springboot整合redis之消息队列

2022-11-13 11:11:47 整合消息队列

一、项目准备

依赖

        <!-- RedisTemplate -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-data-redis</artifactId>
        </dependency>
        <!-- Redis-Jedis -->
        <dependency>
            <groupId>redis.clients</groupId>
            <artifactId>jedis</artifactId>
            <version>2.9.0</version>
        </dependency>

application.yaml配置文件

spring:
  redis:
    host: 127.0.0.1
    port: 6379
    database: 0
    timeout: 4000
    jedis:
      pool:
        max-wait: -1
        max-active: -1
        max-idle: 20
        min-idle: 10

二、配置类

public class ObjectMapperConfig {

    public static final ObjectMapper objectMapper;
    private static final String PATTERN = "yyyy-MM-dd HH:mm:ss";

    static {
        JavaTimeModule javaTimeModule = new JavaTimeModule();
        javaTimeModule.addSerializer(LocalDateTime.class, new LocalDateTimeSerializer());
        javaTimeModule.aDDDeserializer(LocalDateTime.class, new LocalDateTimeDeserializer());
        objectMapper = new ObjectMapper()
                // 转换为格式化的JSON(控制台打印时，自动格式化规范)
                //.enable(SerializationFeature.INDENT_OUTPUT)
                // Include.ALWAYS  是序列化对像所有属性(默认)
                // Include.NON_NULL 只有不为null的字段才被序列化,属性为NULL 不序列化
                // Include.NON_EMPTY 如果为null或者 空字符串和空集合都不会被序列化
                // Include.NON_DEFAULT 属性为默认值不序列化
                .setSerializationInclusion(jsonInclude.Include.NON_NULL)
                // 如果是空对象的时候,不抛异常
                .configure(SerializationFeature.FAIL_ON_EMPTY_BEANS, false)
                // 反序列化的时候如果多了其他属性,不抛出异常
                .configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false)
                // 取消时间的转化格式,默认是时间戳,可以取消,同时需要设置要表现的时间格式
                .configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false)
                .setDateFORMat(new SimpleDateFormat(PATTERN))
                // 对LocalDateTime序列化跟反序列化
                .reGISterModule(javaTimeModule)

                .setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY)
                // 此项必须配置，否则会报java.lang.ClassCastException: java.util.LinkedHashMap cannot be cast to XXX
                .enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL, JsonTypeInfo.As.PROPERTY)
        ;
    }

    static class LocalDateTimeSerializer extends JsonSerializer<LocalDateTime> {
        @Override
        public void serialize(LocalDateTime value, JsonGenerator gen, SerializerProvider serializers) throws IOException {
            gen.writeString(value.format(DateTimeFormatter.ofPattern(PATTERN)));
        }
    }

    static class LocalDateTimeDeserializer extends JsonDeserializer<LocalDateTime> {
        @Override
        public LocalDateTime deserialize(JsonParser p, DeserializationContext deserializationContext) throws IOException {
            return LocalDateTime.parse(p.getValueAsString(), DateTimeFormatter.ofPattern(PATTERN));
        }
    }

}

@Configuration
public class RedisConfig {

    
    @Bean
    public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) {
        RedisTemplate<String, Object> template = new RedisTemplate<>();
        // 配置连接工厂
        template.setConnectionFactory(factory);

        //使用Jackson2JsonRedisSerializer来序列化和反序列化redis的value值（默认使用jdk的序列化方式）
        Jackson2JsonRedisSerializer<Object> jacksonSerializer = new Jackson2JsonRedisSerializer<>(Object.class);
        jacksonSerializer.setObjectMapper(ObjectMapperConfig.objectMapper);
        StringRedisSerializer stringRedisSerializer = new StringRedisSerializer();

        // 使用StringRedisSerializer来序列化和反序列化redis的key,value采用json序列化
        template.seTKEySerializer(stringRedisSerializer);
        template.setValueSerializer(jacksonSerializer);

        // 设置hash key 和value序列化模式
        template.setHashKeySerializer(stringRedisSerializer);
        template.setHashValueSerializer(jacksonSerializer);
        template.afterPropertiesSet();

        return template;
    }
}

三、redis中list数据类型

在Redis中，List类型是按照插入顺序排序的字符串链表。和数据结构中的普通链表一样，我们可以在其头部和尾部添加新的元素

优势：

顺序排序，保证先进先出
队列为空时，自动从Redis数据库删除
在队列的两头插入或删除元素，效率极高，即使队列中元素达到百万级
List中可以包含的最大元素数量是4294967295

定时器监听队列

生产者

@Slf4j
@Component
public class MessageProducer {

    public static final String MESSAGE_KEY = "message:queue";

    @Autowired
    private RedisTemplate<String,Object> redisTemplate;

    public void lPush() {
        for (int i = 0; i < 10; i++) {
            new Thread(() -> {
                Long size = redisTemplate.opsForList().leftPush(MESSAGE_KEY, Thread.currentThread().getName() + "：hello world");
                log.info(Thread.currentThread().getName() + "：put message size = " + size);
            }).start();
        }
    }
}

消费者：消费消息，定时器以达到监听队列功能

@Slf4j
@Component
@EnableScheduling
public class MessageConsumer {

    public static final String MESSAGE_KEY = "message:queue";

    @Autowired
    private RedisTemplate<String,Object> redisTemplate;

    @Scheduled(initialDelay = 5 * 1000, fixedRate = 2 * 1000)
    public void rPop() {
        String message = (String) redisTemplate.opsForList().rightPop(MESSAGE_KEY);
        log.info(message);
    }
}

@RestController
public class RedisController {

    @Autowired
    private MessageProducer messageProducer;

    @GetMapping("/lPush")
    public void lPush() {
        messageProducer.lPush();
    }
}

测试

Http://localhost:8080/lPush

可能出现的问题：

1.通过定时器监听List中是否有待处理消息，每执行一次都会发起一次连接，这会造成不必要的浪费。

2.生产速度大于消费速度，队列堆积，消息时效性差，占用内存。

运行即监控队列

修改消息消费者代码。

当队列没有元素时，会阻塞10秒，然后再次监听队列，
需要注意的是，阻塞时间必须小于连接超时时间

@Slf4j
@Component
@EnableScheduling
public class MessageConsumer {

    public static final String MESSAGE_KEY = "message:queue";

    @Autowired
    private RedisTemplate<String,Object> redisTemplate;

    //@Scheduled(initialDelay = 5 * 1000, fixedRate = 2 * 1000)
    public void rPop() {
        String message = (String) redisTemplate.opsForList().rightPop(MESSAGE_KEY);
        log.info(message);
    }

    @PostConstruct
    public void brPop() {
        new Thread(() -> {
            while (true) {
                String message = (String) redisTemplate.opsForList().rightPop(MESSAGE_KEY, 10, TimeUnit.SECONDS);
                log.info(message);
            }
        }).start();
    }
}

阻塞时间不能为负，直接报错超时为负
阻塞时间为零，此时阻塞时间等于超时时间，最后报错连接超时
阻塞时间大于超时时间，报错连接超时

测试：

消息不可重复消费，因为消息从队列POP之后就被移除了，即不支持多个消费者消费同一批数据

消息丢失，消费期间发生异常，消息未能正常消费

四、发布/订阅模式

消息可以重复消费，多个消费者订阅同一频道即可

一个消费者根据匹配规则订阅多个频道

消费者只能消费订阅之后发布的消息，这意味着，消费者下线再上线这期间发布的消息将会丢失

数据不具有持久化。同样Redis宕机也会数据丢失

消息发布后，是推送到一个缓冲区(内存)，消费者从缓冲区拉取消息，当消息堆积，缓冲区溢出，消费者就会被迫下线，同时释放对应的缓冲区

RedisConfig中添加监听器

    
    @Bean
    public RedisMessageListenerContainer container(RedisConnectionFactory connectionFactory) {
        RedisMessageListenerContainer container = new RedisMessageListenerContainer();
        container.setConnectionFactory(connectionFactory);

        //订阅频道，通配符*表示任意多个占位符
        container.addMessageListener(new MySubscribe(), new PatternTopic("channel*"));

        return container;
    }

订阅者

package com.yzm.redis08.message;

import org.springframework.data.redis.connection.Message;
import org.springframework.data.redis.connection.MessageListener;

public class MySubscribe implements MessageListener {

    @Override
    public void onMessage(Message message, byte[] bytes) {
        System.out.println("订阅频道:" + new String(message.getChannel()));
        System.out.println("接收数据:" + new String(message.getBody()));
    }
}

消息发布

    @GetMapping("/publish")
    public void publish() {
        redisTemplate.convertAndSend("channel_first", "hello world");
    }

另一种发布方式

    
    @Bean
    public RedisMessageListenerContainer container(RedisConnectionFactory connectionFactory) {
        RedisMessageListenerContainer container = new RedisMessageListenerContainer();
        container.setConnectionFactory(connectionFactory);

        //订阅频道，通配符*表示任意多个占位符
        container.addMessageListener(new MySubscribe(), new PatternTopic("channel*"));
        // 通配符?：表示一个占位符
        MessageListenerAdapter listenerAdapter = new MessageListenerAdapter(new MySubscribe2(), "getMessage");
        listenerAdapter.afterPropertiesSet();
        container.addMessageListener(listenerAdapter, new PatternTopic("channel?"));

        return container;
    }

public class MySubscribe2 {

    public void getMessage(Object message, String channel) {
        System.out.println("订阅频道2:" + channel);
        System.out.println("接收数据2:" + message);
    }
}

    @GetMapping("/publish2")
    public void publish2() {
        redisTemplate.convertAndSend("channel2", "hello world");
    }

消息是实体对象，进行转换

@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
public class User implements Serializable {
    private static final long serialVersionUID = 5250232737975907491L;
    private Integer id;
    private String username;
}

public class MySubscribe3 implements MessageListener {

    @Override
    public void onMessage(Message message, byte[] bytes) {
        Jackson2JsonRedisSerializer<User> jacksonSerializer = new Jackson2JsonRedisSerializer<>(User.class);
        jacksonSerializer.setObjectMapper(ObjectMapperConfig.objectMapper);
        User user = jacksonSerializer.deserialize(message.getBody());
        
        System.out.println("订阅频道3:" + new String(message.getChannel()));
        System.out.println("接收数据3:" + user);
    }
}

    
    @Bean
    public RedisMessageListenerContainer container(RedisConnectionFactory connectionFactory) {
        RedisMessageListenerContainer container = new RedisMessageListenerContainer();
        container.setConnectionFactory(connectionFactory);

        //订阅频道，通配符*：表示任意多个占位符
        container.addMessageListener(new MySubscribe(), new PatternTopic("channel*"));
        // 通配符?：表示一个占位符
        MessageListenerAdapter listenerAdapter = new MessageListenerAdapter(new MySubscribe2(), "getMessage");
        listenerAdapter.afterPropertiesSet();
        container.addMessageListener(listenerAdapter, new PatternTopic("channel?"));

        container.addMessageListener(new MySubscribe3(), new PatternTopic("user"));

        return container;
    }

    @GetMapping("/publish3")
    public void publish3() {
        User user = User.builder().id(1).username("yzm").build();
        redisTemplate.convertAndSend("user", user);
    }

五、ZSet实现延迟队列

生产消息，score = 时间搓+60s随机数

    public static final String MESSAGE_ZKEY = "message:ZSetqueue";
    public volatile AtomicInteger count =  new AtomicInteger();
    public void zAdd() {
        for (int i = 0; i < 10; i++) {
            new Thread(() -> {
                int increment = count.getAndIncrement();
                log.info(Thread.currentThread().getName() + "：put message to zset = " + increment);
                double score = System.currentTimeMillis() + new Random().nextInt(60 * 1000);
                redisTemplate.opsForZSet().add(MESSAGE_ZKEY, Thread.currentThread().getName() + " hello zset：" + increment, score);
            }).start();
        }
    }

消费者：定时任务，每秒执行一次

    public static final String MESSAGE_ZKEY = "message:ZSetqueue";
    public SimpleDateFormat simpleDateFormat = new SimpleDateFormat();
    @Scheduled(initialDelay = 5 * 1000, fixedRate = 1000)
    public void zrangebysocre() {
        log.info("延时队列消费。。。");
        // 拉取score小于当前时间戳的消息
        Set<Object> messages = redisTemplate.opsForZSet().rangeByScore(MESSAGE_ZKEY, 0, System.currentTimeMillis());
        if (messages != null) {
            for (Object message : messages) {
                Double score = redisTemplate.opsForZSet().score(MESSAGE_ZKEY, message);
                log.info("消费了：" + message + "消费时间为：" + simpleDateFormat.format(score));
                redisTemplate.opsForZSet().remove(MESSAGE_ZKEY, message);
            }
        }
    }

    @GetMapping("/zadd")
    public void zadd() {
        messageProducer.zAdd();
    }

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