本文介绍了spring boot与kafka集成的简单实例,分享给大家,具体如下:
引入相关依赖
1
2
3
4
5
6
7
8
9
10
|
< dependency > < groupId >org.springframework.boot</ groupId > < artifactId >spring-boot-starter</ artifactId > </ dependency > < dependency > < groupId >org.springframework.kafka</ groupId > < artifactId >spring-kafka</ artifactId > < version >1.1.1.RELEASE</ version > </ dependency > |
从依赖项的引入即可看出,当前spring boot(1.4.2)还不支持完全以配置项的配置来实现与kafka的无缝集成。也就意味着必须通过java config的方式进行手工配置。
定义kafka基础配置
与redisTemplate及jdbcTemplate等类似。spring同样提供了org.springframework.kafka.core.KafkaTemplate作为kafka相关api操作的入口。
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
|
import java.util.HashMap; import java.util.Map; import org.apache.kafka.clients.producer.ProducerConfig; import org.apache.kafka.common.serialization.StringSerializer; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.kafka.annotation.EnableKafka; import org.springframework.kafka.core.DefaultKafkaProducerFactory; import org.springframework.kafka.core.KafkaTemplate; import org.springframework.kafka.core.ProducerFactory; @Configuration @EnableKafka public class KafkaProducerConfig { public Map<String, Object> producerConfigs() { Map<String, Object> props = new HashMap<>(); props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.179.200:9092" ); props.put(ProducerConfig.RETRIES_CONFIG, 0 ); props.put(ProducerConfig.BATCH_SIZE_CONFIG, 4096 ); props.put(ProducerConfig.LINGER_MS_CONFIG, 1 ); props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 40960 ); props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer. class ); props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer. class ); return props; } public ProducerFactory<String, String> producerFactory() { return new DefaultKafkaProducerFactory<>(producerConfigs()); } @Bean public KafkaTemplate<String, String> kafkaTemplate() { return new KafkaTemplate<String, String>(producerFactory()); } } |
KafkaTemplate依赖于ProducerFactory,而创建ProducerFactory时则通过一个Map指定kafka相关配置参数。通过KafkaTemplate对象即可实现消息发送。
1
2
3
|
kafkaTemplate.send( "test-topic" , "hello" ); or kafkaTemplate.send( "test-topic" , "key-1" , "hello" ); |
监听消息配置
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
import org.apache.kafka.clients.consumer.ConsumerConfig; import org.apache.kafka.common.serialization.StringDeserializer; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.kafka.annotation.EnableKafka; import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory; import org.springframework.kafka.config.KafkaListenerContainerFactory; import org.springframework.kafka.core.ConsumerFactory; import org.springframework.kafka.core.DefaultKafkaConsumerFactory; import org.springframework.kafka.listener.ConcurrentMessageListenerContainer; import java.util.HashMap; import java.util.Map; @Configuration @EnableKafka public class KafkaConsumerConfig { @Bean public KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String, String>> kafkaListenerContainerFactory() { ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>(); factory.setConsumerFactory(consumerFactory()); factory.setConcurrency( 3 ); factory.getContainerProperties().setPollTimeout( 3000 ); return factory; } public ConsumerFactory<String, String> consumerFactory() { return new DefaultKafkaConsumerFactory<>(consumerConfigs()); } public Map<String, Object> consumerConfigs() { Map<String, Object> propsMap = new HashMap<>(); propsMap.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.179.200:9092" ); propsMap.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false ); propsMap.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "100" ); propsMap.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "15000" ); propsMap.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer. class ); propsMap.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer. class ); propsMap.put(ConsumerConfig.GROUP_ID_CONFIG, "test-group" ); propsMap.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest" ); return propsMap; } @Bean public Listener listener() { return new Listener(); } } |
实现消息监听的最终目标是得到监听器对象。该监听器对象自行实现。
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
|
import org.apache.kafka.clients.consumer.ConsumerRecord; import org.springframework.kafka.annotation.KafkaListener; import java.util.Optional; public class Listener { @KafkaListener (topics = { "test-topic" }) public void listen(ConsumerRecord<?, ?> record) { Optional<?> kafkaMessage = Optional.ofNullable(record.value()); if (kafkaMessage.isPresent()) { Object message = kafkaMessage.get(); System.out.println( "listen1 " + message); } } } |
只需用@KafkaListener指定哪个方法处理消息即可。同时指定该方法用于监听kafka中哪些topic。
注意事项
定义监听消息配置时,GROUP_ID_CONFIG配置项的值用于指定消费者组的名称,如果同组中存在多个监听器对象则只有一个监听器对象能收到消息。
@KafkaListener中topics属性用于指定kafka topic名称,topic名称由消息生产者指定,也就是由kafkaTemplate在发送消息时指定。
KEY_DESERIALIZER_CLASS_CONFIG与VALUE_DESERIALIZER_CLASS_CONFIG指定key和value的编码、解码策略。kafka用key值确定value存放在哪个分区中。
后记
时间是解决问题的有效手段之一。
在spring boot 1.5版本中即可实现spring boot与kafka Auto-configuration
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。
原文链接:http://www.jianshu.com/p/907731a373a4