public class LruCache<K, V> { //緩存 map 集合，為什么要用LinkedHashMap //因為沒錯取了緩存值之后，都要進行排序，以確保 //下次移除的是最少使用的值 private final LinkedHashMap<K, V> map; //當前緩存的值 private int size; //最大值 private int maxSize; //添加到緩存中的個數 private int putCount; //創建的個數 private int createCount; //被移除的個數 private int evictionCount; //命中個數 private int hitCount; //丟失個數 private int missCount; //實例化 Lru，需要傳入緩存的最大值 //這個最大值可以是個數，比如對象的個數，也可以是內存的大小 //比如，最大內存只能緩存5兆 public LruCache(int maxSize) {  if (maxSize <= 0) {   throw new IllegalArgumentException("maxSize <= 0");  }  this.maxSize = maxSize;  this.map = new LinkedHashMap<K, V>(0, 0.75f, true); } //重置最大緩存的值 public void resize(int maxSize) {  if (maxSize <= 0) {   throw new IllegalArgumentException("maxSize <= 0");  }  synchronized (this) {   this.maxSize = maxSize;  }  trimToSize(maxSize); } //通過 key 獲取緩存值 public final V get(K key) {  if (key == null) {   throw new NullPointerException("key == null");  }  V mapValue;  synchronized (this) {   mapValue = map.get(key);   if (mapValue != null) {    hitCount++;    return mapValue;   }   missCount++;  }  //如果沒有，用戶可以去創建  V createdValue = create(key);  if (createdValue == null) {   return null;  }  synchronized (this) {   createCount++;   mapValue = map.put(key, createdValue);   if (mapValue != null) {    // There was a conflict so undo that last put    map.put(key, mapValue);   } else {    //緩存的大小改變    size += safeSizeOf(key, createdValue);   }  }  //這里沒有移除，只是改變了位置  if (mapValue != null) {   entryRemoved(false, key, createdValue, mapValue);   return mapValue;  } else {   //判斷緩存是否越界   trimToSize(maxSize);   return createdValue;  } } //添加緩存，跟上面這個方法的 create 之后的代碼一樣的 public final V put(K key, V value) {  if (key == null || value == null) {   throw new NullPointerException("key == null || value == null");  }  V previous;  synchronized (this) {   putCount++;   size += safeSizeOf(key, value);   previous = map.put(key, value);   if (previous != null) {    size -= safeSizeOf(key, previous);   }  }  if (previous != null) {   entryRemoved(false, key, previous, value);  }  trimToSize(maxSize);  return previous; } //檢測緩存是否越界 private void trimToSize(int maxSize) {  while (true) {   K key;   V value;   synchronized (this) {    if (size < 0 || (map.isEmpty() && size != 0)) {     throw new IllegalStateException(getClass().getName()       + ".sizeOf() is reporting inconsistent results!");    }    //如果沒有，則返回    if (size <= maxSize) {     break;    }    //以下代碼表示已經超出了最大范圍    Map.Entry<K, V> toEvict = null;    for (Map.Entry<K, V> entry : map.entrySet()) {     toEvict = entry;    }    if (toEvict == null) {     break;    }    //移除最后一個，也就是最少使用的緩存    key = toEvict.getKey();    value = toEvict.getValue();    map.remove(key);    size -= safeSizeOf(key, value);    evictionCount++;   }   entryRemoved(true, key, value, null);  } } //手動移除，用戶調用 public final V remove(K key) {  if (key == null) {   throw new NullPointerException("key == null");  }  V previous;  synchronized (this) {   previous = map.remove(key);   if (previous != null) {    size -= safeSizeOf(key, previous);   }  }  if (previous != null) {   entryRemoved(false, key, previous, null);  }  return previous; } //這里用戶可以重寫它，實現數據和內存回收操作 protected void entryRemoved(boolean evicted, K key, V oldValue, V newValue) {} protected V create(K key) {  return null; } private int safeSizeOf(K key, V value) {  int result = sizeOf(key, value);  if (result < 0) {   throw new IllegalStateException("Negative size: " + key + "=" + value);  }  return result; }  //這個方法要特別注意，跟我們實例化 LruCache 的 maxSize 要呼應，怎么做到呼應呢，比如 maxSize 的大小為緩存的個數，這里就是 return 1就 ok，如果是內存的大小，如果5M，這個就不能是個數 了，這是應該是每個緩存 value 的 size 大小，如果是 Bitmap，這應該是 bitmap.getByteCount(); protected int sizeOf(K key, V value) {  return 1; } //清空緩存 public final void evictAll() {  trimToSize(-1); // -1 will evict 0-sized elements } public synchronized final int size() {  return size; } public synchronized final int maxSize() {  return maxSize; } public synchronized final int hitCount() {  return hitCount; } public synchronized final int missCount() {  return missCount; } public synchronized final int createCount() {  return createCount; } public synchronized final int putCount() {  return putCount; } public synchronized final int evictionCount() {  return evictionCount; } public synchronized final Map<K, V> snapshot() {  return new LinkedHashMap<K, V>(map); }}

/** * Created by gyzhong on 15/4/5. */public class LruPageAdapter extends PagerAdapter { private List<String> mData ; private LruCache<String,Bitmap> mLruCache ; private int mTotalSize = (int) Runtime.getRuntime().totalMemory(); private ViewPager mViewPager ; public LruPageAdapter(ViewPager viewPager ,List<String> data){  mData = data ;  mViewPager = viewPager ;  /*實例化LruCache*/  mLruCache = new LruCache<String,Bitmap>(mTotalSize/5){   /*當緩存大于我們設定的最大值時，會調用這個方法，我們可以用來做內存釋放操作*/   @Override   protected void entryRemoved(boolean evicted, String key, Bitmap oldValue, Bitmap newValue) {    super.entryRemoved(evicted, key, oldValue, newValue);    if (evicted && oldValue != null){     oldValue.recycle();    }   }   /*創建 bitmap*/   @Override   protected Bitmap create(String key) {    final int resId = mViewPager.getResources().getIdentifier(key,"drawable",      mViewPager.getContext().getPackageName()) ;    return BitmapFactory.decodeResource(mViewPager.getResources(),resId) ;   }   /*獲取每個 value 的大小*/   @Override   protected int sizeOf(String key, Bitmap value) {    return value.getByteCount();   }  } ; } @Override public Object instantiateItem(ViewGroup container, int position) {  View view = LayoutInflater.from(container.getContext()).inflate(R.layout.view_pager_item, null) ;  ImageView imageView = (ImageView) view.findViewById(R.id.id_view_pager_item);  Bitmap bitmap = mLruCache.get(mData.get(position));  imageView.setImageBitmap(bitmap);  container.addView(view);  return view; } @Override public void destroyItem(ViewGroup container, int position, Object object) {  container.removeView((View) object); } @Override public int getCount() {  return mData.size(); } @Override public boolean isViewFromObject(View view, Object object) {  return view == object; }}