基于twemproxy的redis分布式应用
- - 数据库 - ITeye博客根据以往的测试结论,单个redis的实例的内存总量最好控制在8G以内(最大不能超过20G),而实际上应用对redis的内存的需求可能会远远大于8G,因此需要一个保持redis server性能不下降,但可以有效扩充redis server的容量的方案. twemproxy是一个恰当的选择. twemproxy,也叫nutcraker.
限流的目的是通过对并发访问/请求进行限速或者一个时间窗口内的的请求进行限速来保护系统,一旦达到限制速率则可以拒绝服务。
前几天在DD的公众号,看了一篇关于使用 瓜娃 实现单应用限流的方案,参考《redis in action》 实现了一个jedis版本的,都属于业务层次限制。 实际场景中常用的限流策略:
import redis.clients.jedis.Jedis; import redis.clients.jedis.Transaction; import redis.clients.jedis.ZParams; import java.util.List; import java.util.UUID; /** * @email [email protected] * @data 2017-08 */ public class RedisRateLimiter { private static final String BUCKET = "BUCKET"; private static final String BUCKET_COUNT = "BUCKET_COUNT"; private static final String BUCKET_MONITOR = "BUCKET_MONITOR"; static String acquireTokenFromBucket( Jedis jedis, int limit, long timeout) { String identifier = UUID.randomUUID().toString(); long now = System.currentTimeMillis(); Transaction transaction = jedis.multi(); //删除信号量 transaction.zremrangeByScore(BUCKET_MONITOR.getBytes(), "-inf".getBytes(), String.valueOf(now - timeout).getBytes()); ZParams params = new ZParams(); params.weightsByDouble(1.0,0.0); transaction.zinterstore(BUCKET, params, BUCKET, BUCKET_MONITOR); //计数器自增 transaction.incr(BUCKET_COUNT); List<Object> results = transaction.exec(); long counter = (Long) results.get(results.size() - 1); transaction = jedis.multi(); transaction.zadd(BUCKET_MONITOR, now, identifier); transaction.zadd(BUCKET, counter, identifier); transaction.zrank(BUCKET, identifier); results = transaction.exec(); //获取排名,判断请求是否取得了信号量 long rank = (Long) results.get(results.size() - 1); if (rank < limit) { return identifier; } else {//没有获取到信号量,清理之前放入redis 中垃圾数据 transaction = jedis.multi(); transaction.zrem(BUCKET_MONITOR, identifier); transaction.zrem(BUCKET, identifier); transaction.exec(); } return null; } }
测试接口调用 @GetMapping("/") public void index(HttpServletResponse response) throws IOException { Jedis jedis = jedisPool.getResource(); String token = RedisRateLimiter.acquireTokenFromBucket(jedis, LIMIT, TIMEOUT); if (token == null) { response.sendError(500); }else{ //TODO 你的业务逻辑 } jedisPool.returnResource(jedis); }
使用拦截器 + 注解优化代码
@Configuration static class WebMvcConfigurer extends WebMvcConfigurerAdapter { private Logger logger = LoggerFactory.getLogger(WebMvcConfigurer.class); @Autowired private JedisPool jedisPool; public void addInterceptors(InterceptorRegistry registry) { registry.addInterceptor(new HandlerInterceptorAdapter() { public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception { HandlerMethod handlerMethod = (HandlerMethod) handler; Method method = handlerMethod.getMethod(); RateLimiter rateLimiter = method.getAnnotation(RateLimiter.class); if (rateLimiter != null){ int limit = rateLimiter.limit(); int timeout = rateLimiter.timeout(); Jedis jedis = jedisPool.getResource(); String token = RedisRateLimiter.acquireTokenFromBucket(jedis, limit, timeout); if (token == null) { response.sendError(500); return false; } logger.debug("token -> {}",token); jedis.close(); } return true; } }).addPathPatterns("/*"); } }
/** * @email [email protected] * @data 2017-08 * 限流注解 */ @Target(ElementType.METHOD) @Retention(RetentionPolicy.RUNTIME) @Documented public @interface RateLimiter { int limit() default 5; int timeout() default 1000; }
@RateLimiter(limit = 2, timeout = 5000) @GetMapping("/test") public void test() { }
工具:apache-jmeter-3.2
说明: 没有获取到信号量的接口返回500,status是红色,获取到信号量的接口返回200,status是绿色。
当限制请求信号量为2,并发5个线程:
当限制请求信号量为5,并发10个线程: