基于LinkedHashMap实现LRU缓存调度算法原理及应用

在Android中实用LRU+软引用（弱引用）的方法来缓存图片，可以减少内存溢出的情况。

实现思路：

在把图片保存到LRU集合中的时候，同时保存在一个弱引用的集合之中，如果此元素被LRU算法删除，可能垃圾回收器还并没有回收，可以通过弱引用的集合获取到此引用。

 

public LinkedHashMap (int initialCapacity, float loadFactor, boolean accessOrder)；

 initialCapacity   初始容量

 loadFactor    加载因子，一般是 0.75f

 accessOrder   false 基于插入顺序  true  基于访问顺序（get一个元素后，这个元素被加到最后，使用了LRU  最近最少被使用的调度算法）

 

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。 

 

如 boolean accessOrder = true； 

      Map<String, String> m = new LinkedHashMap<String, String>(20, .80f,  accessOrder  );

      m.put("1", "my"));

      m.put("2", "map"));

      m.put("3", "test"));

      m.get("1");

      m.get("2");

      Log.d("tag",  m);

     若 accessOrder == true;  输出 {3=test, 1=my, 2=map}

         accessOrder == false;  输出 {1=my, 2=map，3=test}

 

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。 

/**
  * 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？ 

   //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, 

 

 

本文出处:http://blog.csdn.net/wo6925371/article/details/7921394