离线下载
PDF版 ePub版

李大辉 · 更新于 2018-11-28 11:00:43

LinkedHashMap 与 LRUcache

LRU 缓存介绍

我们平时总会有一个电话本记录所有朋友的电话,但是,如果有朋友经常联系,那些朋友的电话号码不用翻电话本我们也能记住,但是,如果长时间没有联系了,要再次联系那位朋友的时候,我们又不得不求助电话本,但是,通过电话本查找还是很费时间的。但是,我们大脑能够记住的东西是一定的,我们只能记住自己最熟悉的,而长时间不熟悉的自然就忘记了。

其实,计算机也用到了同样的一个概念,我们用缓存来存放以前读取的数据,而不是直接丢掉,这样,再次读取的时候,可以直接在缓存里面取,而不用再重新查找一遍,这样系统的反应能力会有很大提高。但是,当我们读取的个数特别大的时候,我们不可能把所有已经读取的数据都放在缓存里,毕竟内存大小是一定的,我们一般把最近常读取的放在缓存里(相当于我们把最近联系的朋友的姓名和电话放在大脑里一样)。

LRU 缓存利用了这样的一种思想。LRU 是 Least Recently Used 的缩写,翻译过来就是“最近最少使用”,也就是说,LRU 缓存把最近最少使用的数据移除,让给最新读取的数据。而往往最常读取的,也是读取次数最多的,所以,利用 LRU 缓存,我们能够提高系统的 performance。

实现

要实现 LRU 缓存,我们首先要用到一个类 LinkedHashMap。

用这个类有两大好处:一是它本身已经实现了按照访问顺序的存储,也就是说,最近读取的会放在最前面,最最不常读取的会放在最后(当然,它也可以实现按照插入顺序存储)。第二,LinkedHashMap 本身有一个方法用于判断是否需要移除最不常读取的数,但是,原始方法默认不需要移除(这是,LinkedHashMap 相当于一个linkedlist),所以,我们需要 override 这样一个方法,使得当缓存里存放的数据个数超过规定个数后,就把最不常用的移除掉。关于 LinkedHashMap 中已经有详细的介绍。

代码如下:(可直接复制,也可以通过LRUcache-Java下载)

import java.util.LinkedHashMap;
import java.util.Collection;
import java.util.Map;
import java.util.ArrayList;

/**
 * An LRU cache, based on <code>LinkedHashMap</code>.
 *
 * <p>
 * This cache has a fixed maximum number of elements (<code>cacheSize</code>).
 * If the cache is full and another entry is added, the LRU (least recently
 * used) entry is dropped.
 *
 * <p>
 * This class is thread-safe. All methods of this class are synchronized.
 *
 * <p>
 * Author: Christian d'Heureuse, Inventec Informatik AG, Zurich, Switzerland<br>
 * Multi-licensed: EPL / LGPL / GPL / AL / BSD.
 */
public class LRUCache<K, V> {
    private static final float hashTableLoadFactor = 0.75f;
    private LinkedHashMap<K, V> map;
    private int cacheSize;

    /**
     * Creates a new LRU cache. 在该方法中,new LinkedHashMap<K,V>(hashTableCapacity,
     * hashTableLoadFactor, true)中,true代表使用访问顺序
     *
     * @param cacheSize
     *            the maximum number of entries that will be kept in this cache.
     */
    public LRUCache(int cacheSize) {
        this.cacheSize = cacheSize;
        int hashTableCapacity = (int) Math
                .ceil(cacheSize / hashTableLoadFactor) + 1;
        map = new LinkedHashMap<K, V>(hashTableCapacity, hashTableLoadFactor,
                true) {
            // (an anonymous inner class)
            private static final long serialVersionUID = 1;

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

    /**
     * Retrieves an entry from the cache.<br>
     * The retrieved entry becomes the MRU (most recently used) entry.
     *
     * @param key
     *            the key whose associated value is to be returned.
     * @return the value associated to this key, or null if no value with this
     *         key exists in the cache.
     */
    public synchronized V get(K key) {
        return map.get(key);
    }

    /**
     * Adds an entry to this cache. The new entry becomes the MRU (most recently
     * used) entry. If an entry with the specified key already exists in the
     * cache, it is replaced by the new entry. If the cache is full, the LRU
     * (least recently used) entry is removed from the cache.
     *
     * @param key
     *            the key with which the specified value is to be associated.
     * @param value
     *            a value to be associated with the specified key.
     */
    public synchronized void put(K key, V value) {
        map.put(key, value);
    }

    /**
     * Clears the cache.
     */
    public synchronized void clear() {
        map.clear();
    }

    /**
     * Returns the number of used entries in the cache.
     *
     * @return the number of entries currently in the cache.
     */
    public synchronized int usedEntries() {
        return map.size();
    }

    /**
     * Returns a <code>Collection</code> that contains a copy of all cache
     * entries.
     *
     * @return a <code>Collection</code> with a copy of the cache content.
     */
    public synchronized Collection<Map.Entry<K, V>> getAll() {
        return new ArrayList<Map.Entry<K, V>>(map.entrySet());
    }

    // Test routine for the LRUCache class.
    public static void main(String[] args) {
        LRUCache<String, String> c = new LRUCache<String, String>(3);
        c.put("1", "one"); // 1
        c.put("2", "two"); // 2 1
        c.put("3", "three"); // 3 2 1
        c.put("4", "four"); // 4 3 2
        if (c.get("2") == null)
            throw new Error(); // 2 4 3
        c.put("5", "five"); // 5 2 4
        c.put("4", "second four"); // 4 5 2
        // Verify cache content.
        if (c.usedEntries() != 3)
            throw new Error();
        if (!c.get("4").equals("second four"))
            throw new Error();
        if (!c.get("5").equals("five"))
            throw new Error();
        if (!c.get("2").equals("two"))
            throw new Error();
        // List cache content.
        for (Map.Entry<String, String> e : c.getAll())
            System.out.println(e.getKey() + " : " + e.getValue());
    }
}