Apache Flink:将DataStream写入Postgres表

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.jdbc.JDBCSinkFunction;
import org.apache.flink.streaming.connectors.jdbc.JdbcSink;

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

        // 创建DataStream，这里使用Tuple2作为示例数据
        DataStream<Tuple2<String, Integer>> dataStream = env.fromElements(
                new Tuple2<>("A", 1),
                new Tuple2<>("B", 2),
                new Tuple2<>("C", 3)
        );

        // 将DataStream转换为需要写入PostgreSQL的格式
        DataStream<Tuple2<String, Integer>> transformedStream = dataStream.map(new MapFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>() {
            @Override
            public Tuple2<String, Integer> map(Tuple2<String, Integer> value) throws Exception {
                // 在这里进行数据转换，将数据转换为需要写入PostgreSQL的格式
                return value;
            }
        });

        // 创建JDBC连接器
        JDBCSinkFunction<Tuple2<String, Integer>> jdbcSink = JdbcSink.sink(
                "INSERT INTO your_table_name (column1, column2) VALUES (?, ?)",
                (ps, value) -> {
                    ps.setString(1, value.f0);
                    ps.setInt(2, value.f1);
                });

        // 将DataStream写入PostgreSQL表
        transformedStream.addSink(jdbcSink);

        // 执行任务
        env.execute("Flink Postgres Example");
    }
}