【Flink-cdc-Mysql-To-Kafka】使用 Flinksql 利用集成的 connector 实现 Mysql 数据写入 Kafka

1）环境准备
2）准备相关 jar 包
3）实现场景
4）准备工作
- 4.1.Mysql
- 4.2.Kafka
5）Flink-Sql
6）验证

1）环境准备

Linux 或者 Windows 端需要安装：Mysql，Kafka，Flink 等。（略）

2）准备相关 jar 包

flink-connector-jdbc_2.11-1.12.0.jar
mysql-connector-java-5.1.49.jar

下载地址：JDBC-Sql-Connector

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flink-format-changelog-json-1.2.0.jar
flink-sql-connector-mysql-cdc-1.2.0.jar
flink-sql-connector-postgres-cdc-1.2.0.jar

下载地址：ververica/flink-cdc-connectors

在这里插入图片描述

备用下载地址：gitee地址(github上不去就下载源码,改好version自己打包)

flink-sql-connector-kafka_2.11-1.12.0.jar

下载地址：flink-sql-connector-kafka

将下载好的包放在 Flink 的 lib 目录下

3）实现场景

1、首先确认MySQL是否开启binlog机制，log_bin = ON 为开启（如下图）

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2、如果是本地环境的 Mysql 按照下面方式开启 binlog

在 C:\ProgramData\MySQL\MySQL Server 5.7\my.ini 下添加

log_bin = mysql-bin
binlog_format = ROW
expire_logs_days = 30

3、重启 Mysql 服务

4）准备工作

4.1.Mysql

1、在 Mysql 中创建 source 表：

CREATE TABLE `mysql2kafka_cdc_test` (`id` int(11) NOT NULL AUTO_INCREMENT,`eventId` varchar(255) DEFAULT NULL,`eventStDt` varchar(255) DEFAULT NULL,`bak6` varchar(255) DEFAULT NULL,`bak7` varchar(255) DEFAULT NULL,`businessId` varchar(255) DEFAULT NULL,`phone` varchar(255) DEFAULT NULL,`bak1` varchar(255) DEFAULT NULL,`bak2` varchar(255) DEFAULT NULL,`bak13` varchar(255) DEFAULT NULL,`bak14` varchar(255) DEFAULT NULL,`bak11` varchar(255) DEFAULT NULL,PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8

2、写入数据的语句准备就绪

INSERT INTO mysql2kafka_cdc_test(
eventId,
eventStDt,
bak6,
bak7,
businessId,
phone,
bak1,
bak2,
bak13,
bak14,
bak11
) VALUES(
'111',
'2022-11-3023:37:49',
'测试',
'https://test?user',
'1727980911111111111111111111',
'12345678910',
'1234',
'2021-12-0100:00:00',
'1727980911111111111111111111',
'APP',
'TEST1'
);

4.2.Kafka

创建 Topic

5）Flink-Sql

source

set table.dynamic-table-options.enabled=true;
set table.exec.source.cdc-events-duplicate=true;CREATE TABLE source_mysql_test(id INT,eventId STRING,eventStDt STRING,bak6 STRING,bak7 STRING,businessId STRING,phone STRING,bak1 STRING,bak2 STRING,bak13 STRING,bak14 STRING,bak11 STRING,PRIMARY KEY (id) NOT ENFORCED
) WITH('connector' = 'mysql-cdc','hostname' = '${ip}','port' = '${port}','database-name' = 'test','table-name' = 'mysql2kafka_cdc_test','username' = '${username}','password' = '${password}','scan.startup.mode'='timestamp','scan.startup.timestamp-millis' = '1692115200000'
);

sink

CREATE TABLE sink_kafka_test (id INT,eventId STRING,eventStDt STRING,bak6 STRING,bak7 STRING,businessId STRING,phone STRING,bak1 STRING,bak2 STRING,bak13 STRING,bak14 STRING,bak11 STRING,PRIMARY KEY (id) NOT ENFORCED) WITH ('connector' = 'upsert-kafka','topic' = 'test','sink.parallelism' = '3','key.format' = 'json','value.format' = 'json','properties.bootstrap.servers' = '${kafka-bootstrap-server}','properties.security.protocol' = 'SASL_PLAINTEXT','properties.sasl.kerberos.service.name' = 'kafka','metadata.max.age.ms' = '300000'
);

insert

insert into sink_kafka_test select * from source_mysql_test;

6）验证

Mysql 中写入测试数据，Kafka-Topic 中观察是否有数据生成。

INSERT INTO mysql2kafka_cdc_test(
eventId,
eventStDt,
bak6,
bak7,
businessId,
phone,
bak1,
bak2,
bak13,
bak14,
bak11
) VALUES(
'111',
'2022-11-3023:37:49',
'测试',
'https://test?user',
'1727980911111111111111111111',
'12345678910',
'1234',
'2021-12-0100:00:00',
'1727980911111111111111111111',
'APP',
'TEST1'
);