Flink之Mysql数据CDC

知识点：

https://github.com/ververica/flink-cdc-connectors  //官网地址

1、处理类

import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.sourceFunction;
import com.alibaba.ververica.cdc.debezium.StringDebeziumDeserializationSchema;
import com.alibaba.ververica.cdc.connectors.MysqL.MysqLSource;
/**
 * @program: Flink1.11
 * @description:
 * @author: yang
 * @create: 2021-01-11 17:41
 */
public class MysqLbinlogSourceExample {
    public static void main(String[] args) throws Exception {
        SourceFunction<String> sourceFunction = MysqLSource.<String>builder()
                .hostname("localhost")
                .port(3306)
                .databaseList("test")
                // monitor all tables under inventory database
                .username("root")
                .password("root")
                .deserializer(new StringDebeziumDeserializationSchema())
                // converts SourceRecord to String
                .build();

        StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(new Configuration());

        env.addSource(sourceFunction).print().setParallelism(1);
        // use parallelism 1 for sink to keep message ordering
        env.execute("test");
    }
}

2、binlog结果

修改:befor and after 
SourceRecord{
    sourcePartition={server=MysqL-binlog-source}, 
    sourceOffset={ts_sec=1610362335, file=MysqL-bin.000004, pos=233445691, row=1, server_id=1, event=2}
} 
ConnectRecord
{topic='MysqL-binlog-source.test.weblog', kafkaPartition=null, key=Struct{id=5}, keySchema=Schema{MysqL_binlog_source.test.weblog.Key:STRUCT}, value=Struct{before=Struct{id=5,url=5,method=5,ip=5,args=5,create_time=1610390670000},after=Struct{id=5,url=5555,method=5555,ip=5555,args=5555,create_time=1610390670000},source=Struct{version=1.2.0.Final,connector=MysqL,name=MysqL-binlog-source,ts_ms=1610362335000,db=test,table=weblog,server_id=1,file=MysqL-bin.000004,pos=233445826,row=0,thread=944986},op=u,ts_ms=1610362335615}, valueSchema=Schema{MysqL_binlog_source.test.weblog.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)
}


增加:只有after
SourceRecord{sourcePartition={server=MysqL-binlog-source}, sourceOffset={file=MysqL-bin.000004, pos=233455303}} 
ConnectRecord
{topic='MysqL-binlog-source.test.weblog', kafkaPartition=null, key=Struct{id=7}, keySchema=Schema{MysqL_binlog_source.test.weblog.Key:STRUCT}, value=Struct{after=Struct{id=7,url=7,method=7,ip=7,args=7,create_time=1610391478000},source=Struct{version=1.2.0.Final,connector=MysqL,name=MysqL-binlog-source,ts_ms=0,snapshot=last,db=test,table=weblog,server_id=0,file=MysqL-bin.000004,pos=233455303,row=0},op=c,ts_ms=1610362692061}, valueSchema=Schema{MysqL_binlog_source.test.weblog.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}


删除:只有before
SourceRecord{sourcePartition={server=MysqL-binlog-source}, sourceOffset={ts_sec=1610362743, file=MysqL-bin.000004, pos=233456891, row=1, server_id=1, event=2}} ConnectRecord{topic='MysqL-binlog-source.test.weblog', kafkaPartition=null, key=Struct{id=1}, keySchema=Schema{MysqL_binlog_source.test.weblog.Key:STRUCT}, value=Struct{before=Struct{id=1,url=1,method=1,ip=1,args=1,create_time=1603115590000},source=Struct{version=1.2.0.Final,connector=MysqL,name=MysqL-binlog-source,ts_ms=1610362743000,db=test,table=weblog,server_id=1,file=MysqL-bin.000004,pos=233457026,row=0,thread=944986},op=d,ts_ms=1610362744527}, valueSchema=Schema{MysqL_binlog_source.test.weblog.Envelope:STRUCT}, timestamp=null, headers=ConnectHeaders(headers=)}

3、如果需要将数据进行etl，可以自定义实现sink