LruCache算法原理及实现
LruCache算法原理
LRU为Least Recently Used的缩写，意思也就是近期最少使用算法。LruCache将LinkedHashMap的顺序设置为LRU顺序来实现LRU缓存，每次调用get并获取到值(也就是从内存缓存中命中)，则将该对象移到链表的尾端。调用put插入新的对象也是存储在链表尾端，这样当内存缓存达到设定的最大值时，将链表头部的对象（近期最少用到的）移除。
基于LinkedHashMap的LRUCache的实现，关键是重写LinkedHashMap的removeEldestEntry方法，在LinkedHashMap中该方法默认返回false（LRUCache本身未考虑线程安全的问题），这样此映射的行为将类似于正常映射，即永远不能移除最旧的元素。
LruCache算法实现的思路
- 按从近期访问最少到近期访问最多的顺序（即访问顺序）来保存元素，LinkedHashMap提供了LinkedHashMap(int initialCapacity, float loadFactor, boolean accessOrder)构造函数，该哈希映射的迭代顺序就是最后访问其条目的顺序，这种映射很适合构建LRU缓存。
- LinkedHashMap提供了removeEldestEntry(Map.Entry eldest)方法。该方法在每次添加新条目时移除最旧条目，但该方法默认返回false，这样，此映射的行为将类似于正常映射，即永远不能移除最旧的元素。因而需要重写该方法。
基于LinkedHashMap的LruCache具体实现
import java.util.LinkedHashMap;
import java.util.Map;
public class LruCache<K, V> {
private LinkedHashMap<K, V> map;//链表存储对象
private int cacheSize;//cache大小
private int hitCount;//命中次数
private int missCount;//未命中次数
public synchronized final int getCacheSize() {
return cacheSize;
}
public synchronized final int getHitCount() {
return hitCount;
}
public synchronized final int getMissCount() {
return missCount;
}
static final int DEFAULT_CACHE_SIZE = 2;//cache默认大小
public V put(K key, V value) {
return map.put(key, value);
}
public V get(Object key) {
if (null == key) {
throw new NullPointerException(" key == null ");
}
V val = null;
synchronized (this) {
val = map.get(key);
if (null != val) {
hitCount += 1;
return val;
}
missCount += 1;
}
return val;
}
public LruCache() {
this(DEFAULT_CACHE_SIZE);
}
public LruCache(int cacheSize) {
this.cacheSize = cacheSize;
int hashTableSize = (int) (Math.ceil(cacheSize / 0.75f) + 1);
//LruCache算法实现的关键
//1、按从近期访问最少到近期访问最多的顺序（即访问顺序）来保存元素，那么请使用下面的构造方法构造LinkedHashMap
//public LinkedHashMap(int initialCapacity, float loadFactor, boolean accessOrder); //该哈希映射的迭代顺序就是最后访问其条目的顺序，这种映射很适合构建LRU缓存。
//2、LinkedHashMap提供了removeEldestEntry(Map.Entry<K,V> eldest)方法。该方法可以提供在每次添加新条目时移除最旧条目的实现程序，默认返回false，这样，此映射的行为将类似于正常映射，即永远不能移除最旧的元素。
map = new LinkedHashMap<K, V>(hashTableSize, 0.75f, true){
private static final long serialVersionUID = 1L;
@Override
protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
System.out.println(" ***** size=" + size() + " cacheSize=" + LruCache.this.cacheSize + " ****");
// return super.removeEldestEntry(eldest);
return size() > LruCache.this.cacheSize;
}
};
}
public static void main(String[] args) {
LruCache<String, String> lruCache = new LruCache<String, String>(3);
lruCache.put("1", "1");
lruCache.put("2", "2");
lruCache.put("3", "3");
lruCache.put("4", "4");
lruCache.put("5", "5");
System.out.println("==========================================================================");
System.out.println("hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println("==========================================================================");
System.out.println(lruCache.get("1") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println(lruCache.get("2") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println(lruCache.get("3") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println(lruCache.get("4") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println(lruCache.get("4") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println(lruCache.get("4") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println(lruCache.get("4") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
lruCache.put("6", "6");
lruCache.put("7", "7");
System.out.println(lruCache.get("4") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
lruCache.put("8", "8");
System.out.println(lruCache.get("5") + " hitCount=" + lruCache.getHitCount() + " missCount=" + lruCache.getMissCount());
System.out.println("==========================================================================");
for(Map.Entry<String, String> entry : lruCache.map.entrySet()) {
System.out.println(entry.getKey()+":"+entry.getValue());
}
}
}执行结果
***** size=1 cacheSize=3 ****
***** size=2 cacheSize=3 ****
***** size=3 cacheSize=3 ****
***** size=4 cacheSize=3 ****
***** size=4 cacheSize=3 ****
==========================================================================
hitCount=0 missCount=0
==========================================================================
null hitCount=0 missCount=1
null hitCount=0 missCount=2
3 hitCount=1 missCount=2
4 hitCount=2 missCount=2
4 hitCount=3 missCount=2
4 hitCount=4 missCount=2
4 hitCount=5 missCount=2
***** size=4 cacheSize=3 ****
***** size=4 cacheSize=3 ****
4 hitCount=6 missCount=2
***** size=4 cacheSize=3 ****
null hitCount=6 missCount=3
==========================================================================
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4:4
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