Question

每当我尝试从kafka队列中读取消息时，我都会遇到以下异常：

const Promise = require('bluebird');
const fsp = require('fs-promise');
const path = require('path');


class Reader {

  static readFiles(jsonPath, jsonFiles){
    let fileReadCount = 0;
    return Promise.map(jsonFiles, name => {
        let filePath = path.join(jsonPath, name);
        return fsp.readJson(filePath);
      })
      .filter((content, index, length) => {
        if (!content) return false;
        console.log(`Loaded >> ${jsonFiles[index]} ${index+1} / ${length}`);
        return true;
      })
  }

  static readJson() {
    return this.readFiles(this.jsonPath, this.jsonFiles).then(contents => {
      console.log('Done Reading Json Content!', contents);
      return this.jsonContents = contents;
    })
  }

}

Reader.jsonFiles = ['json1.json', 'json2.json', 'json3.json', 'json4.json'];
Reader.jsonPath = 'D:\\Development\\Java';

module.exports = Reader;

卡夫卡制片人代码：

[error] (run-main-0) java.lang.ClassCastException: org.apache.avro.generic.GenericData$Record cannot be cast to com.harmeetsingh13.java.Customer
java.lang.ClassCastException: org.apache.avro.generic.GenericData$Record cannot be cast to com.harmeetsingh13.java.Customer
        at com.harmeetsingh13.java.consumers.avrodesrializer.AvroSpecificDeserializer.infiniteConsumer(AvroSpecificDeserializer.java:79)
        at com.harmeetsingh13.java.consumers.avrodesrializer.AvroSpecificDeserializer.main(AvroSpecificDeserializer.java:87)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:498)

卡夫卡消费者代码：

public class AvroSpecificProducer {
    private static Properties kafkaProps = new Properties();
    private static KafkaProducer<String, Customer> kafkaProducer;

    static {
        kafkaProps.put("bootstrap.servers", "localhost:9092");
        kafkaProps.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, KafkaAvroSerializer.class);
        kafkaProps.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, KafkaAvroSerializer.class);
        kafkaProps.put("schema.registry.url", "http://localhost:8081");
        kafkaProducer = new KafkaProducer<>(kafkaProps);
    }

    public static void fireAndForget(ProducerRecord<String, Customer> record) {
        kafkaProducer.send(record);
    }

    public static void asyncSend(ProducerRecord<String, Customer> record) {
        kafkaProducer.send(record, (recordMetaData, ex) -> {
            System.out.println("Offset: "+ recordMetaData.offset());
            System.out.println("Topic: "+ recordMetaData.topic());
            System.out.println("Partition: "+ recordMetaData.partition());
            System.out.println("Timestamp: "+ recordMetaData.timestamp());
        });
    }

    public static void main(String[] args) throws InterruptedException, IOException {
        Customer customer1 = new Customer(1002, "Jimmy");
        ProducerRecord<String, Customer> record1 = new ProducerRecord<>("CustomerSpecificCountry",
                "Customer One 11 ", customer1
        );

        asyncSend(record1);

        Thread.sleep(1000);
    }
}

我正在关注，这些例子：

Answer 1

在与@harmeen

讨论后，这是最终的代码

static { 
    kafkaProps.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "smallest"); 
    kafkaProps.put(ConsumerConfig.GROUP_ID_CONFIG, "CustomerCountryGroup1"); 
    kafkaProps.put("zookeeper.connect", "localhost:2181"); 
    kafkaProps.put("schema.registry.url", "http://localhost:8081"); 
    kafkaProps.put(KafkaAvroDeserializerConfig.SPECIFIC_AVRO_READER_CONFIG, true); 
}

public static void infiniteConsumer() throws IOException { 

VerifiableProperties properties = new VerifiableProperties(kafkaProps); 
StringDecoder keyDecoder = new StringDecoder(properties); 
KafkaAvroDecoder valueDecoder = new KafkaAvroDecoder(properties); 

Map<String, Integer> topicCountMap = new HashMap<>(); 
topicCountMap.put("BrandNewTopics", 1); 

ConsumerConnector consumer = createJavaConsumerConnector(new kafka.consumer.ConsumerConfig(kafkaProps)); 
Map<String, List<KafkaStream<String, Object>>> consumerMap = consumer.createMessageStreams(topicCountMap, keyDecoder, valueDecoder); 

KafkaStream stream = consumerMap.get("BrandNewTopics").get(0); 
ConsumerIterator it = stream.iterator(); 

while (it.hasNext()) { 
    MessageAndMetadata messageAndMetadata = it.next(); 
    String key = (String) messageAndMetadata.key(); 
    GenericRecord record = (GenericRecord) messageAndMetadata.message(); 
    Customer customer = (Customer) SpecificData.get().deepCopy(Customer.SCHEMA$, record); 
    System.out.println("Key: " + key); 
    System.out.println("Value: " + customer); 
}

变化的事情：

将SPECIFIC_AVRO_READER_CONFIG属性添加到true。
使用最小从主题的开头开始。
使用StringSerializer和StringDeserializer作为密钥。
更改生产者和消费者以反映之前的更改
调整代表Avro记录的Customer类的名称空间。

Apache Kafka和Avro：org.apache.avro.generic.GenericData $ Record无法强制转换为com.harmeetsingh13.java.Customer

1 个答案: