Redis精通系列——LFU算法详述(Least Frequently Used - 最不经常使用)

1.package com.lizba.redis.lru;
import java.util.Comparator;
import java.util.List;
import java.util.concurrent.ConcurrentHashMap;
import java.util.stream.Collectors;
/**
 * <p>
 * Redis中LRU算法的实现demo
 * </p>
 *
 * @Author: Liziba
 * @Date: 2021/9/22 22:36
 */
public class RedisLruDemo {
    /**
     * 缓存容器
     */
    private ConcurrentHashMap<String, RedisHead> cache;
    /**
     * 初始化大小
     */
    private int initialCapacity;
    public RedisLruDemo(int initialCapacity) {
        this.initialCapacity = initialCapacity;
        this.cache = new ConcurrentHashMap<>(initialCapacity);
        ;
    }
    /**
     * 设置key/value 设置的时候更新LRU
     *
     * @param key
     * @param body
     */
    public void set(String key, Object body) {
        // 触发LRU淘汰
        synchronized (RedisLruDemo.class) {
            if (!cache.containsKey(key) && cache.size() >= initialCapacity) {
                this.flushLruKey();
            }
        }
        RedisHead obj = this.getRedisHead().setBody(body).setLru(System.currentTimeMillis());
        cache.put(key, obj);
    }
    /**
     * 获取key，存在则更新LRU
     *
     * @param key
     * @return
     */
    public Object get(String key) {
        RedisHead result = null;
        if (cache.containsKey(key)) {
            result = cache.get(key);
            result.setLru(System.currentTimeMillis());
        }
        return result;
    }
    /**
     * 清除LRU key
     */
    private void flushLruKey() {
        List<String> sortData = cache.keySet()
                .stream()
                .sorted(Comparator.comparing(key -> cache.get(key).getLru()))
                .collect(Collectors.toList());
        String removeKey = sortData.get(0);
        System.out.println( "淘汰 -> " + "lru : " + cache.get(removeKey).getLru() + " body : " + cache.get(removeKey).getBody());
        cache.remove(removeKey);
        if (cache.size() >= initialCapacity) {
            this.flushLruKey();
        }
        return;
    }
    /**
     *  获取所有数据测试用
     *
     * @return
     */
    public List<RedisHead> getAll() {
         return cache.keySet().stream().map(key -> cache.get(key)).collect(Collectors.toList());
    }
    private RedisHead getRedisHead() {
        return new RedisHead();
    }
}

1.package com.lizba.redis.lru;
import java.util.Random;
import java.util.concurrent.TimeUnit;
/**
 * <p>
 *      测试LRU
 * </p>
 *
 * @Author: Liziba
 * @Date: 2021/9/22 22:51
 */
public class TestRedisLruDemo {
    public static void main(String[] args) throws InterruptedException {
        RedisLruDemo demo = new RedisLruDemo(10);
        // 先加入10个key，此时cache达到容量，下次加入会淘汰key
        for (int i = 0; i < 10; i++) {
            demo.set(i + "", i);
        }
        // 随机访问前十个key，这样可以保证下次加入时随机淘汰
        for (int i = 0; i < 20; i++) {
            int nextInt = new Random().nextInt(10);
            TimeUnit.SECONDS.sleep(1);
            demo.get(nextInt + "");
        }
        // 再次添加5个key，此时每次添加都会触发淘汰
        for (int i = 10; i < 15; i++) {
            demo.set(i + "", i);
        }
        System.out.println("-------------------------------------------");
        demo.getAll().forEach( redisHead -> System.out.println("剩余 -> " + "lru : " + redisHead.getLru() + " body : " + redisHead.getBody()));
    }
}