SpringBoot集成Flink CDC实现binlog监听

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.api.*;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;
 
public class FlinkCDCExample {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
 
        // 配置MySQL CDC源连接参数
        String name = "inventory_source";
        String hostname = "localhost";
        String database = "inventory";
        String username = "flinkuser";
        String password = "flinkpw";
 
        String scanStartupMode = "initial"; // 或者 "latest-offset"
 
        // 创建MySQL CDC表源
        String sourceDDL = "" +
                "CREATE TABLE " + name + " (" +
                "  inventory_id INT," +
                "  product_name STRING," +
                "  count INT" +
                ") WITH (" +
                "  'connector' = 'mysql-cdc'," +
                "  'hostname' = '" + hostname + "'," +
                "  'port' = '3306'," +
                "  'username' = '" + username + "'," +
                "  'password' = '" + password + "'," +
                "  'database-name' = '" + database + "'," +
                "  'table-name' = 'inventory'," +
                "  'scan.startup.mode' = '" + scanStartupMode + "'" +
                ")";
 
        tableEnv.executeSql(sourceDDL);
 
        // 注册CDC表作为源表进行查询
        TableResult tableResult = tableEnv.executeSql(
                "SELECT inventory_id, product_name, count FROM " + name + " WHERE count > 0"
        );
 
        // 打印结果
        tableResult.print();
 
        env.execute("Flink CDC Example");
    }
}

这段代码展示了如何在Flink程序中集成CDC源来监听MySQL中的binlog变更。首先，我们创建了一个MySQL CDC表源，并指定了连接参数和启动模式。然后，我们执行了一个简单的SQL查询，该查询会监控库存表中库存数量大于0的变化情况，并将结果打印输出。最后，我们执行了Flink程序。