flinkcdc断点续传

package com.atguigu.flink;

import com.ververica.cdc.connectors.mysql.source.MySqlSource;
import com.ververica.cdc.connectors.mysql.table.StartupOptions;
import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.restartstrategy.RestartStrategies;
import org.apache.flink.api.common.time.Time;
import org.apache.flink.runtime.state.hashmap.HashMapStateBackend;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.environment.CheckpointConfig;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

/**
 * @author sy
 * @date 2026/4/7
 * @description TODO: Describe the class purpose
 */

public class FlinkCDC_01_DS {
    public static void main(String[] args) throws Exception {
        // TODO 1.获取执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        // TODO 2. 开启检查点   Flink-CDC将读取binlog的位置信息以状态的方式保存在CK,如果想要做到断点续传,
        // 需要从Checkpoint或者Savepoint启动程序
        // 2.1 开启Checkpoint,每隔5秒钟做一次CK  ,并指定CK的一致性语义
        env.enableCheckpointing(3000L, CheckpointingMode.EXACTLY_ONCE);
        // 2.2 设置超时时间为 1 分钟
        env.getCheckpointConfig().setCheckpointTimeout(60 * 1000L);
        // 2.3 设置两次重启的最小时间间隔
        env.getCheckpointConfig().setMinPauseBetweenCheckpoints(30000L);
        // 2.4 设置任务关闭的时候保留最后一次 CK 数据
        env.getCheckpointConfig().enableExternalizedCheckpoints(
                CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
        // 2.5 指定从 CK 自动重启策略
        env.setRestartStrategy(RestartStrategies.failureRateRestart(
                3, Time.days(1L), Time.minutes(1L)
        ));
        // 2.6 设置状态后端
        env.setStateBackend(new HashMapStateBackend());
        env.getCheckpointConfig().setCheckpointStorage(
                "hdfs://mycluster/flinkCDC"
        );

        // 2.7 设置访问HDFS的用户名
        System.setProperty("HADOOP_USER_NAME", "atguigu");

        //3.获取source
        MySqlSource<String> mySqlSource =  MySqlSource.<String>builder()
                .hostname("hadoop102")
                .port(3306)
                .username("root")
                .password("000000")
                .databaseList("tms01")
                .tableList("tms01.user_info")
                .serverId("1103")
                .deserializer(new JsonDebeziumDeserializationSchema())
                .startupOptions(StartupOptions.initial())
                .build();
        env
                .fromSource(
                        mySqlSource,
                        WatermarkStrategy.noWatermarks(),
                        "MySqlSource")
                .print();
        env.execute();
    }

}

shell 脚本

bin/flink run \
-Dexecution.runtime-mode=streaming \
-s hdfs://mycluster/flinkCDC/3ab9c67f3f232ac69f6e519695d1affa/chk-16 \
-c com.atguigu.flink.FlinkCDC_01_DS \
/opt/module/flink-1.17.0/myjars/flink-ods-1.0-SNAPSHOT-jar-with-dependencies.jar