SpringBoot+Redis实现接口限流
原文链接:https://mp.weixin.qq.com/s/xa7oLSiSnYlVPEyMReCCaQ
1.使用maven添加依赖库,本项目中使用的是:
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis</artifactId> <version>2.1.4.RELEASE</version> </dependency>
2.配置redis服务
下载地址:
https://github.com/MicrosoftArchive/redis/releases
下载完成后启动即可
linux安装教程可参考:
https://blog.csdn.net/fm_vae/article/details/80234340
3.回到正题,目的是使用redis达到接口限流的效果。
定义一个注解标明需要使用限流的接口
@Retention(RUNTIME) @Target(METHOD) public @interface AccessLimit { int seconds(); int maxCount(); }
在springboot的拦截器中,如果你没有配置拦截器,需要自定义类继承HandlerInterceptor
,
@Override public boolean preHandle(HttpServletRequest httpServletRequest, HttpServletResponse httpServletResponse, Object handler) throws Exception { //如果请求输入方法 if (handler instanceof HandlerMethod) { HandlerMethod hm = (HandlerMethod) handler; //获取方法中的注解,看是否有该注解 AccessLimit accessLimit = hm.getMethodAnnotation(AccessLimit.class); if (accessLimit != null) { long seconds = accessLimit.seconds(); int maxCount = accessLimit.maxCount(); //关于key的生成规则可以自己定义 本项目需求是对每个方法都加上限流功能,如果你只是针对ip地址限流,那么key只需要只用ip就好 String key = SystemUtil.getClientIp(httpServletRequest)+hm.getMethod().getName(); //从redis中获取用户访问的次数 try { long q = redisService.incr(key, seconds);//此操作代表获取该key对应的值自增1后的结果 if (q > maxCount) { //加1 render(httpServletResponse, new ResponseMsg(0, "请求过于频繁,请稍候再试", null)); //这里的CodeMsg是一个返回参数 return false; } return true; }catch (RedisConnectionFailureException e){ logger.info("redis错误"+e.getMessage().toString()); return true; } } } return false; } private void render(HttpServletResponse response, ResponseMsg cm) throws Exception { response.setContentType("application/json;charset=UTF-8"); OutputStream out = response.getOutputStream(); String str = new Gson().toJson(cm); out.write(str.getBytes("UTF-8")); out.flush(); out.close(); }
上面使用到的redisservice
public interface RedisService { /** * set存数据 * @param key * @param value * @return */ boolean set(String key, String value); /** * get获取数据 * @param key * @return */ String get(String key); /** * 设置有效天数 * @param key * @param expire * @return */ boolean expire(String key, long expire); /** * 移除数据 * @param key * @return */ boolean remove(String key); /** * 获取自增1后的 值 * @param key * @param time * @return */ Long incr(String key,long time); }
redisservice的实现类
@Service("redisService") public class RedisServiceImpl implements RedisService { @Resource private RedisTemplate<String, ?> redisTemplate; @Override public boolean set(final String key, final String value) { boolean result = redisTemplate.execute(new RedisCallback<Boolean>() { @Override public Boolean doInRedis(RedisConnection connection) throws DataAccessException { RedisSerializer<String> serializer = redisTemplate.getStringSerializer(); connection.set(serializer.serialize(key), serializer.serialize(value)); return true; } }); return result; } @Override public String get(final String key) { String result = redisTemplate.execute(new RedisCallback<String>() { @Override public String doInRedis(RedisConnection connection) throws DataAccessException { RedisSerializer<String> serializer = redisTemplate.getStringSerializer(); byte[] value = connection.get(serializer.serialize(key)); return serializer.deserialize(value); } }); return result; } @Override public boolean expire(final String key, long expire) { return redisTemplate.expire(key, expire, TimeUnit.SECONDS); } @Override public boolean remove(final String key) { boolean result = redisTemplate.execute(new RedisCallback<Boolean>() { @Override public Boolean doInRedis(RedisConnection connection) throws DataAccessException { RedisSerializer<String> serializer = redisTemplate.getStringSerializer(); connection.del(key.getBytes()); return true; } }); return result; } @Override public Long incr(String key,long time){ long count = redisTemplate.opsForValue().increment(key, 1); if (count == 1) { //设置有效期一分钟 set(key,"1"); redisTemplate.expire(key, time, TimeUnit.SECONDS); } return count; } }
至此限流的准备工作都做完了,测试一下ok,在controller方法中加上如下注解即可
@AccessLimit(seconds=second, maxCount=maxCount)