1.kafka集群配置的话需要在本地host文件里配置
如下:
192.168.5.11 kafka1
192.168.5.12 kafka2
192.168.5.13 kafka3
192.168.5.14 kafka4
192.168.5.15 kafka5
192.168.5.16 kafka6
2.先引依赖
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>
这是对应的版本,千万不要引错版本,负责回报找不到类这种异常
3.在application.yml中进行配置kafka
kafka:
bootstrap-servers: 192.168.5.11:9092,192.168.5.12:9092,192.168.5.13:9092,192.168.5.14:9092,192.168.5.15:9092
producer:
retries: 0
batch-size: 16384
buffer-memory: 33554432
key-serializer: org.apache.kafka.common.serialization.StringSerializer
value-serializer: org.apache.kafka.common.serialization.StringSerializer
properties:
linger.ms: 1
consumer:
enable-auto-commit: false
auto-commit-interval: 100ms
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
properties:
session.timeout.ms: 15000
group-id: test-group-id
listener:
# 在侦听器容器中运行的线程数。
concurrency: 5
#listner负责ack,每调用一次,就立即commit
ack-mode: manual_immediate
missing-topics-fatal: false
4.可配置kafkaconfig也可让springboot自动装配
@Configuration
@EnableKafka
public class KafkaConfig {
@Value("${spring.kafka.bootstrap-servers}")
private String servers;
@Value("${spring.kafka.producer.retries}")
private int retries;
@Value("${spring.kafka.producer.batch-size}")
private int batchSize;
@Value("${spring.kafka.producer.properties.linger.ms}")
private int linger;
@Value("${spring.kafka.producer.buffer-memory}")
private int bufferMemory;
@Bean
public ProducerFactory<String, Object> producerFactory() {
return new DefaultKafkaProducerFactory<>(producerConfig());
}
@Bean
public Map<String, Object> producerConfig() {
Map<String, Object> props = new HashMap<>();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, servers);
props.put(ProducerConfig.RETRIES_CONFIG, retries);
props.put(ProducerConfig.BATCH_SIZE_CONFIG, batchSize);
props.put(ProducerConfig.LINGER_MS_CONFIG, linger);
props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, bufferMemory);
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return props;
}
@Bean
public KafkaTemplate<String, Object> kafkaTemplate() {
return new KafkaTemplate<String, Object>(producerFactory());
}
@Bean//通过bean创建(bean的名字为initialTopic)
public NewTopic initialTopic() {
return new NewTopic("test",3, (short) 1 );
}
@Bean //创建一个kafka管理类,相当于rabbitMQ的管理类rabbitAdmin,没有此bean无法自定义的使用adminClient创建topic
public KafkaAdmin kafkaAdmin() {
Map<String, Object> props = new HashMap<>();
//配置Kafka实例的连接地址
//kafka的地址,不是zookeeper
props.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG, servers);
KafkaAdmin admin = new KafkaAdmin(props);
return admin;
}
@Bean //kafka客户端,在spring中创建这个bean之后可以注入并且创建topic,用于集群环境,创建对个副本
public AdminClient adminClient() {
return AdminClient.create(kafkaAdmin().getConfig());
}
}
5.注入kafkaTemplate,生产者发送消息
@Slf4j
public class TestHandlerKafka {
@Autowired
private KafkaTemplate<String, Object> kafkaTemplate;
private static final String TOPIC_NOTIFY = "test";
@Autowired
private KafkaSendResultHandler producerListener;
public ResponseStatusList producer() {
ResponseStatusList responseStatusList = new ResponseStatusList();
try {
//发送消息前配置回调
kafkaTemplate.setProducerListener(producerListener);
String key = "test";
ListenableFuture<SendResult<String, Object>> send = kafkaTemplate.send(TOPIC_NOTIFY, key, JSON.toJSONString(entity));
SendResult<String, Object> stringObjectSendResult = send.get();
log.info("发送消息成功,", stringObjectSendResult);
responseStatusList.setLocalDate(new Date());
responseStatusList.setStatusCode("0");
responseStatusList.setStatusString("正常");
return responseStatusList;
} catch (Exception e) {
log.error(Status.KAFKA_SEND_ERROR.getMsg(), e);
responseStatusList.setLocalDate(new Date());
responseStatusList.setStatusCode("1");
responseStatusList.setStatusString("其他未知错误");
return responseStatusList;
}
}
}
6.可进行简单的消费
@Component
public class KafkaConsumer {
private static final String TOPIC_NOTIFY = "test";
// 消费监听
@KafkaListener(topics = {TOPIC_NOTIFY})
public void onMessage1(ConsumerRecord<?, ?> record){
// 消费的哪个topic、partition的消息,打印出消息内容
System.err.println("简单消费:"+record.topic()+"-"+record.partition()+"-"+record.value());
}
}