LRU缓存 用缓存来存放之前读取过的数据，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，所以一般把最近常读取的放在缓存里。
LRU(Least Recently Used)缓存利用了这样的一种思想, 把最新读取的数据放在最前面，缓存中存储的是读取最频繁的数据，以能够提高系统的性能。
LinkedHashMap实现LRU LinkedHashMap支持按照访问顺序的存储，也就是说，最近读取的会放在最前面，最不常读取的会放在最后。其次，LinkedHashMap 有一个方法用于判断是否需要移除最不常读取的数，原始方法默认不需要移除，所以，LRU 需要 override 这个方法，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。
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()); } }