基于LinkedHashMap实现LRU缓存调度算法原理及应用

最近手里事情不太多，随意看了看源码，在学习缓存技术的时候，都少不了使用各种缓存调度算法（FIFO,LRU,LFU），今天总结一下LRU算法。
LinkedHashMap已经为我们自己实现LRU算法提供了便利。
LinkedHashMap继承了HashMap底层是通过Hash表+单向链表实现Hash算法，内部自己维护了一套元素访问顺序的列表。

   /**
     * The head of the doubly linked list.
     */
    private transient Entry<K,V> header;
    .....
   /**
     * LinkedHashMap entry.
     */
    private static class Entry<K,V> extends HashMap.Entry<K,V> {
        // These fields comprise the doubly linked list used for iteration.
        Entry<K,V> before, after;

 HashMap构造函数中回调了子类的init方法实现对元素初始化

    void init() {
        header = new Entry<K,V>(-1, null, null, null);
        header.before = header.after = header;
    }

 

LinkedHashMap中有一个属性可以执行列表元素的排序算法

   /**
     * The iteration ordering method for this linked hash map: <tt>true</tt>
     * for access-order, <tt>false</tt> for insertion-order.
     *
     * @serial
     */
    private final boolean accessOrder;

 

注释已经写的很明白，accessOrder为true使用访问顺序排序，false使用插入顺序排序那么在哪里可以设置这个值。

写道

/**
* Constructs an empty <tt>LinkedHashMap</tt> instance with the
* specified initial capacity, load factor and ordering mode.
*
* @param initialCapacity the initial capacity.
* @param loadFactor the load factor.
* @param accessOrder the ordering mode - <tt>true</tt> for
* access-order, <tt>false</tt> for insertion-order.
* @throws IllegalArgumentException if the initial capacity is negative
* or the load factor is nonpositive.
*/
public LinkedHashMap(int initialCapacity,
float loadFactor,
boolean accessOrder) {
super(initialCapacity, loadFactor);
this.accessOrder = accessOrder;
}

 那么我们就行有访问顺序排序方式实现LRU,那么哪里LinkedHashMap是如何实现LRU的呢？

写道

//LinkedHashMap方法
public V get(Object key) {
Entry<K,V> e = (Entry<K,V>)getEntry(key);
if (e == null)
return null;
e.recordAccess(this);
return e.value;
}
//HashMap方法
public V put(K key, V value) {
if (key == null)
return putForNullKey(value);
int hash = hash(key.hashCode());
int i = indexFor(hash, table.length);
for (Entry<K,V> e = table[i]; e != null; e = e.next) {
Object k;
if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {
V oldValue = e.value;
e.value = value;
e.recordAccess(this);
return oldValue;
}
}

modCount++;
addEntry(hash, key, value, i);
return null;
}

 当调用get或者put方法的时候，如果K-V已经存在，会回调Entry.recordAccess()方法
我们再看一下LinkedHashMap的Entry实现

       /**
         * This method is invoked by the superclass whenever the value
         * of a pre-existing entry is read by Map.get or modified by Map.set.
         * If the enclosing Map is access-ordered, it moves the entry
         * to the end of the list; otherwise, it does nothing. 
         */
        void recordAccess(HashMap<K,V> m) {
            LinkedHashMap<K,V> lm = (LinkedHashMap<K,V>)m;
            if (lm.accessOrder) {
                lm.modCount++;
                remove();
                addBefore(lm.header);
            }
        }

        /**
         * Remove this entry from the linked list.
         */
        private void remove() {
            before.after = after;
            after.before = before;
        }

        /**                                             
         * Insert this entry before the specified existing entry in the list.
         */
        private void addBefore(Entry<K,V> existingEntry) {
            after  = existingEntry;
            before = existingEntry.before;
            before.after = this;
            after.before = this;
        }

 

recordAccess方法会accessOrder为true会先调用remove清楚的当前首尾元素的指向关系，之后调用addBefore方法，将当前元素加入header之前。

当有新元素加入Map的时候会调用Entry的addEntry方法，会调用removeEldestEntry方法，这里就是实现LRU元素过期机制的地方，默认的情况下removeEldestEntry方法只返回false表示元素永远不过期。

   /**
     * This override alters behavior of superclass put method. It causes newly
     * allocated entry to get inserted at the end of the linked list and
     * removes the eldest entry if appropriate.
     */
    void addEntry(int hash, K key, V value, int bucketIndex) {
        createEntry(hash, key, value, bucketIndex);

        // Remove eldest entry if instructed, else grow capacity if appropriate
        Entry<K,V> eldest = header.after;
        if (removeEldestEntry(eldest)) {
            removeEntryForKey(eldest.key);
        } else {
            if (size >= threshold) 
                resize(2 * table.length);
        }
    }

    /**
     * This override differs from addEntry in that it doesn't resize the
     * table or remove the eldest entry.
     */
    void createEntry(int hash, K key, V value, int bucketIndex) {
        HashMap.Entry<K,V> old = table[bucketIndex];
	Entry<K,V> e = new Entry<K,V>(hash, key, value, old);
        table[bucketIndex] = e;
        e.addBefore(header);
        size++;
    }

    protected boolean removeEldestEntry(Map.Entry<K,V> eldest) {
        return false;
    }

 

基本的原理已经介绍完了，那基于LinkedHashMap我们看一下是该如何实现呢？

public static class LRULinkedHashMap<K, V> extends LinkedHashMap<K, V> {

        /** serialVersionUID */
        private static final long serialVersionUID = -5933045562735378538L;

        /** 最大数据存储容量 */
        private static final int  LRU_MAX_CAPACITY     = 1024;

        /** 存储数据容量  */
        private int               capacity;

        /**
         * 默认构造方法
         */
        public LRULinkedHashMap() {
            super();
        }

        /**
         * 带参数构造方法
         * @param initialCapacity   容量
         * @param loadFactor        装载因子
         * @param isLRU             是否使用lru算法，true：使用（按方案顺序排序）;false：不使用（按存储顺序排序）
         */
        public LRULinkedHashMap(int initialCapacity, float loadFactor, boolean isLRU) {
            super(initialCapacity, loadFactor, true);
            capacity = LRU_MAX_CAPACITY;
        }

        /**
         * 带参数构造方法
         * @param initialCapacity   容量
         * @param loadFactor        装载因子
         * @param isLRU             是否使用lru算法，true：使用（按方案顺序排序）;false：不使用（按存储顺序排序）
         * @param lruCapacity       lru存储数据容量       
         */
        public LRULinkedHashMap(int initialCapacity, float loadFactor, boolean isLRU, int lruCapacity) {
            super(initialCapacity, loadFactor, true);
            this.capacity = lruCapacity;
        }

        /** 
         * @see java.util.LinkedHashMap#removeEldestEntry(java.util.Map.Entry)
         */
        @Override
        protected boolean removeEldestEntry(Entry<K, V> eldest) {
            System.out.println(eldest.getKey() + "=" + eldest.getValue());
            
            if(size() > capacity) {
                return true;
            }
            return false;
        }
    }

 

测试代码：

    public static void main(String[] args) {

        LinkedHashMap<String, String> map = new LRULinkedHashMap<String, String>(16, 0.75f, true);
        map.put("a", "a"); //a  a
        map.put("b", "b"); //a  a b
        map.put("c", "c"); //a  a b c
        map.put("a", "a"); //   b c a     
        map.put("d", "d"); //b  b c a d
        map.put("a", "a"); //   b c d a
        map.put("b", "b"); //   c d a b     
        map.put("f", "f"); //c  c d a b f
        map.put("g", "g"); //c  c d a b f g

        map.get("d"); //c a b f g d
        for (Entry<String, String> entry : map.entrySet()) {
            System.out.print(entry.getValue() + ", ");
        }
        System.out.println();

        map.get("a"); //c b f g d a
        for (Entry<String, String> entry : map.entrySet()) {
            System.out.print(entry.getValue() + ", ");
        }
        System.out.println();

        map.get("c"); //b f g d a c
        for (Entry<String, String> entry : map.entrySet()) {
            System.out.print(entry.getValue() + ", ");
        }
        System.out.println();

        map.get("b"); //f g d a c b
        for (Entry<String, String> entry : map.entrySet()) {
            System.out.print(entry.getValue() + ", ");
        }
        System.out.println();

        map.put("h", "h"); //f  f g d a c b h
        for (Entry<String, String> entry : map.entrySet()) {
            System.out.print(entry.getValue() + ", ");
        }
        System.out.println();
    }

 

运行结果：
a=a
a=a
a=a
b=b
c=c
c=c
c, a, b, f, g, d,
c, b, f, g, d, a,
b, f, g, d, a, c,
f, g, d, a, c, b,
f=f
f, g, d, a, c, b, h,