写个flink 流关联sink到clickhouse的代码

好的，请稍等，我正在为您编写代码。

import org.apache.flink.api.common.serialization.SimpleStringSchema;
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.KafkaDeserializationSchema;
import org.apache.flink.streaming.connectors.kafka.KafkaSerializationSchema;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.util.serialization.KeyedSerializationSchema;
import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchema;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.typeutils.TypeExtractor;
import org.apache.flink.streaming.api.functions.sink.SinkFunction;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.types.Row;

import java.util.Properties;

import ru.yandex.clickhouse.ClickHouseDataSource;

public class FlinkClickhouseSink {
    public static void main(String[] args) throws Exception {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // Kafka consumer properties
        Properties consumerProperties = new Properties();
        consumerProperties.setProperty("bootstrap.servers", "localhost:9092");
        consumerProperties.setProperty("group.id", "test-group");

        // Kafka producer properties
        Properties producerProperties = new Properties();
        producerProperties.setProperty("bootstrap.servers", "localhost:9092");

        // ClickHouse properties
        Properties clickHouseProperties = new Properties();
        clickHouseProperties.setProperty("user", "default");
        clickHouseProperties.setProperty("password", "");
        clickHouseProperties.setProperty("database", "test");
        ClickHouseDataSource clickHouseDataSource = new ClickHouseDataSource("jdbc:clickhouse://localhost:8123/test", clickHouseProperties);

        // Kafka consumer
        DataStream<String> stream = env
                .addSource(new FlinkKafkaConsumer<>("test-topic", new SimpleStringSchema(), consumerProperties));

        // Flink transformation, e.g. filter or map
        DataStream<Tuple2<Integer, String>> mappedStream = stream
                .map(new MapFunction<String, Tuple2<Integer, String>>() {
                    @Override
                    public Tuple2<Integer, String> map(String value) throws Exception {
                        Integer key = Integer.parseInt(value.split(",")[0]);
                        String message = value.split(",")[1];
                        return new Tuple2<>(key, message);
                    }
                });

        // Kafka producer serialization schema
        KafkaSerializationSchema<Tuple2<Integer, String>> kafkaSerializationSchema = new KafkaSerializationSchema<Tuple2<Integer, String>>() {
            @Override
            public void open(SerializationSchema.InitializationContext context) throws Exception {
            }

            @Override
            public ProducerRecord<byte[], byte[]> serialize(Tuple2<Integer, String> element, Long timestamp) {
                return new ProducerRecord<>("test-topic", (element.f0 + "," + element.f1).getBytes());
            }
        };

        // Kafka producer
        FlinkKafkaProducer<Tuple2<Integer, String>> kafkaProducer = new FlinkKafkaProducer<>("test-topic", kafkaSerializationSchema, producerProperties);

        // ClickHouse sink function
        SinkFunction<Tuple2<Integer, String>> clickHouseSinkFunction = new SinkFunction<Tuple2<Integer, String>>() {
            @Override
            public void invoke(Tuple2<Integer, String> value, Context context) throws Exception {
                String sql = "INSERT INTO test (id, message) values (?, ?)";
                try (ClickHouseConnection connection = clickHouseDataSource.getConnection();
                     ClickHousePreparedStatement stmt = (ClickHousePreparedStatement) connection.prepareStatement(sql)) {
                    stmt.setInt(1, value.f0);
                    stmt.setString(2, value.f1);
                    stmt.execute();
                }
            }
        };

        // ClickHouse sink
        mappedStream.addSink(clickHouseSinkFunction);

        // Kafka producer sink
        mappedStream.addSink(kafkaProducer);

        env.execute();
    }
}

这是一个简单的 Flink 流程序，将从 Kafka 中读取数据，经过 Flink 的转换后将数据写入 Kafka 和 ClickHouse 中。请注意，这个程序只是示例代码，如果您在实际环境中使用，请根据实际情况进行修改。