Redis动态热点数据缓存策略设计

Redis动态热点数据缓存策略设计

1. 热点数据识别机制

1.1 计数器方式

@Service
public class HotDataCounter {
   
   
    @Autowired
    private RedisTemplate<String, Object> redisTemplate;

    // 访问计数
    public void incrementCounter(String key) {
   
   
        String countKey = "counter:" + key;
        redisTemplate.opsForValue().increment(countKey, 1);
        // 设置计数器过期时间，比如1小时
        redisTemplate.expire(countKey, 1, TimeUnit.HOURS);
    }

    // 获取访问次数
    public Long getCounter(String key) {
   
   
        String countKey = "counter:" + key;
        return (Long) redisTemplate.opsForValue().get(countKey);
    }
}

1.2 LRU算法实现

public class LRUCache<K, V> extends LinkedHashMap<K, V> {
   
   
    private final int capacity;

    public LRUCache(int capacity) {
   
   
        super(capacity, 0.75f, true);
        this.capacity = capacity;
    }

    @Override
    protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
   
   
        return size() > capacity;
    }
}

2. 动态缓存策略实现

2.1 基础缓存服务

@Service
public class DynamicCacheService {
   
   
    @Autowired
    private RedisTemplate<String, Object> redisTemplate;
    @Autowired
    private HotDataCounter hotDataCounter;
    // 热点阈值