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Flink CDC 实时mysql到mysql

CDC 的全称是 Change Data Capture ,在广义的概念上,只要是能捕获数据变更的技术,我们都可以称之为 CDC 。目前通常描述的 CDC 技术主要面向数据库的变更,是一种用于捕获数据库中数据变更的技术。

**mysqlcdc需要mysql开启binlog,找到my.cnf,在

[mysqld]

中加入如下信息**

[mysqld]

server-id=1

log-bin=mysql-bin

binlog-format=row

重启数据库。

2.创建springboot项目,pom添加依赖

<properties> <java.version>1.8</java.version> <flink.version>1.13.6</flink.version> <scala.binary.version>2.11</scala.binary.version> <slf4j.version>1.7.30</slf4j.version> </properties> <dependencies> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-planner-blink_2.11</artifactId> <version>1.13.6</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>${flink.version}</version> </dependency> <dependency> <groupId>mysql</groupId> <artifactId>mysql-connector-java</artifactId> <version>8.0.17</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-api-java</artifactId> <version>${flink.version}</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-table-api-java-bridge_${scala.binary.version}</artifactId> <version>${flink.version}</version> </dependency> <dependency> <groupId>com.ververica</groupId> <artifactId>flink-connector-mysql-cdc</artifactId> <version>2.2.0</version> </dependency> <dependency> <groupId>org.apache.flink</groupId> <artifactId>flink-connector-jdbc_2.12</artifactId> <version>1.13.1</version> </dependency> </dependencies> <build> <plugins> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-shade-plugin</artifactId> <version>3.1.0</version> <executions> <execution> <phase>package</phase> <goals> <goal>shade</goal> </goals> <configuration> <filters> <filter> <artifact>*:*</artifact> <excludes> <exclude>META-INF/*.SF</exclude> <exclude>META-INF/*.DSA</exclude> <exclude>META-INF/*.RSA</exclude> </excludes> </filter> </filters> </configuration> </execution> </executions> </plugin> </plugins> </build>

Flink cdc实现mysql到mysql代码

import org.apache.flink.api.common.restartstrategy.RestartStrategies;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

public class FlinkMysqlToMysql {

public static void main(String[] args) {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setRestartStrategy(RestartStrategies.fixedDelayRestart(3, 5000));
env.enableCheckpointing(5000);
env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
// 创建Table环境
EnvironmentSettings settings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
StreamTableEnvironment tEnv = StreamTableEnvironment.create(env, settings);

// 注册源表和目标表
tEnv.executeSql("create table sourceTable(id bigint,organization_code VARCHAR, organization_name VARCHAR, parent_code VARCHAR, parent_name VARCHAR,PRIMARY KEY (id) NOT ENFORCED ) WITH (\n" +
//源表连接器一定得是mysql-cdc
"'connector' = 'mysql-cdc'," +
"'hostname' = 'localhost',\n" +
" 'port' = '3306',\n" +
" 'database-name' = 'quarant_db',\n" +
" 'table-name' = 'organization_info',\n" +
" 'username' = 'root',\n" +
" 'password' = 'admin'\n" +
")");
// Table result = tEnv.sqlQuery("SELECT id, name,card_num,phone,address FROM quarantine");
// tEnv.registerTable("sourceTable",result);
tEnv.executeSql("create table targetTable(id bigint,organization_code VARCHAR, organization_name VARCHAR, parent_code VARCHAR, parent_name VARCHAR,PRIMARY KEY (id) NOT ENFORCED ) WITH (\n" +
//目标表连接器是jdbc
"'connector' = 'jdbc'," +
"'url' = 'jdbc:mysql://localhost:3306/testdb?serverTimezone=UTC&useUnicode=true&characterEncoding=utf-8&useSSL=false',\n" +
" 'table-name' = 'organization_info',\n" +
" 'username' = 'root',\n" +
" 'driver' = 'com.mysql.cj.jdbc.Driver',\n" +
" 'password' = 'admin'\n" +
")");
// 执行CDC过程
String query = "INSERT INTO targetTable SELECT * FROM sourceTable";
tEnv.executeSql(query).print();
}
}

运行Main方法

Flink会同步源表数据到目标表,后续源表的增删改都会实时同步至目标表中。

3.将程序打包成flink jar

idea使用快捷键control+alt+shift+s,点击Artifacts->JAR

选择Main class,点击ok

然后选择上面菜单栏Build Artifacts

点击build

生成的jar在项目目录下面有个out目录

至此,flink jar程序就写好了,可以把jar丢到flink上运行了

标签: flink 大数据

本文转载自: https://blog.csdn.net/letterss/article/details/131128378
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