redis热点发现以及保护措施

╰半橙微兮° 2022-01-27 11:51 196阅读 0赞

### 前言 ###

看过很多文章讲述redis热点key的发现以及处理措施

### redis热点发现 ###

1.客户端

在客户端get的时候进行统计

2.美团TMC框架

重写redis源代码进行统计

3.预先知道的热点key

比如我在一个大促的活动中，哪些key是热点的应该知道的吧

### 处理措施 ###

为了避免所有的请求都砸到redis上，一般处理方式：启动二级缓存，比如ehcache

讲下个人思路，当key请求次数达到一定数量时，我们把它放到ehcache缓存中，以后该key的请求从缓存里面读取

@Component
    public class RedisUtil {
    
        ConcurrentHashMap<String, Integer> concurrentHashMap = new ConcurrentHashMap();
    
        private static final String CACHE_NAME = "cache";
    
        @Resource
        private RedisTemplate redisTemplate;
    
        public String getRedis(String key) {
            if (concurrentHashMap.get(key) != null) {
                concurrentHashMap.put(key, concurrentHashMap.get(key) + 1);
                if(concurrentHashMap.get(key)>=1000){
                    return getCache(key);
                }
            } else {
                concurrentHashMap.put(key, 1);
            }
            return (String) redisTemplate.opsForValue().get(key);
        }
    
    
        @Cacheable(value = CACHE_NAME, key = "redis+'_'+#key")
        public String getCache(String key){
            System.out.println("使用Cache");
            return (String) redisTemplate.opsForValue().get(key);
        }
    
    }

代码如上图，当请求超过1000个的时候缓存起来

控制器

@RestController
    public class RedisController {
    
        @Resource
        private RedisTemplate redisTemplate;
    
        @Autowired
        private RedisUtil redisUtil;
    
        @RequestMapping("/redis")
        public void getRedis() throws InterruptedException {
            long time=System.nanoTime();
            String key = "dajitui";
            redisTemplate.opsForValue().set(key, "0");
            CountDownLatch countDownLatch = new CountDownLatch(5000);
            for (int i = 0; i < 30000; i++) {
                new Thread(new Runnable() {
                    @Override
                    public void run() {
                        countDownLatch.countDown();
                        System.out.println(redisUtil.getRedis(key));
                    }
                }).start();
            }
            countDownLatch.await();
            long time1=System.nanoTime();
            System.out.println("耗时"+(time1-time));
        }
    
        @RequestMapping("/redis1")
        public void getRedis1() throws InterruptedException {
            long time=System.nanoTime();
            String key = "dajitui";
            redisTemplate.opsForValue().set(key, "0");
            CountDownLatch countDownLatch = new CountDownLatch(5000);
            for (int i = 0; i < 30000; i++) {
                new Thread(new Runnable() {
                    @Override
                    public void run() {
                        countDownLatch.countDown();
                        System.out.println(redisTemplate.opsForValue().get(key));
                    }
                }).start();
            }
            countDownLatch.await();
            long time1=System.nanoTime();
            System.out.println("耗时"+(time1-time));
        }
    
    
    }

[http://localhost:8080/redis1][http_localhost_8080_redis1]是没有使用二级缓存的，[http://localhost:8080/redis][http_localhost_8080_redis]使用了二级缓存

运行结果发现，没有用缓存的耗时6秒多，使用缓存的耗时2秒多

[源码下载][Link 1]

[http_localhost_8080_redis1]: http://localhost:8080/redis1
[http_localhost_8080_redis]: http://localhost:8080/redis
[Link 1]: https://github.com/dajitui/redisTest