLE," +
        "`amplitude` DOUBLE," +
        "`turnover_rate` DOUBLE," +
        "`operation` DOUBLE," +
        "`volume_rate` DOUBLE," +
        "`high` DOUBLE," +
        "`low` DOUBLE," +
        "`open` DOUBLE," +
        "`previous_close` DOUBLE," +
        "`pb` DOUBLE," +
        "`create_time` STRING," +
        "rise int"+
        ") WITH (" +
        "'connector' = 'kafka'," +
        "'topic' = 'east_money'," +
        "'properties.bootstrap.servers' = '127.0.0.1:9092'," +
        "'properties.group.id' = 'mysql2kafka'," +
        "'scan.startup.mode' = 'earliest-offset'," +
        "'format' = 'csv'," +
        "'csv.field-delimiter' = ','" +
        ")"
    )

数据转换和写入：最后，我们执行了一个插入操作，将从MySQL读取的数据转换（这里通过case when语句添加了一个新字段rise）并写入到Kafka中。这个可以实现任何的sql etl 来满足我们的需求。

scala 复制代码

    tEnv.executeSql("insert into re_stock_code_price_kafka select *,case when change_percent>0 then 1 else 0 end as rise from t_stock_code_price")

全部代码

scala 复制代码

package org.east

import org.apache.flink.api.common.RuntimeExecutionMode
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.table.api.bridge.scala.StreamTableEnvironment

object Mysql2Kafka {

  def main(args: Array[String]): Unit = {
    val senv = StreamExecutionEnvironment.getExecutionEnvironment
      .setRuntimeMode(RuntimeExecutionMode.STREAMING)
    val tEnv = StreamTableEnvironment.create(senv)

    val source_table =
      """
        |CREATE TEMPORARY TABLE t_stock_code_price (
        |  id BIGINT NOT NULL,
        |  code STRING NOT NULL,
        |  name STRING NOT NULL,
        |  `close` DOUBLE,
        |  change_percent DOUBLE,
        |  change DOUBLE,
        |  volume DOUBLE,
        |  amount DOUBLE,
        |  amplitude DOUBLE,
        |  turnover_rate DOUBLE,
        |  peration DOUBLE,
        |  volume_rate DOUBLE,
        |  hign DOUBLE,
        |  low DOUBLE,
        |  `open` DOUBLE,
        |  previous_close DOUBLE,
        |  pb DOUBLE,
        |  create_time STRING NOT NULL,
        |  PRIMARY KEY (id) NOT ENFORCED
        |) WITH (
        |   'connector' = 'jdbc',
        |   'url' = 'jdbc:mysql://localhost:3306/mydb',
        |   'driver' = 'com.mysql.cj.jdbc.Driver',
        |   'table-name' = 't_stock_code_price',
        |   'username' = 'root',
        |   'password' = '12345678'
        |)
        |""".stripMargin

    tEnv.executeSql(source_table)

    val result = tEnv.executeSql("select * from t_stock_code_price")
    result.print()


    tEnv.executeSql(
      "CREATE TABLE re_stock_code_price_kafka (" +
        "`id` BIGINT," +
        "`code` STRING," +
        "`name` STRING," +
        "`close` DOUBLE," +
        "`change_percent` DOUBLE," +
        "`change` DOUBLE," +
        "`volume` DOUBLE," +
        "`amount` DOUBLE," +
        "`amplitude` DOUBLE," +
        "`turnover_rate` DOUBLE," +
        "`operation` DOUBLE," +
        "`volume_rate` DOUBLE," +
        "`high` DOUBLE," +
        "`low` DOUBLE," +
        "`open` DOUBLE," +
        "`previous_close` DOUBLE," +
        "`pb` DOUBLE," +
        "`create_time` STRING," +
        "rise int"+
        ") WITH (" +
        "'connector' = 'kafka'," +
        "'topic' = 'east_money'," +
        "'properties.bootstrap.servers' = '127.0.0.1:9092'," +
        "'properties.group.id' = 'mysql2kafka'," +
        "'scan.startup.mode' = 'earliest-offset'," +
        "'format' = 'csv'," +
        "'csv.field-delimiter' = ','" +
        ")"
    )
    tEnv.executeSql("insert into re_stock_code_price_kafka select *,case when change_percent>0 then 1 else 0 end as rise from t_stock_code_price")

  }
}

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