JDK自带的LinkedHashMap来实现LRU算法

1 代码如下

public class LRULinkedHashMap<K, V> extends LinkedHashMap<K, V> {
    private final int maxCapacity;
 
    private static final float DEFAULT_LOAD_FACTOR = 0.75f;
 
    private final Lock lock = new ReentrantLock();
 
    public LRULinkedHashMap(int maxCapacity) { // true 表示让 LinkedHashMap 按照访问顺序来进行排序，最近访问的放在头部，最老访问的放在尾部        super(maxCapacity, DEFAULT_LOAD_FACTOR, true);
        this.maxCapacity = maxCapacity;
    }
 
    @Override
    protected boolean removeEldestEntry(java.util.Map.Entry<K, V> eldest) {// 当 map 中的数据量大于指定的缓存个数的时候，就自动删除最老的数据。        return size() > maxCapacity;
    }
 
    @Override
    public boolean containsKey(Object key) {
        try {
            lock.lock();
            return super.containsKey(key);
        } finally {
            lock.unlock();
        }
    }
 
 
    @Override
    public V get(Object key) {
        try {
            lock.lock();
            return super.get(key);
        } finally {
            lock.unlock();
        }
    }
 
    @Override
    public V put(K key, V value) {
        try {
            lock.lock();
            return super.put(key, value);
        } finally {
            lock.unlock();
        }
    }
 
    @Override
    public int size() {
        try {
            lock.lock();
            return super.size();
        } finally {
            lock.unlock();
        }
    }
 
    @Override
    public void clear() {
        try {
            lock.lock();
            super.clear();
        } finally {
            lock.unlock();
        }
    }
 
    public Collection<Map.Entry<K, V>> getAll() {
        try {
            lock.lock();
            return new ArrayList<Map.Entry<K, V>>(super.entrySet());
        } finally {
            lock.unlock();
        }
    }
}

2 原理图

A 新数据插入到链表头部； 
B 每当缓存命中（即缓存数据被访问），则将数据移到链表头部； 
C 当链表满的时候，将链表尾部的数据丢弃。 
　　分析 
【命中率】 
当存在热点数据时，LRU的效率很好，但偶发性的、周期性的批量操作会导致LRU命中率急剧下降，缓存污染情况比较严重。 
　　【复杂度】 
　　实现简单。 
　　【代价】 
命中时需要遍历链表，找到命中的数据块索引，然后需要将数据移到头部。
 
 
　

3 源码分析

　　put方法入口调用

　　super的put方法

　　然后调用putVal方法

final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                   boolean evict) {
        Node<K,V>[] tab; Node<K,V> p; int n, i;
        if ((tab = table) == null || (n = tab.length) == 0)
            n = (tab = resize()).length;
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);
        else {
            Node<K,V> e; K k;
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
            else if (p instanceof TreeNode)
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else {
                for (int binCount = 0; ; ++binCount) {
                    if ((e = p.next) == null) {
                        p.next = newNode(hash, key, value, null);
                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                            treeifyBin(tab, hash);
                        break;
                    }
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;
                }
            }
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;
        if (++size > threshold)
            resize();
        afterNodeInsertion(evict);
        return null;
    }