FlinkCDC介绍及使用

本文主要是介绍FlinkCDC介绍及使用，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

CDC简介

        什么是CDC？

                cdc是Change Data Capture(变更数据获取)的简称。核心思想是，监测并捕获数据库的

变动(包括数据或数据表的插入，更新以及删除等)，将这些变更按发生的顺序完整记录下来，写入到消息中间件以供其它服务进行订阅及消费

        CDC的种类？

CDC主要分为基于查询和基于Binlog两种方式，咱们主要了解一下这两种的区别：

	基于查询的CDC	基于Binlog的CDC
开源产品	Sqoop、Kafka JDBC Source	Canal、Maxwell、Debezium
执行模式	Batch	Streaming
是否可以捕获所有数据变化	否	是
延迟性	高延迟	低延迟
是否增加数据库压力	是	否

FlinkCDC案例实操

        开启MySQL Binlog并重启MySQL

sudo vim/etc/my.cnf

把需要监控的数据库名写入到里面

重启mysql

sudo systemctl restart mysqld

DataStream方式的应用

导入依赖

<properties>

    <maven.compiler.source>8</maven.compiler.source>

    <maven.compiler.target>8</maven.compiler.target>

    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>

    <flink.version>1.17.1</flink.version>

    <flink-cdc.vesion>2.4.0</flink-cdc.vesion>

    <hadoop.version>3.3.4</hadoop.version>

</properties>

<dependencies>

    <dependency>

        <groupId>org.apache.flink</groupId>

        <artifactId>flink-clients</artifactId>

        <version>${flink.version}</version>

        <scope>provided</scope>

    </dependency>

    <dependency>

        <groupId>org.apache.flink</groupId>

        <artifactId>flink-connector-kafka</artifactId>

        <version>${flink.version}</version>

    </dependency>

    <dependency>

        <groupId>org.apache.flink</groupId>

        <artifactId>flink-json</artifactId>

        <version>${flink.version}</version>

        <scope>provided</scope>

    </dependency>

    <dependency>

        <groupId>com.alibaba</groupId>

        <artifactId>fastjson</artifactId>

        <version>1.2.83</version>

    </dependency>

    <!--如果保存检查点到hdfs上，需要引入此依赖-->

    <dependency>

        <groupId>org.apache.hadoop</groupId>

        <artifactId>hadoop-client-api</artifactId>

        <version>${hadoop.version}</version>

        <!--<scope>provided</scope>-->

    </dependency>

    <dependency>

        <groupId>org.apache.hadoop</groupId>

        <artifactId>hadoop-client-runtime</artifactId>

        <version>${hadoop.version}</version>

        <!--<scope>provided</scope>-->

    </dependency>

    <dependency>

        <groupId>org.apache.logging.log4j</groupId>

        <artifactId>log4j-to-slf4j</artifactId>

        <version>2.14.0</version>

        <scope>provided</scope>

    </dependency>

    <dependency>

        <groupId>org.apache.logging.log4j</groupId>

        <artifactId>log4j-api</artifactId>

        <version>2.14.0</version>

    </dependency>

    <dependency>

        <groupId>org.slf4j</groupId>

        <artifactId>slf4j-log4j12</artifactId>

        <version>1.7.36</version>

    </dependency>

    <!--cdc 依赖-->

    <dependency>

        <groupId>com.ververica</groupId>

        <artifactId>flink-connector-mysql-cdc</artifactId>

        <version>${flink-cdc.vesion}</version>

    </dependency>

    <!--   flink sql 相关的依赖: 使用 cdc 必须导入 sql 依赖-->

    <dependency>

        <groupId>org.apache.flink</groupId>

        <artifactId>flink-table-api-java-bridge</artifactId>

        <version>${flink.version}</version>

        <scope>provided</scope>

    </dependency>

    <dependency>

        <groupId>org.apache.flink</groupId>

        <artifactId>flink-table-planner-loader</artifactId>

        <version>${flink.version}</version>

        <scope>provided</scope>

    </dependency>

    <dependency>

        <groupId>org.apache.flink</groupId>

        <artifactId>flink-table-runtime</artifactId>

        <version>${flink.version}</version>

        <scope>provided</scope>

    </dependency>

</dependencies>

编写代码

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