投稿
  1. 首页
  2. 随笔

kafka笔记

adobe是什么 • 2022-12-17 • 随笔 • 阅读 30

kafka笔记,第1张

kafka笔记

一.概述

消息对于现代软件项目来说，占有很重要的地位；同时市场上也发展处ActiveMq、RabbitMQ、Kafka、RocketMQ、Pulsar等众多优秀的框架；这些优秀的框架都由自身的特点和擅长的业务领域，在大数据领域中Kafka目前是使用较多的框架，Pulsar是一个后起之秀，目前处于一个快速发展的状态，有望能够成为下一代中间件的黑马。在本案例中我们选择使用Kafka作为内部消息通知的框架，以适应项目中大数据量的高吞吐、实时流计算等功能实现。

二.约束定义

Topic命名约束

Topic分为单类和混合类消息，不同类的消息命名约束如下：

单类：xxx.topic.[自定义名称].sigle混合类：xxx.topic.[自定义名称].bus

三.各类介绍

KafkaProducerConfig自动配置Kafka生产者KafkaConsumerConfig自动配置Kafka消费者RetryErrorHandler实现消费者处理消息失败后重新发送到消息队列KafkaMessage实现对发送的消息包装，提供重试次数、分类等信息KafkaSender实现消息的统一发送入口功能KafkaTopicConfig自动装载topic名称信息KafkaListener提供自动注册消息消费监听接口类KafkaListenerFactory提供启动时自动注册实现了KafkaListener的消息消费者

四.实现

    配置文件
    Kafka功能有独立的配置文件，放置在srcmainresourceskafka.properties，相关的值在maven_*.properties中配置。
# kafka config
kafka.hosts=localhost:9092
kafka.group=xxx.${profiles.name}.${spring.application.name}

# 单消息通道，需要以sigle结尾
kafka.topic.admin-test=${kafka.topic.admin-test}
    KafkaMessage
    创建类com.xxx.common.kafka.KafkaMessage。KafkaMessage是一个抽象类包含记录当前消息重发处理的次数retry、消息类型type、第一次创建消息的时间time信息。
public abstract class KafkaMessage {
	// 尝试次数
	@Getter
	int retry;
	// 生成时间
	@Getter
	long time = System.currentTimeMillis();

	// 消息类型
	String type;
	// 消息实体数据
	@Setter
	@Getter
	T data;
	public KafkaMessage(){}
	public KafkaMessage(T data){
		this.data = data;
	}
	public void addRetry(){
		this.retry++;
	}
	// 获取消息类型
	protected abstract String getType();
}
    KafkaListener
    创建类com.xxx.common.kafka.KafkaListener。KafkaListener是一个接口，继承ConsumerAwareMessageListener（提供Consumer信息和自动提交offsets功能）接口。

    topic方法用于返回监听器监听的topic名称factory方法用于指定监听器容器的创建工厂group方法用于指定监听器的groupid 

public interface KafkaListener extends ConsumerAwareMessageListener {
	String topic();
	default String factory(){
		return "defaultKafkaListenerContainerFactory";
	}
	default String group(){ return "default";}
}
    KafkaTopicConfig

创建类：com.xxx.common.kafka.KafkaTopicConfig。KafkaTopicConfig用于自动装入kafka.properties文件中的kafka.topic.*信息

@Data
@Configuration
@ConfigurationProperties(prefix="kafka.topic")
@PropertySource("classpath:kafka.properties")
public class KafkaTopicConfig {
	String userLogin;
	String userLogout;
	String userRefresh;
	String userRegister;
	String hotArticle;
}
    KafkaProducerConfig
    创建类com.xxx.common.kafka.KafkaProducerConfig。KafkaProducerConfig类是自动化配置类，定义了默认的Producer工厂，以及KafkaTemplate，并约束了消息的类型为String，大小不超过16M。
@Data
@Configuration
@EnableKafka
@ConfigurationProperties(prefix="kafka")
@PropertySource("classpath:kafka.properties")
public class KafkaProducerConfig {
	private static final int MAX_MESSAGE_SIZE = 16* 1024 * 1024;
	private String hosts;
	
	@Autowired(required = false)
	private ProducerListener producerListener;
	
	@Bean
	public DefaultKafkaProducerFactory producerFactory() {
		Map props = new HashMap<>();
		props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, this.getHosts());
		props.put(ProducerConfig.RETRIES_CONFIG, 10);
		props.put(ProducerConfig.RETRY_BACKOFF_MS_CONFIG, 5_000);
		props.put(ProducerConfig.BUFFER_MEMORY_CONFIG,3*MAX_MESSAGE_SIZE);
		props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,
StringSerializer.class);
		props.put(ProducerConfig.MAX_REQUEST_SIZE_CONFIG,3*MAX_MESSAGE_SIZE);
		props.put(ProducerConfig.COMPRESSION_TYPE_CONFIG, "lz4");
		props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
		props.put(ProducerConfig.BATCH_SIZE_CONFIG, 256 * 1024);
		return new DefaultKafkaProducerFactory<>( props);
	}
	
	@Bean
	public KafkaTemplate kafkaTemplate(ProducerFactory producerFactory) {
		KafkaTemplate t = new KafkaTemplate<>		(producerFactory);
		if (this.producerListener != null) {
			t.setProducerListener(this.producerListener);
		}
		return t;
	}
}
    KafkaSender
    创建类com.xxx.common.kafka.KafkaSender。KafkaSender类是所有发送消息的方法统一管理器，其实是通过kafkaTemplate发送。
@Component
public class KafkaSender {
	Logger logger = LoggerFactory.getLogger(KafkaSender.class);
	
	@Autowired
	KafkaTemplate kafkaTemplate;
	@Autowired
	ObjectMapper mapper;
	@Autowired
	KafkaTopicConfig kafkaTopicConfig;
	
	
	public void sendMesssage(String topic, String key, KafkaMessage message){
		try {
			this.kafkaTemplate.send(topic, key, mapper.writevalueAsString(message));
		}catch (Exception e){
			logger.error("send message to [{}] error:",topic,e);
		}
	}
	
	
	public void sendMesssageNoWrap(String topic, String key, String message){
		try {
			this.kafkaTemplate.send(topic, key, message);
		}catch (Exception e){
			logger.error("send message to [{}] error:",topic,e);
		}
	}
}
    RetryErrorHandler
    创建类com.xxx.common.kafka.RetryErrorHandler。RetryErrorHandler类用于在消费者解析消息出现错误时，重新放回消息到队列中，并设置超过一个小时或者超过10次处理错误的消息丢弃，避免消息无限滚动；然后这类消息可以通过日志搜索查找出数据补偿重试。
@Component
public class RetryErrorHandler extends LoggingErrorHandler {
	private static Logger logger =
	LoggerFactory.getLogger(RetryErrorHandler.class);
	private static final int RETRY_COUNT = 10;
	private static final int TIME_OUT = 3_600_000;//1个小时超时
	
	@Autowired
	KafkaSender sender;
	@Autowired
	ObjectMapper mapper;
	
	@Override
	public void handle(Exception thrownException, ConsumerRecord record) {
		super.handle(thrownException, record);
		if (record != null) {
			try{
				KafkaMessage message =
				mapper.readValue((String)record.value(),KafkaMessage.class);
				message.addRetry();
				long time = System.currentTimeMillis()-message.getTime();
				if(message.getRetry()>RETRY_COUNT||time>TIME_OUT){
					logger.info("超时或者尝试{}次后，抛弃消息[topic:{}][{}]",RETRY_COUNT,record.topic(),record.value());
				}else{
					this.sender.sendMesssage(record.topic(), (String)record.key(), message);
					logger.info("处理失败重新回滚到队列[retry:{}][topic:{}][key:{}]", message.getRetry(), record.topic(), record.key());
}
			}catch (Exception e){
				sender.sendMesssageNoWrap(record.topic(), (String) record.key(), (String) record.value());
			}
		}
	}
}
    KafkaProducerConfig
    创建类com.xxx.common.kafka.KafkaProducerConfig。KafkaProducerConfig主要配置消费者监听器，配置重试器、错误处理器等信息，同时设置group消费者。
@Data
@Configuration
@EnableKafka
@ConfigurationProperties(prefix="kafka")
@PropertySource("classpath:kafka.properties")
public class KafkaConsumerConfig {
	private static final int ConCURRENCY = 8;
	public final static Logger LOGGER = LoggerFactory.getLogger(KafkaConsumerConfig.class);
 	String hosts;
	String group;

	@Bean("defaultKafkaListenerContainerFactory")
	public ConcurrentKafkaListenerContainerFactory kafkaListenerContainerFactory(RetryErrorHandler retryErrorHandler) {
		ConcurrentKafkaListenerContainerFactory factory = new ConcurrentKafkaListenerContainerFactory<>();
		factory.setRetryTemplate(this.buildRetryTemplate());
		factory.setErrorHandler(retryErrorHandler);
		factory.getContainerProperties().setAckOnError(false);
		factory.setConsumerFactory(new DefaultKafkaConsumerFactory<>
(buildComsumerConfig()));
		factory.setConcurrency(KafkaConsumerConfig.CONCURRENCY);
		return factory;
	}
	
	protected Map buildComsumerConfig() {
		Map propsMap = new HashMap<>();
		propsMap.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, this.getHosts());
		propsMap.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false);
		propsMap.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG,
StringDeserializer.class);
		propsMap.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,StringDeserializer.class);
		propsMap.put(ConsumerConfig.GROUP_ID_CONFIG, this.group);
		propsMap.put(ConsumerConfig.MAX_PARTITION_FETCH_BYTES_CONFIG, 8 * 1024 * 1024);
		propsMap.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, 90_000);
   		return propsMap;
}

	private RetryTemplate buildRetryTemplate() {
		RetryTemplate t = new RetryTemplate();
		ExponentialBackOffPolicy backOff = new ExponentialRandomBackOffPolicy();
		backOff.setInitialInterval(1000L);
		t.setBackOffPolicy(backOff);
		t.setRetryPolicy(new SimpleRetryPolicy(5));
		t.registerListener(new RetryListenerSupport() {
			@Override
			public  void onError(RetryContext context, RetryCallback callback, Throwable throwable) {
				KafkaConsumerConfig.LOGGER.warn("Retry processing Kafka message" + context.getRetryCount() + " times", throwable);
			}
		});
		return t;
	}
}
    KafkaListenerFactory
    创建类com.xxx.common.kafka.KafkaListenerFactory。KafkaListenerFactory类实现在构造之后扫描实现了的KafkaListener接口的Bean，并自动注册成消费者监听器。
@Component
public class KafkaListenerFactory implements InitializingBean {
	Logger logger = LoggerFactory.getLogger(KafkaListenerFactory.class);
	
	@Autowired
	DefaultListableBeanFactory defaultListableBeanFactory;
	
	@Override
	public void afterPropertiesSet() {
		Map map = defaultListableBeanFactory.getBeansOfType(KafkaListener.class);
		for (String key : map.keySet()) {
			KafkaListener k = map.get(key);
			AbstractKafkaListenerContainerFactory factory = (AbstractKafkaListenerContainerFactory)defaultListableBeanFactory.getBean(k.factory());
			AbstractMessageListenerContainer container = factory.createContainer(k.topic());
			container.setupMessageListener(k);
			String beanName = k.getClass().getSimpleName()+"AutoListener" ;
			defaultListableBeanFactory.registerSingleton(beanName,container);
			logger.info("add auto listener [{}]",beanName);
		}
	}
}
    MessagesRegister
@Log4j2
@Component
public class MessagesRegister implements InitializingBean {
	Map messages = Maps.newConcurrentMap();
	
	@Override
	public void afterPropertiesSet() throws Exception {
		Reflections reflections = new Reflections("com.xxx");
		Set> ms = reflections.getSubTypesOf(KafkaMessage.class);
		if(ms!=null){
			ms.forEach(cla->{
				try {
					Constructor[] cs = cla.getConstructors();
					KafkaMessage mess = null;
					if (cs != null && cs.length > 0) {
						Class[] temp = cs[0].getParameterTypes();
						Object[] parms = new Object[temp.length];
						for (int i = 0; i < temp.length; i++) {
							if(temp[i].isPrimitive()){
								if(temp[i].getName().contains("boolean")){
									parms[i]=false;
								}else {
									parms[i] = 0;
								}
							}else{
								parms[i]=null;
							}
						}
						mess = (KafkaMessage) cs[0].newInstance(parms);
					} else {
						mess = (KafkaMessage) cla.newInstance();
					}
					String type = mess.getType();
					messages.put(type,cla);
				}catch (Exception e){
					System.out.println(cla+"====================:"+cla.getConstructors()[0].getParameterCount());
					e.printStackTrace();
				}
			});
		}
		log.info("=================================================");
		log.info("scan kafka message resultt[{}]",messages);
		log.info("=================================================");
	}
	
	
	public Class findClassByType(String type){
		return this.messages.get(type);
	}
}

五.消息生产者

@SpringBootTest
@RunWith(SpringRunner.class)
public class KafkaTest {

	@Autowired
	KafkaTemplate kafkaTemplate;
	
	@Test
	public void test(){
		try {
			this.kafkaTemplate.send("topic.test", "123key","123value");
			System.out.println("=================================");
			Thread.sleep(500000);// 休眠等待消费者接收消息
		} catch (Exception e) {
			e.printStackTrace();
		}
	}
}

六.消息消费者

@Component
public class TestKafkaListener implements KafkaListener {
	@Override
	public String topic () {
		return "topic.test";
	}
	@Override
	public void onMessage (ConsumerRecord< String, String > data, Consumer< ?, ? > consumer){
		System.out.println("===========receive test message:" + data);
	}
}

欢迎分享，转载请注明来源：内存溢出

原文地址: http://outofmemory.cn/zaji/5705952.html

赞 (0)
打赏 微信扫一扫 微信扫一扫 支付宝扫一扫 支付宝扫一扫
adobe是什么 adobe是什么 一级用户组
0 0
上一篇 2022-12-17
下一篇 2022-12-17

发表评论

登录后才能评论

评论列表（0条）

保存