flink消费kafka数据到postgresql用代码怎么编写，举例展示代码

下面是一个示例代码，演示如何使用Flink消费Kafka数据流并将数据写入PostgreSQL数据库:

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.util.serialization.SimpleStringSchema;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;

import java.util.Properties;

public class KafkaToFlinkToPostgreSQL {

    public static void main(String[] args) throws Exception {

        // 设置Flink的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 配置Kafka消费者
        Properties consumerProperties = new Properties();
        consumerProperties.setProperty(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        consumerProperties.setProperty(ConsumerConfig.GROUP_ID_CONFIG, "flink-consumer");
        FlinkKafkaConsumer<String> kafkaConsumer = new FlinkKafkaConsumer<>("kafka-topic", new SimpleStringSchema(), consumerProperties);

        // 从Kafka读取数据
        DataStream<String> kafkaDataStream = env.addSource(kafkaConsumer);

        // 将数据写入PostgreSQL
        kafkaDataStream.map(new MapFunction<String, Object>() {
            @Override
            public Object map(String value) throws Exception {
                // 这里编写将数据写入PostgreSQL的代码
                return null;
            }
        });

        // 启动Flink任务
        env.execute("Kafka to Flink to PostgreSQL");
    }
}

在这个示例代码中，我们使用Flink的Kafka消费者从Kafka读取数据流，并使用`map`操作将数据写入PostgreSQL。需要根据具体的业务需求编写具体的写入PostgreSQL的代码。