flink读取kafka写到kudu

以下是使用Flink从Kafka读取数据并将其写入Kudu的示例代码：

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.kudu.KuduSink;
import org.apache.flink.streaming.connectors.kudu.KuduTableInfo;
import org.apache.flink.streaming.connectors.kudu.serialization.KuduSerialization;
import org.apache.kudu.client.KuduClient;

import java.util.Properties;

public class FlinkKafkaKuduExample {

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

        // set up the streaming execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

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

        // create a Kafka consumer
        FlinkKafkaConsumer<String> kafkaConsumer = new FlinkKafkaConsumer<>("test-topic", new SimpleStringSchema(), properties);

        // create a Kudu table information object
        KuduTableInfo tableInfo = KuduTableInfo.Builder.create("test-table")
                .addColumn("column1", "STRING")
                .addColumn("column2", "INT32")
                .addPrimaryKeyColumn("column1")
                .build();

        // create a Kudu serialization object
        KuduSerialization<String> serialization = new KuduSerialization<>(tableInfo);

        // create a Kudu sink
        KuduSink<String> kuduSink = new KuduSink<>(new KuduClient.KuduClientBuilder("localhost:7051").build(), serialization);

        // add the Kafka source to the execution environment
        DataStream<String> kafkaDataStream = env.addSource(kafkaConsumer);

        // add the Kudu sink to the execution environment
        kafkaDataStream.addSink(kuduSink);

        // execute the Flink job
        env.execute("Flink Kafka Kudu Example");
    }
}

在该示例中，我们使用了FlinkKafkaConsumer将Kafka主题中的数据读取到DataStream中，并使用KuduSink将其写入Kudu表中。我们还使用了KuduTableInfo和KuduSerialization来定义Kudu表的模式和序列化方式。最后，我们将Kafka数据流连接到Kudu数据流，并执行Flink作业。