RedisLua限流实现

Abel sun2022年12月24日

架构

约 493 字大约 2 分钟

RedisLua限流实现

1. Redis 配置

其中配置了默认的限流脚本就是采用Lua 的形式


/**
 * redis配置
 * 
 */
@Configuration
@EnableCaching
public class RedisConfig extends CachingConfigurerSupport
{
    @Bean
    @SuppressWarnings(value = { "unchecked", "rawtypes" })
    public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory connectionFactory)
    {
        RedisTemplate<Object, Object> template = new RedisTemplate<>();
        template.setConnectionFactory(connectionFactory);

        FastJson2JsonRedisSerializer serializer = new FastJson2JsonRedisSerializer(Object.class);

        ObjectMapper mapper = new ObjectMapper();
        mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
        mapper.activateDefaultTyping(LaissezFaireSubTypeValidator.instance, ObjectMapper.DefaultTyping.NON_FINAL, JsonTypeInfo.As.PROPERTY);
        serializer.setObjectMapper(mapper);

        // 使用StringRedisSerializer来序列化和反序列化redis的key值
        template.setKeySerializer(new StringRedisSerializer());
        template.setValueSerializer(serializer);

        // Hash的key也采用StringRedisSerializer的序列化方式
        template.setHashKeySerializer(new StringRedisSerializer());
        template.setHashValueSerializer(serializer);

        template.afterPropertiesSet();
        return template;
    }

    @Bean
    public DefaultRedisScript<Long> limitScript()
    {
        DefaultRedisScript<Long> redisScript = new DefaultRedisScript<>();
        redisScript.setScriptText(limitScriptText());
        redisScript.setResultType(Long.class);
        return redisScript;
    }

    /**
     * 限流脚本
     */
    private String limitScriptText()
    {
        return "local key = KEYS[1]\n" +
                "local count = tonumber(ARGV[1])\n" +
                "local time = tonumber(ARGV[2])\n" +
                "local current = redis.call('get', key);\n" +
                "if current and tonumber(current) > count then\n" +
                "    return tonumber(current);\n" +
                "end\n" +
                "current = redis.call('incr', key)\n" +
                "if tonumber(current) == 1 then\n" +
                "    redis.call('expire', key, time)\n" +
                "end\n" +
                "return tonumber(current);";
    }
}

2. 定义限流注解


/**
 * 限流注解
 */
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
@Documented
public @interface RateLimiter
{
    /**
     * 限流key
     */
    public String key() default Constants.RATE_LIMIT_KEY;

    /**
     * 限流时间,单位秒
     */
    public int time() default 60;

    /**
     * 限流次数
     */
    public int count() default 100;

    /**
     * 限流类型
     */
    public LimitType limitType() default LimitType.DEFAULT;
}

3. 定义限流类型


/**
 * 限流类型
 */
public enum LimitType
{
    /**
     * 默认策略全局限流
     */
    DEFAULT,

    /**
     * 根据请求者IP进行限流
     */
    IP
}

4. 限流切面


/**
 * 限流处理
 *
 * @author fd
 */
@Aspect
@Component
public class RateLimiterAspect
{
    private static final Logger log = LoggerFactory.getLogger(RateLimiterAspect.class);

    private RedisTemplate<Object, Object> redisTemplate;

    private RedisScript<Long> limitScript;

    @Autowired
    public void setRedisTemplate1(RedisTemplate<Object, Object> redisTemplate)
    {
        this.redisTemplate = redisTemplate;
    }

    @Autowired
    public void setLimitScript(RedisScript<Long> limitScript)
    {
        this.limitScript = limitScript;
    }

    @Before("@annotation(rateLimiter)")
    public void doBefore(JoinPoint point, RateLimiter rateLimiter) throws Throwable
    {
        String key = rateLimiter.key();
        int time = rateLimiter.time();
        int count = rateLimiter.count();

        String combineKey = getCombineKey(rateLimiter, point);
        List<Object> keys = Collections.singletonList(combineKey);
        try
        {
            Long number = redisTemplate.execute(limitScript, keys, count, time);
            if (StringUtils.isNull(number) || number.intValue() > count)
            {
                throw new ServiceException("访问过于频繁，请稍候再试");
            }
            log.info("限制请求'{}',当前请求'{}',缓存key'{}'", count, number.intValue(), key);
        }
        catch (ServiceException e)
        {
            throw e;
        }
        catch (Exception e)
        {
            throw new RuntimeException("服务器限流异常，请稍候再试");
        }
    }

    public String getCombineKey(RateLimiter rateLimiter, JoinPoint point)
    {
        StringBuffer stringBuffer = new StringBuffer(rateLimiter.key());
        if (rateLimiter.limitType() == LimitType.IP)
        {
            stringBuffer.append(IpUtils.getIpAddr(ServletUtils.getRequest())).append("-");
        }
        MethodSignature signature = (MethodSignature) point.getSignature();
        Method method = signature.getMethod();
        Class<?> targetClass = method.getDeclaringClass();
        stringBuffer.append(targetClass.getName()).append("-").append(method.getName());
        return stringBuffer.toString();
    }
}

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RedisLua限流实现

# RedisLua限流实现

# 1. Redis 配置

# 2. 定义限流注解

# 3. 定义限流类型

# 4. 限流切面

预览:

RedisLua限流实现

1. Redis 配置

2. 定义限流注解

3. 定义限流类型

4. 限流切面