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
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 {
/**
* redisTemplate配置
*/
@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;
}
}
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：
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。
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
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
/**
* redis消息监听器容器
*/
@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
/**
* redis消息监听器容器
*/
@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*"));
// 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);
}
}
/**
* redis消息监听器容器
*/
@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*"));
// 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);
}
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();
}
到此这篇关于springboot整合redis之消息队列的文章就介绍到这了,更多相关springboot redis消息队列内容请搜索以前的文章或继续浏览下面的相关文章希望大家以后多多支持！
