android 图片缓存 异步加载 简要介绍

Caching Bitmaps [缓存位图]

•          加载单个Bitmap到UI是简单直接的，但是如果你需要一次加载大量的图片，事情则会变得复杂起来。在大多数情况下(例如在ListView,GridView or ViewPager), 显示图片的数量通常是没有限制的。
• 通过循环利用子视图可以抑制内存的使用，GC(garbage collector)也会释放那些不再需要使用的bitmap。这些机制都非常好，但是为了保持一个流畅的用户体验，你想要在屏幕滑回来时避免每次重复处理那些图片。内存与磁盘缓存通常可以起到帮助的作用，允许组件快速的重新加载那些处理过的图片。
  
• 这一课会介绍在加载多张位图时使用内存Cache与磁盘Cache来提高反应速度与UI的流畅度

Use a Memory Cache [使用内存缓存]

          异步加载图片的例子，网上也比较多，大部分用了HashMap<String, SoftReference<Drawable>> imageCache ，但是现在已经不再推荐使用这种方式了，因为从 Android 2.3 (API Level 9)开始，垃圾回收器会更倾向于回收持有软引用或弱引用（soft/weak references）的对象，这让软引用和弱引用变得不再可靠。另外，Android 3.0 (API Level 11)中，图片的数据会存储在本地的内存（native memory）当中，因而无法用一种可预见的方式将其释放，这就有潜在的风险造成应用程序的内存溢出并崩溃，所以我这里用得是LruCache来缓存图片，当存储Image的大小大于LruCache设定的值，系统自动释放内存，这个类是3.1版本中提供的，如果你是在更早的Android版本中开发，则需要导入android-support-v4的jar包（这里要注意咯）

• 为了给LruCache选择一个合适的大小，有下面一些因素需要考虑到：
• • 你的程序剩下了多少可用的内存?
  • 多少图片会被一次呈现到屏幕上？有多少图片需要准备好以便马上显示到屏幕？
  • 设备的屏幕大小与密度是多少? 一个具有特别高密度屏幕(xhdpi)的设备，像 Galaxy Nexus 会比 Nexus S (hdpi)需要一个更大的Cache来hold住同样数量的图片.
  • 位图的尺寸与配置是多少，会花费多少内存？
  • 图片被访问的频率如何？是其中一些比另外的访问更加频繁吗？如果是，也许你想要保存那些最常访问的到内存中，或者为不同组别的位图(按访问频率分组)设置多个LruCache 对象。
  • 你可以平衡质量与数量吗? 某些时候保存大量低质量的位图会非常有用，在另外一个后台任务中加载更高质量的图片。
• 没有指定的大小与公式能够适用与所有的程序，那取决于分析你的使用情况后提出一个合适的解决方案。一个太小的Cache会导致额外的花销却没有明显的好处，一个太大的Cache同样会导致java.lang.OutOfMemory的异常[Cache占用太多内存，其他活动则会因为内存不够而异常]，并且使得你的程序只留下小部分的内存用来工作。

  Android提供的LruCache类简介

•  <span style="color:#000000;">package android.util;    import java.util.LinkedHashMap;  import java.util.Map;    /**  * A cache that holds strong references to a limited number of values. Each time  * a value is accessed, it is moved to the head of a queue. When a value is  * added to a full cache, the value at the end of that queue is evicted and may  * become eligible for garbage collection.</span>

• <span style="color:#000000;"> * Cache保存一个强引用来限制内容数量，每当Item被访问的时候，此Item就会移动到队列的头部。 * 当cache已满的时候加入新的item时，在队列尾部的item会被回收。</span>

• <span style="color:#000000;"> * <p>If your cached values hold resources that need to be explicitly released,  * override {@link #entryRemoved}.  * 如果你cache的某个值需要明确释放，重写entryRemoved() * <p>If a cache miss should be computed on demand for the corresponding keys,  * override {@link #create}. This simplifies the calling code, allowing it to  * assume a value will always be returned, even when there's a cache miss.  * 如果key相对应的item丢掉啦，重写create().这简化了调用代码，即使丢失了也总会返回。 * <p>By default, the cache size is measured in the number of entries. Override  * {@link #sizeOf} to size the cache in different units. For example, this cache  * is limited to 4MiB of bitmaps: 默认cache大小是测量的item的数量，重写sizeof计算不同item的 *  大小。 * <pre>   {@code  *   int cacheSize = 4 * 1024 * 1024; // 4MiB  *   LruCache<String, Bitmap> bitmapCache = new LruCache<String, Bitmap>(cacheSize) {  *       protected int sizeOf(String key, Bitmap value) {  *           return value.getByteCount();  *       }  *   }}</pre>  *  * <p>This class is thread-safe. Perform multiple cache operations atomically by  * synchronizing on the cache:</span>

• 线程安全的 有多种缓存操作 被自动用于异步缓存
  

• <span style="color:#000000;"> <pre>   {@code  *   synchronized (cache) {  *     if (cache.get(key) == null) {  *         cache.put(key, value);  *     }  *   }}</pre>  *  * <p>This class does not allow null to be used as a key or value. A return  * value of null from {@link #get}, {@link #put} or {@link #remove} is  * unambiguous: the key was not in the cache. * 不允许key或者value为null *  当get（），put（），remove（）返回值为null时，key相应的项不在cache中 */  public class LruCache<K, V> {      private final LinkedHashMap<K, V> map;        /** Size of this cache in units. Not necessarily the number of elements. */      private int size; //已经存储的大小    private int maxSize; //规定的最大存储空间      private int putCount;  //put的次数    private int createCount;  //create的次数    private int evictionCount;  //回收的次数    private int hitCount;  //命中的次数    private int missCount;  //丢失的次数      /**      * @param maxSize for caches that do not override {@link #sizeOf}, this is      *     the maximum number of entries in the cache. For all other caches,      *     this is the maximum sum of the sizes of the entries in this cache.      */      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);      }        /**      * Returns the value for {@code key} if it exists in the cache or can be      * created by {@code #create}. If a value was returned, it is moved to the      * head of the queue. This returns null if a value is not cached and cannot      * be created. 通过key返回相应的item，或者创建返回相应的item。相应的item会移动到队列的头部，     * 如果item的value没有被cache或者不能被创建，则返回null。     */      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++;  //命中                return mapValue;              }              missCount++;  //丢失        }            /*          * Attempt to create a value. This may take a long time, and the map          * may be different when create() returns. If a conflicting value was          * added to the map while create() was working, we leave that value in          * the map and release the created value.          * 如果丢失了就试图创建一个item         */            V createdValue = create(key);          if (createdValue == null) {              return null;          }            synchronized (this) {              createCount++;//创建++              mapValue = map.put(key, createdValue);                if (mapValue != null) {                  // There was a conflict so undo that last put                  //如果前面存在oldValue，那么撤销put（）                 map.put(key, mapValue);              } else {                  size += safeSizeOf(key, createdValue);              }          }            if (mapValue != null) {              entryRemoved(false, key, createdValue, mapValue);              return mapValue;          } else {              trimToSize(maxSize);              return createdValue;          }      }        /**      * Caches {@code value} for {@code key}. The value is moved to the head of      * the queue.      *      * @return the previous value mapped by {@code key}.      */      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) {  //返回的先前的value值                size -= safeSizeOf(key, previous);              }          }            if (previous != null) {              entryRemoved(false, key, previous, value);          }            trimToSize(maxSize);          return previous;      }        /**      * @param maxSize the maximum size of the cache before returning. May be -1      *     to evict even 0-sized elements.      *  清空cache空间     */      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!");                  }                    if (size <= maxSize) {                      break;                  }                    Map.Entry<K, V> toEvict = map.eldest();                  if (toEvict == null) {                      break;                  }                    key = toEvict.getKey();                  value = toEvict.getValue();                  map.remove(key);                  size -= safeSizeOf(key, value);                  evictionCount++;              }                entryRemoved(true, key, value, null);          }      }        /**      * Removes the entry for {@code key} if it exists.      * 删除key相应的cache项，返回相应的value     * @return the previous value mapped by {@code key}.      */      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;      }        /**      * Called for entries that have been evicted or removed. This method is      * invoked when a value is evicted to make space, removed by a call to      * {@link #remove}, or replaced by a call to {@link #put}. The default      * implementation does nothing.      * 当item被回收或者删掉时调用。改方法当value被回收释放存储空间时被remove调用，     * 或者替换item值时put调用，默认实现什么都没做。     * <p>The method is called without synchronization: other threads may      * access the cache while this method is executing.      *      * @param evicted true if the entry is being removed to make space, false      *     if the removal was caused by a {@link #put} or {@link #remove}.      * true---为释放空间被删除；false---put或remove导致     * @param newValue the new value for {@code key}, if it exists. If non-null,      *     this removal was caused by a {@link #put}. Otherwise it was caused by      *     an eviction or a {@link #remove}.      */      protected void entryRemoved(boolean evicted, K key, V oldValue, V newValue) {}        /**      * Called after a cache miss to compute a value for the corresponding key.      * Returns the computed value or null if no value can be computed. The      * default implementation returns null.      * 当某Item丢失时会调用到，返回计算的相应的value或者null     * <p>The method is called without synchronization: other threads may      * access the cache while this method is executing.      *      * <p>If a value for {@code key} exists in the cache when this method      * returns, the created value will be released with {@link #entryRemoved}      * and discarded. This can occur when multiple threads request the same key      * at the same time (causing multiple values to be created), or when one      * thread calls {@link #put} while another is creating a value for the same      * key.      */      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;      }        /**      * Returns the size of the entry for {@code key} and {@code value} in      * user-defined units.  The default implementation returns 1 so that size      * is the number of entries and max size is the maximum number of entries.      * 返回用户定义的item的大小，默认返回1代表item的数量，最大size就是最大item值     * <p>An entry's size must not change while it is in the cache.      */      protected int sizeOf(K key, V value) {          return 1;      }        /**      * Clear the cache, calling {@link #entryRemoved} on each removed entry.      * 清空cacke     */      public final void evictAll() {          trimToSize(-1); // -1 will evict 0-sized elements      }        /**      * For caches that do not override {@link #sizeOf}, this returns the number      * of entries in the cache. For all other caches, this returns the sum of      * the sizes of the entries in this cache.      */      public synchronized final int size() {          return size;      }        /**      * For caches that do not override {@link #sizeOf}, this returns the maximum      * number of entries in the cache. For all other caches, this returns the      * maximum sum of the sizes of the entries in this cache.      */      public synchronized final int maxSize() {          return maxSize;      }        /**      * Returns the number of times {@link #get} returned a value that was      * already present in the cache.      */      public synchronized final int hitCount() {          return hitCount;      }        /**      * Returns the number of times {@link #get} returned null or required a new      * value to be created.      */      public synchronized final int missCount() {          return missCount;      }        /**      * Returns the number of times {@link #create(Object)} returned a value.      */      public synchronized final int createCount() {          return createCount;      }        /**      * Returns the number of times {@link #put} was called.      */      public synchronized final int putCount() {          return putCount;      }        /**      * Returns the number of values that have been evicted.      * 返回被回收的数量     */      public synchronized final int evictionCount() {          return evictionCount;      }        /**      * Returns a copy of the current contents of the cache, ordered from least      * recently accessed to most recently accessed. 返回当前cache的副本，从最近最少访问到最多访问     */      public synchronized final Map<K, V> snapshot() {          return new LinkedHashMap<K, V>(map);      }        @Override public synchronized final String toString() {          int accesses = hitCount + missCount;          int hitPercent = accesses != 0 ? (100 * hitCount / accesses) : 0;          return String.format("LruCache[maxSize=%d,hits=%d,misses=%d,hitRate=%d%%]",                  maxSize, hitCount, missCount, hitPercent);      }  }  </span>

  
  
  
• 下面是一个为bitmap建立LruCache 的示例：

    private LruCache mMemoryCache;            @Override      protected void onCreate(Bundle savedInstanceState) {          ...          // Get memory class of this device, exceeding this amount will throw an          // OutOfMemory exception.          final int memClass = ((ActivityManager) context.getSystemService(                  Context.ACTIVITY_SERVICE)).getMemoryClass();                // Use 1/8th of the available memory for this memory cache.          final int cacheSize = 1024 * 1024 * memClass / 8;                mMemoryCache = new LruCache(cacheSize) {              @Override              protected int sizeOf(String key, Bitmap bitmap) {                  // The cache size will be measured in bytes rather than number of items.                  return bitmap.getByteCount();              }          };          ...      }            public void addBitmapToMemoryCache(String key, Bitmap bitmap) {          if (getBitmapFromMemCache(key) == null) {              mMemoryCache.put(key, bitmap);          }      }            public Bitmap getBitmapFromMemCache(String key) {          return mMemoryCache.get(key);      }  

• Note:  在上面的例子中, 有1/8的程序内存被作为Cache. 在一个常见的设备上(hdpi)，最小大概有4MB (32/8). 一个全屏的 GridView 组件，如果被800x480像素的图片填满大概会花费1.5MB (800*480*4 bytes), 因此这大概最少可以缓存2.5张图片到内存中.

当加载位图到 ImageView 时，LruCache 会先被检查是否存在这张图片。如果找到有，它会被用来立即更新 ImageView 组件，否则一个后台线程则被触发去处理这张图片

    public void loadBitmap(int resId, ImageView imageView) {          final String imageKey = String.valueOf(resId);                final Bitmap bitmap = getBitmapFromMemCache(imageKey);          if (bitmap != null) {              mImageView.setImageBitmap(bitmap);          } else {  <span style="font-family:'Microsoft YaHei';"><span style="font-family:'Microsoft YaHei';">              //<span style="font-family:'Microsoft YaHei';">默认图片 并开启异步线程</span></span></span>            mImageView.setImageResource(R.drawable.image_placeholder);              BitmapWorkerTask task = new BitmapWorkerTask(mImageView);              task.execute(resId);          }      }  

• ~上面的程序中 BitmapWorkerTask 也需要做添加到内存Cache中的动作：

•     class BitmapWorkerTask extends AsyncTask {          ...          // Decode image in background.          @Override          protected Bitmap doInBackground(Integer... params) {              final Bitmap bitmap = decodeSampledBitmapFromResource(                      getResources(), params[0], 100, 100));              addBitmapToMemoryCache(String.valueOf(params[0]), bitmap);//<span style="font-family:'Microsoft YaHei';">添加到内存<span style="font-family:'Microsoft YaHei';">cache</span></span>              return bitmap;          }          ...      }  

  Use a Disk Cache [使用磁盘缓存]

  •    内存缓存能够提高访问最近查看过的位图，但是你不能保证这个图片会在Cache中。像类似 GridView 等带有大量数据的组件很容易就填满内存Cache。你的程序可能会被类似Phone call等任务而中断，这样后台程序可能会被杀死，那么内存缓存就会被销毁。一旦用户恢复前面的状态，你的程序就又需要为每个图片重新处理。
  • 磁盘缓存磁盘缓存可以用来保存那些已经处理好的位图，并且在那些图片在内存缓存中不可用时减少加载的次数。当然从磁盘读取图片会比从内存要慢，而且读取操作需要在后台线程中处理，因为磁盘读取操作是不可预期的。
    • Note:  如果图片被更频繁的访问到，也许使用 ContentProvider 会更加的合适，比如在Gallery程序中。
  • 在下面的sample code中实现了一个基本的 DiskLruCache 。然而，Android 4.0 的源代码提供了一个更加robust并且推荐使用的DiskLruCache 方案。(libcore/luni/src/main/java/libcore/io/DiskLruCache.java). 因为向后兼容，所以在前面发布的Android版本中也可以直接使用。 (quick search 提供了一个实现这个解决方案的示例)。

  Handle Configuration Changes [处理配置改变]

  • 运行时配置改变，例如屏幕方向的改变会导致Android去destory并restart当前运行的Activity。(关于这一行为的更多信息，请参考 Handling Runtime Changes). 你想要在配置改变时避免重新处理所有的图片，这样才能提供给用户一个良好的平滑过度的体验。
  • 幸运的是，在前面介绍 Use a Memory Cache 的部分，你已经知道如何建立一个内存缓存。这个缓存可以通过使用一个Fragment去调用 setRetainInstance(true) 传递到新的Activity中。在这个activity被recreate之后, 这个保留的 Fragment 会白重新附着上。这样你就可以访问Cache对象，从中获取到图片信息并快速的重新添加到ImageView对象中。
  • 下面配置改变时使用Fragment来重新获取LruCache 的示例：

      private LruCache mMemoryCache;            @Override      protected void onCreate(Bundle savedInstanceState) {          ...          RetainFragment mRetainFragment =                  RetainFragment.findOrCreateRetainFragment(getFragmentManager());          mMemoryCache = RetainFragment.mRetainedCache;          if (mMemoryCache == null) {              mMemoryCache = new LruCache(cacheSize) {                  ... // Initialize cache here as usual              }              mRetainFragment.mRetainedCache = mMemoryCache;          }          ...      }            class RetainFragment extends Fragment {          private static final String TAG = "RetainFragment";          public LruCache mRetainedCache;                public RetainFragment() {}                public static RetainFragment findOrCreateRetainFragment(FragmentManager fm) {              RetainFragment fragment = (RetainFragment) fm.findFragmentByTag(TAG);              if (fragment == null) {                  fragment = new RetainFragment();              }              return fragment;          }                @Override          public void onCreate(Bundle savedInstanceState) {              super.onCreate(savedInstanceState);              setRetainInstance(true);          }      }  

  为了测试上面的效果，尝试对比retaining 这个 Fragment.与没有这样做的时候去旋转屏幕。你会发现从内存缓存中重新绘制几乎没有卡的现象，而从磁盘缓存则显得稍慢，如果两个缓存中都没有，则处理速度像平时一样。