【Flink-cdc-Mysql-To-Kafka】使用 Flinksql 利用集成的 connector 实现 Mysql 数据写入 Kafka
2023-12-16 11:57:29
【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
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
- 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
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)
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'
);
文章来源:https://blog.csdn.net/weixin_53543905/article/details/135029225
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