Flink CDC 2.0原理详解和生产实践

2022-04-13 09:37:12 浏览数 (1)

Flink CDC 概念

CDC 的全称是 Change Data Capture ，在广义的概念上，只要能捕获数据变更的技术，我们都可以称为 CDC 。通常我们说的 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。

应用场景

  1. 数据同步，用于备份，容灾
  2. 数据分发，一个数据源分发给多个下游
  3. 数据采集(E)，面向数据仓库/数据湖的 ETL 数据集成

CDC 技术

目前业界主流的实现机制的可以分为两种：

  1. 基于查询的 CDC
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a.离线调度查询作业，批处理。
b.无法保障数据一致性。
c.不保障实时性。
  1. 基于日志的 CDC
代码语言：javascript复制
a.实时消费日志，流处理。
b.保障数据一致性。
c.提供实时数据。

常见的开源 CDC 方案

Flink CDC 2.0 设计详解

Source 官网

代码语言：javascript复制
https://github.com/ververica/flink-cdc-connectors

支持的连接

实战应用

pom 文件

代码语言：javascript复制
<?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">
    <parent>
        <artifactId>Flink-learning</artifactId>
        <groupId>com.wudl.flink</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>Flink-cdc2.0</artifactId>
    <properties>
        <flink-version>1.13.0</flink-version>
            <maven.compiler.source>1.8</maven.compiler.source>
            <maven.compiler.target>1.8</maven.compiler.target>
    </properties>



    <dependencies>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <version>1.18.2</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink-version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.12</artifactId>
            <version>${flink-version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.12</artifactId>
            <version>${flink-version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>3.1.3</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.49</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner-blink_2.12</artifactId>
            <version>${flink-version}</version>
        </dependency>

        <dependency>
            <groupId>com.ververica</groupId>
            <artifactId>flink-connector-mysql-cdc</artifactId>
            <version>2.0.2</version>
        </dependency>

        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.75</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_2.12</artifactId>
            <version>1.13.3</version>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.0.0</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

代码

代码语言：javascript复制
package com.wud.cdc2;

import com.ververica.cdc.connectors.mysql.MySqlSource;
import com.ververica.cdc.connectors.mysql.table.StartupOptions;
import com.ververica.cdc.debezium.DebeziumDeserializationSchema;
import com.ververica.cdc.debezium.DebeziumSourceFunction;
import com.ververica.cdc.debezium.StringDebeziumDeserializationSchema;
import org.apache.flink.runtime.state.filesystem.FsStateBackend;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.CheckpointConfig;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.environment.StreamPipelineOptions;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;

import static org.apache.flink.table.api.Expressions.$;

public class FlinkCDC {
    public static void main(String[] args) throws Exception {

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tabEnv = StreamTableEnvironment.create(env);
        env.enableCheckpointing(5000L);
        env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
        // 设置任务关闭时候保留最后一次checkpoint 的数据
        env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
        // 指定ck 的自动重启策略
        env.setStateBackend(new FsStateBackend("hdfs://192.168.1.161:8020/cdc2.0-test/ck"));
        // 设置hdfs 的访问用户名
        System.setProperty("HADOOP_USER_NAME","hdfs");

        DebeziumSourceFunction<String> mySqlSource = MySqlSource.<String>builder()
                .hostname("192.168.1.180")
                .port(3306)
                .username("root")
                .password("123456")
                .databaseList("test")
                .tableList("test.Flink_iceberg")
                .deserializer(new StringDebeziumDeserializationSchema())
                .startupOptions(StartupOptions.initial())
                .build();
        DataStreamSource<String> dataStreamSource = env.addSource(mySqlSource);
        dataStreamSource.print();
        env.execute();


    }
}

执行结果

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SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10011,name=flink-mysql,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585007,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585013}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10012,name=flink-mysqA,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585015,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585016}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10012,name=flink-mysqA,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10011,name=flink-mysql,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10011,name=flink-mysql,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10012,name=flink-mysqA,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10013,name=flink-mysqA3,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10014,name=flink-mysqA4,age=19,dt=2021-09-28},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10011,name=flink-mysql,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585017}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10012,name=flink-mysqA,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585017,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10012,name=flink-mysqA,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10011,name=flink-mysql,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10011,name=flink-mysql,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10012,name=flink-mysqA,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10013,name=flink-mysqA3,age=19,dt=2021-09-24},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765, snapshot=true}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10014,name=flink-mysqA4,age=19,dt=2021-09-28},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=true,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1633178585, file=mysql-bin.000036, pos=765}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=10050,name=flink-cdc-add,age=21,dt=2021-10-2},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1633178585018,snapshot=last,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000036,pos=765,row=0},op=r,ts_ms=1633178585018}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}

集群提交

执行命令
代码语言：javascript复制
[root@basenode flink-1.13.2]# bin/flink run -c com.wud.cdc2.FlinkCDC /opt/datas/Flink-cdc2.0-1.0-SNAPSHOT-jar-with-dependencies.jar

Job has been submitted with JobID 137b680a6bb934e43568f14f6583b62c
手动执行savepoint

给当前程序创建保存点-savepoint

代码语言：javascript复制
[root@basenode flink-1.13.2]# bin/flink savepoint     e8e918c2517a777e817c630cf1d6b932    hdfs://192.168.1.161:8020/cdc-test/savepoint
Triggering savepoint for job e8e918c2517a777e817c630cf1d6b932.
Waiting for response...
Savepoint completed. Path: hdfs://192.168.1.161:8020/cdc-test/savepoint/savepoint-e8e918-9ef094f349be
You can resume your program from this savepoint with the run command.
[root@basenode flink-1.13.2]#
界面停止 flink 程序

然后再mysql中添加数据

启动flink 程序
代码语言：javascript复制
[root@basenode flink-1.13.2]# bin/flink run -s hdfs://192.168.1.161:8020/cdc-test/savepoint/savepoint-e8e918-9ef094f349be -c  com.wud.cdc2.FlinkCDC /opt/datas/Flink-cdc2.0-1.0-SNAPSHOT-jar-with-dependencies.jar
Job has been submitted with JobID 474a0da99820aa6025203f9806b9fcad

查看日志：

接下来 flink cdc 2.0 的自定义序列号函数

从上面可以看出flink cdc 的原始结构

代码语言：javascript复制
 SourceRecord{sourcePartition={server=mysql_binlog_source}, 
 sourceOffset={file=mysql-bin.000063, pos=154}}
 ConnectRecord{topic='mysql_binlog_source.wudl-gmall.user_info', kafkaPartition=null, key=Struct{id=4000}, keySchema=Schema{mysql_binlog_source.wudl_gmall.user_info.Key:STRUCT}, value=Struct{after=Struct{id=4000,login_name=i0v0k9,nick_name=xxx,name=xxx,phone_num=137xxxxx,email=xxxx@qq.com,user_level=1,birthday=1969-12-04,gender=F,create_time=2020-12-04 23:28:45},source=Struct{version=1.4.1.Final,connector=mysql,name=mysql_binlog_source,ts_ms=0,snapshot=last,db=wudl-gmall,table=user_info,server_id=0,file=mysql-bin.000063,pos=154,row=0},op=c,ts_ms=1636255826014}, valueSchema=Schema{mysql_binlog_source.wudl_gmall.user_info.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}

我们可以自定义序列化：

代码语言：javascript复制
package com.wud.cdc2;

import com.alibaba.fastjson.JSONObject;
import com.ververica.cdc.debezium.DebeziumDeserializationSchema;
import io.debezium.data.Envelope;
import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.util.Collector;
import org.apache.kafka.connect.data.Field;
import org.apache.kafka.connect.data.Schema;
import org.apache.kafka.connect.data.Struct;
import org.apache.kafka.connect.source.SourceRecord;
import java.util.List;

public class CustomerDeserialization implements DebeziumDeserializationSchema<String> {
    /**
     *
     * SourceRecord{sourcePartition={server=mysql_binlog_source}, sourceOffset={ts_sec=1636269821, file=mysql-bin.000063, pos=6442}} ConnectRecord{topic='mysql_binlog_source.test.Flink_iceberg', kafkaPartition=null, key=null, keySchema=null, value=Struct{after=Struct{id=102,name=flinksql,age=25,dt=2021-11-08},source=Struct{version=1.5.2.Final,connector=mysql,name=mysql_binlog_source,ts_ms=1636269821531,snapshot=last,db=test,table=Flink_iceberg,server_id=0,file=mysql-bin.000063,pos=6442,row=0},op=r,ts_ms=1636269821531}, valueSchema=Schema{mysql_binlog_source.test.Flink_iceberg.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}
     *
     *
     *
     *
     *
     * @param sourceRecord   返回一行数据
     * @param collector 数据输出
     * @throws Exception
     */
    @Override
    public void deserialize(SourceRecord sourceRecord, Collector<String> collector) throws Exception {

        JSONObject  result = new JSONObject();
        String topic = sourceRecord.topic();
        String[] fields = topic.split("\.");
        result.put("db",fields[1]) ;
        result.put("tableName",fields[2]);
        // 获取before 数据
        Struct value = (Struct) sourceRecord.value();
        Struct before = value.getStruct("before");
        JSONObject beforeJson = new JSONObject();
        if (before !=null)
        {
            //获取列信息
            Schema schema = before.schema();
            List<Field> fieldList = schema.fields();
            for (Field field:fieldList)
            {
                beforeJson.put(field.name(),before.get(field));
            }
        }
        result.put("before",beforeJson);
        // 获取after 数据
        Struct after = value.getStruct("after");
        JSONObject afterJson = new JSONObject();
        if (after !=null)
        {
            Schema schema = after.schema();
            List<Field> afterFields = schema.fields();
            for (Field field:afterFields)
            {
                afterJson.put(field.name(),after.get(field));
            }
        }
        result.put("after", afterJson);
        //获取操作类型
        Envelope.Operation operation = Envelope.operationFor(sourceRecord);
        result.put("op", operation);
        //输出数据
        collector.collect(result.toJSONString());
    }
    @Override
    public TypeInformation<String> getProducedType() {
        return  BasicTypeInfo.STRING_TYPE_INFO;
    }
}

调用flink cdc 的自定义函数

代码语言：javascript复制
package com.wud.cdc2;

import com.ververica.cdc.connectors.mysql.MySqlSource;
import com.ververica.cdc.connectors.mysql.table.StartupOptions;
import com.ververica.cdc.debezium.DebeziumDeserializationSchema;
import com.ververica.cdc.debezium.DebeziumSourceFunction;
import com.ververica.cdc.debezium.StringDebeziumDeserializationSchema;
import org.apache.flink.runtime.state.filesystem.FsStateBackend;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.CheckpointConfig;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.environment.StreamPipelineOptions;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;

public class FlinkCDC {
    public static void main(String[] args) throws Exception {

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
//        env.enableCheckpointing(5000L);
//        env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
//        // 设置任务关闭时候保留最后一次checkpoint 的数据
//        env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
//        // 指定ck 的自动重启策略
//        env.setStateBackend(new FsStateBackend("hdfs://192.168.1.161:8020/cdc2.0-test/ck"));
//        // 设置hdfs 的访问用户名
//        System.setProperty("HADOOP_USER_NAME","hdfs");

        DebeziumSourceFunction<String> mySqlSource = MySqlSource.<String>builder()
                .hostname("192.168.1.180")
                .port(3306)
                .username("root")
                .password("123456")
                .databaseList("test")
                .tableList("test.Flink_iceberg")
//                .deserializer(new StringDebeziumDeserializationSchema())
                .deserializer(new CustomerDeserialization())
                .startupOptions(StartupOptions.initial())
                .build();
        DataStreamSource<String> dataStreamSource = env.addSource(mySqlSource);
        dataStreamSource.print();
        env.execute();
    }
}

新增一条数据可以看出 控制台输出结果：

代码语言：javascript复制
{"op":"UPDATE","before":{"dt":"2021-11-07","name":"spark","id":104,"age":22},"after":{"dt":"2021-11-07","name":"spark02","id":104,"age":22},"db":"test","tableName":"Flink_iceberg"}

Flink CDC 2.0 SQL 可以做一个 ETL

需要注意的是必须要有主键 否则更新数据是新增一列，加主键后，更新数据不会新增。

数据库表结构:

代码语言：javascript复制
CREATE TABLE `Flink_iceberg` (
  `id` bigint(64) DEFAULT NULL,
  `name` varchar(64) DEFAULT NULL,
  `age` int(20) DEFAULT NULL,
  `dt` varchar(64) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=latin1

实现代码:

代码语言：javascript复制
package com.wud.cdc2;

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

public class FlinkCdc20MysqlToMysql {
    public static void main(String[] args) throws Exception {

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
        String sourceSql = "CREATE TABLE IF NOT EXISTS mySqlSource ("  
                "id BIGINT primary key, "  
                "name string ,"  
                "age int,"  
                "dt string"  
                ") with ( "  
                " 'connector' = 'mysql-cdc', "  
                " 'scan.startup.mode' = 'latest-offset', "  
                " 'hostname' = '192.168.1.180', "  
                " 'port' = '3306', "  
                " 'username' = 'root', "  
                " 'password' = '123456', "  
                " 'database-name' = 'test', "  
                " 'table-name' = 'Flink_iceberg' "  
                ")";

        String sinkSql = " CREATE TABLE IF NOT EXISTS mySqlSink ("  
                "id BIGINT primary key , "  
                "name string ,"  
                "age int,"  
                "dt string"  
                ") with ("  
                " 'connector' = 'jdbc',"  
                " 'url' = 'jdbc:mysql://192.168.1.180:3306/test',"  
                "'table-name' = 'Flink_iceberg-cdc',"  
                " 'username' = 'root',"  
                " 'password' = '123456' "  
                " )";
        tableEnv.executeSql(sourceSql);
        tableEnv.executeSql(sinkSql);
        tableEnv.executeSql("insert  into  mySqlSink select * from mySqlSource ");
//        env.execute("FlinkCdc20MysqlToMysql");
    }
}
新增一条数据和更新数据显示
代码语言：javascript复制
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysqA","id":10012,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysqA","id":10012,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysql","id":10011,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysql","id":10011,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysqA","id":10012,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysqA3","id":10013,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-28","name":"flink-mysqA4","id":10014,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-09-24","name":"flink-mysql","id":10011,"age":19},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-11-07","name":"flink","id":101,"age":20},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-11-08","name":"flinksql","id":102,"age":25},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-11-09","name":"flink-table","id":103,"age":21},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-11-07","name":"spark","id":104,"age":22},"db":"test","tableName":"Flink_iceberg"}
{"op":"READ","before":{},"after":{"dt":"2021-11-07","name":"hbase","id":105,"age":25},"db":"test","tableName":"Flink_iceberg"}
{"op":"UPDATE","before":{"dt":"2021-11-07","name":"spark","id":104,"age":22},"after":{"dt":"2021-11-07","name":"spark02","id":104,"age":22},"db":"test","tableName":"Flink_iceberg"}
{"op":"CREATE","before":{},"after":{"dt":"2021-11-07","name":"flinkcdc","id":106,"age":22},"db":"test","tableName":"Flink_iceberg"}
flink 大数据 数据库 sql

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