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前些天发现了一个巨牛的人工智能学习网站,通俗易懂,风趣幽默,忍不住分享一下给大家。点击跳转到网站。
JDK 11+
Maven 3.8.x+
springboot 2.5.4 +
springboot的pom文件导入
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-clients</artifactId>
<version>3.4.0</version>
</dependency>
发布者我们使用 KafkaTemplate 来进行消息发布,所以需要先对其进行一些必要的配置。
@Configuration @EnableKafka public class KafkaConfig { /***** 发布者 *****/ //生产者工厂 @Bean public ProducerFactory<Integer, String> producerFactory() { return new DefaultKafkaProducerFactory<>(producerConfigs()); } //生产者配置 @Bean public Map<String, Object> producerConfigs() { Map<String, Object> props = new HashMap<>(); props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.2.83:9092,192.168.2.84:9092,192.168.2.86:9092"); props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class); props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class); return props; } //生产者模板 @Bean public KafkaTemplate<Integer, String> kafkaTemplate() { return new KafkaTemplate<>(producerFactory()); } }
配置完发布者,下来就是发布消息,我们需要继承 ProducerListener<K, V> 接口,该接口完整信息如下:
public interface ProducerListener<K, V> {
void onSuccess(ProducerRecord<K, V> producerRecord, RecordMetadata recordMetadata);
void onError(ProducerRecord<K, V> producerRecord, RecordMetadata recordMetadata,
Exception exception);
}
实现该接口的方法,我们可以获取包含发送结果(成功或失败)的异步回调,也就是可以在这个接口的实现中获取发送结果。
我们简单的实现构建一个发布者类,接收主题和发布消息参数,并打印发布结果。
@Component public class KafkaProducer implements ProducerListener<Object,Object> { private static final Logger producerlog = LoggerFactory.getLogger(KafkaProducer.class); private final KafkaTemplate<Integer, String> kafkaTemplate; public KafkaProducer(KafkaTemplate<Integer, String> kafkaTemplate) { this.kafkaTemplate = kafkaTemplate; } public void producer (String msg,String topic){ ListenableFuture<SendResult<Integer, String>> future = kafkaTemplate.send(topic,0, msg); future.addCallback(new KafkaSendCallback<Integer, String>() { @Override public void onSuccess(SendResult<Integer, String> result) { producerlog.info("发送成功 {}", result); } @Override public void onFailure(KafkaProducerException ex) { ProducerRecord<Integer, String> failed = ex.getFailedProducerRecord(); producerlog.info("发送失败 {}",failed); } }); } }
写一个controller类来测试我们构建的发布者类,这个类中打印接收到的消息,来确保信息接收不出问题。
@RestController
public class KafkaTestController {
private static final Logger kafkaTestLog = LoggerFactory.getLogger(KafkaTestController.class);
@Resource
private KafkaProducer kafkaProducer;
@GetMapping("/kafkaTest")
public void kafkaTest(String msg,String topic){
kafkaProducer.producer(msg,topic);
kafkaTestLog.info("接收到消息 {} {}",msg,topic);
}
}
一切准备就绪,我们启动程序利用postman来进行简单的测试。
进行消息发布:
发布结果:
可以看到消息发送成功。
我们再看看kafka消费者有没有接收到消息:
看以看到,kakfa的消费者也接收到了消息。
消息的接受有多种方式,我们这里选择的是使用 @KafkaListener 注解来进行消息接收。它的使用像下面这样:
public class Listener {
@KafkaListener(id = "foo", topics = "myTopic", clientIdPrefix = "myClientId")
public void listen(String data) {
...
}
}
看起来不是太难吧,但使用这个注解,我们需要配置底层 ConcurrentMessageListenerContainer.kafkaListenerContainerFactor。
我们在原来的kafka配置类 KafkaConfig 中,继续配置消费者,大概就像下面这样
@Configuration @EnableKafka public class KafkaConfig { /***** 发布者 *****/ //生产者工厂 @Bean public ProducerFactory<Integer, String> producerFactory() { return new DefaultKafkaProducerFactory<>(producerConfigs()); } //生产者配置 @Bean public Map<String, Object> producerConfigs() { Map<String, Object> props = new HashMap<>(); props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.2.83:9092,192.168.2.84:9092,192.168.2.86:9092"); props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class); props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class); return props; } //生产者模板 @Bean public KafkaTemplate<Integer, String> kafkaTemplate() { return new KafkaTemplate<>(producerFactory()); } /***** 消费者 *****/ //容器监听工厂 @Bean KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<Integer, String>> kafkaListenerContainerFactory() { ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory<>(); factory.setConsumerFactory(consumerFactory()); factory.setConcurrency(3); factory.getContainerProperties().setPollTimeout(3000); return factory; } //消费者工厂 @Bean public ConsumerFactory<Integer, String> consumerFactory() { return new DefaultKafkaConsumerFactory<>(consumerConfigs()); } //消费者配置 @Bean public Map<String, Object> consumerConfigs() { Map<String, Object> props = new HashMap<>(); props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,"192.168.2.83:9092,192.168.2.84:9092,192.168.2.86:9092"); props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, IntegerDeserializer.class); props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class); props.put(ErrorHandlingDeserializer.KEY_DESERIALIZER_CLASS, JsonDeserializer.class); props.put(ErrorHandlingDeserializer.VALUE_DESERIALIZER_CLASS, JsonDeserializer.class.getName()); props.put(ConsumerConfig.REQUEST_TIMEOUT_MS_CONFIG,3000); return props; } }
注意,要设置容器属性必须使用getContainerProperties()工厂方法。它用作注入容器的实际属性的模板
配置好后,我们就可以使用这个注解了。这个注解的使用有多种方式:
1、用它来覆盖容器工厂的concurrency和属性
@KafkaListener(id = "myListener", topics = "myTopic",
autoStartup = "${listen.auto.start:true}", concurrency = "${listen.concurrency:3}")
public void listen(String data) {
...
}
2、可以使用显式主题和分区(以及可选的初始偏移量)
@KafkaListener(id = "thing2", topicPartitions =
{ @TopicPartition(topic = "topic1", partitions = { "0", "1" }),
@TopicPartition(topic = "topic2", partitions = "0",
partitionOffsets = @PartitionOffset(partition = "1", initialOffset = "100"))
})
public void listen(ConsumerRecord<?, ?> record) {
...
}
3、将初始偏移应用于所有已分配的分区
@KafkaListener(id = "thing3", topicPartitions =
{ @TopicPartition(topic = "topic1", partitions = { "0", "1" },
partitionOffsets = @PartitionOffset(partition = "*", initialOffset = "0"))
})
public void listen(ConsumerRecord<?, ?> record) {
...
}
4、指定以逗号分隔的分区列表或分区范围
@KafkaListener(id = "pp", autoStartup = "false",
topicPartitions = @TopicPartition(topic = "topic1",
partitions = "0-5, 7, 10-15"))
public void process(String in) {
...
}
5、可以向侦听器提供Acknowledgment
@KafkaListener(id = "cat", topics = "myTopic",
containerFactory = "kafkaManualAckListenerContainerFactory")
public void listen(String data, Acknowledgment ack) {
...
ack.acknowledge();
}
6、添加标头
@KafkaListener(id = "list", topics = "myTopic", containerFactory = "batchFactory")
public void listen(List<String> list,
@Header(KafkaHeaders.RECEIVED_KEY) List<Integer> keys,
@Header(KafkaHeaders.RECEIVED_PARTITION) List<Integer> partitions,
@Header(KafkaHeaders.RECEIVED_TOPIC) List<String> topics,
@Header(KafkaHeaders.OFFSET) List<Long> offsets) {
...
}
我们这里写一个简单的,只用它来接受指定主题的数据:
@Component
public class KafkaConsumer {
private static final Logger consumerlog = LoggerFactory.getLogger(KafkaConsumer.class);
@KafkaListener(topicPartitions = @TopicPartition(topic = "kafka-topic-test",
partitions = "0"))
public void consumer (String data){
consumerlog.info("消费者接收数据 {}",data);
}
}
这里解释一下,因为我们进行了手动分配主题/分区,所以 注解中group.id 可以为空。若要指定group.id请在消费者配置中加上props.put(ConsumerConfig.GROUP_ID_CONFIG, “bzt001”); 或在 @TopicPartition 注解后加上 groupId = “组id”
继续使用postman调用我们写好的发布者发布消息,观察控制台的消费者类是否有相关日志出现。
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