如何为Apache Flink创建自定义POJO

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.typeutils.TypeExtractor;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.descriptors.*;

public class CustomPOJOExample {

    public static void main(String[] args) throws Exception {
        // 创建流处理环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        // 创建自定义POJO类
        public class MyPOJO {
            public String name;
            public int age;

            public MyPOJO() {}

            public String getName() {
                return name;
            }

            public void setName(String name) {
                this.name = name;
            }

            public int getAge() {
                return age;
            }

            public void setAge(int age) {
                this.age = age;
            }
        }

        // 注册自定义POJO类
        tableEnv.registerPojoType("MyPOJO", TypeExtractor.createTypeInfo(MyPOJO.class));

        // 创建数据流
        DataStream<MyPOJO> dataStream = env.fromElements(
                new MyPOJO("Alice", 25),
                new MyPOJO("Bob", 30),
                new MyPOJO("Charlie", 35)
        );

        // 将数据流转换为表
        Table table = tableEnv.fromDataStream(dataStream);

        // 执行查询操作
        Table result = table.select("name, age").filter("age > 30");

        // 打印结果
        tableEnv.toRetractStream(result, TypeInformation.of(new TypeHint<Tuple2<Boolean, MyPOJO>>() {}))
                .print();

        // 执行任务
        env.execute("Custom POJO Example");
    }
}