Bitmap缓存机制
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Bitmap缓存机制
载入一个bitmap到UI里面比較简单直接。可是,假设我们一次载入大量的bitmap数据的时候就变得复杂了。很多情况下(比方这些组件:ListVIew,GridView或者ViewPager),显示的图片和将要滚动显示的图片通常是没有限制的。
内存的使用量能够被降下来。通过回收那些移出屏幕之外的组件。android的垃圾回收机制相同会释放你的资源,假设它们没有被引用。这样的机制是好的,可是为了获得流畅高速的UI体验,我们想避免反复下载图片。一种本地内存缓存的方法提供了非常大的帮助。能够高速的又一次载入本地缓存的资源。
本章将带你使用内存缓存的机制来提高UI的响应速度和流畅的体验,当载入多张图片的时候。
原文:http://wear.techbrood.com/training/displaying-bitmaps/cache-bitmap.html#config-changes
使用内存缓存
内存缓存使用有限的应用内存去缓存bitmap。LruCache这个类(also available in the Support
Li brary for use back to API Level 4),很适合缓存bitmaps。他使用LinkedHashMap,它会在超过缓存大小的时候回收近期最少使用的指向。
为了为LrcCache选择合适的内存空间,以下几个因素要被大家重视的:Note:过去。我们常使用 SoftReference or WeakReference 来缓存。可是如今不推荐了。从Android2.3(API Level 9),垃圾回收器抵制使用它们。Android3.0(11)之后。bitmap被存储在有效的缓存里面。在可预測的情况下并不能被释放。这样导致超过内存限制而且导致崩溃。
- 你应用的空余内存是多大?
- 一次将要载入多少张图片显示?如今已经显示了多少张图片?
- 屏幕的尺寸大小和密度是多少?高密度的是被比方Galaxy Nexus要比低密度的设备须要更大的缓存。
- bitmap的尺寸和配置是什么。没一张图片所占资源的大小是多少?
- 你须要什么样的用户体验?还是有一部分须要流畅的体验?假设是这种话,你能够把他们长久的放到内存里面或者使用LrcCache缓存。
- 你须要在质量(内存大小)和“质量”(图片的质量)上做出选择?有时候,我们能够选择存储缩略图,后台载入更高质量的图片。
这里有个使用LruCache的样例:
private LruCache<String, Bitmap> mMemoryCache; @Override protected void onCreate(Bundle savedInstanceState) { ... // Get max available VM memory, exceeding this amount will throw an // OutOfMemory exception. Stored in kilobytes as LruCache takes an // int in its constructor. final int maxMemory = (int) (Runtime.getRuntime().maxMemory() / 1024); // Use 1/8th of the available memory for this memory cache. final int cacheSize = maxMemory / 8; mMemoryCache = new LruCache<String, Bitmap>(cacheSize) { @Override protected int sizeOf(String key, Bitmap bitmap) { // The cache size will be measured in kilobytes rather than // number of items. return bitmap.getByteCount() / 1024; } }; ... } 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: In this example, one eighth of the application memory is allocated for our cache. On a normal/hdpi device this is a minimum of around 4MB (32/8). A fullscreen GridView filled with images on a device with 800x480 resolution would use around 1.5MB (800*480*4 bytes), so this would cache a minimum of around 2.5pages of images in memory.
当我们载入一张图片到ImageView,首先检查Lrucache。
假设一旦找到接口。我们能够非常高速的更新这个ImageView,否则,我们启动一个线程去运行载入这张图片。
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 { mImageView.setImageResource(R.drawable.image_placeholder); BitmapWorkerTask task = new BitmapWorkerTask(mImageView); task.execute(resId); } }BitmapWorkerTask须要更新资源和资源的缓存接口:
class BitmapWorkerTask extends AsyncTask<Integer, Void, Bitmap> { ... // 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); return bitmap; } ... }
使用本地缓存
内存缓存是一种非常好的提快速度的方法,可是你不能全然依靠它。像GridView组件非常快的占用掉大量内存。你的应用可能会被其它任务打断。比方来电,而且后台进程可能会被终止,内存缓存也可能会被释放。当你的应用再次启动时候,你不得不又一次载入。
本地缓存能够解决问题,帮助你存储那些缓存不须要的资源来降低反复载入的次数,当然,本地缓存的使用要比内存缓存的速度要慢,须要在后台操作。担任果然读取的事件是不可预知的
Note: A ContentProvider might
be a more appropriate place to store cached images if they are accessed more frequently, for example in an image gallery application.
以下的代码DiskLrcCache。是从本地载入的一个样例:private DiskLruCache mDiskLruCache; private final Object mDiskCacheLock = new Object(); private boolean mDiskCacheStarting = true; private static final int DISK_CACHE_SIZE = 1024 * 1024 * 10; // 10MB private static final String DISK_CACHE_SUBDIR = "thumbnails"; @Override protected void onCreate(Bundle savedInstanceState) { ... // Initialize memory cache ... // Initialize disk cache on background thread File cacheDir = getDiskCacheDir(this, DISK_CACHE_SUBDIR); new InitDiskCacheTask().execute(cacheDir); ... } class InitDiskCacheTask extends AsyncTask<File, Void, Void> { @Override protected Void doInBackground(File... params) { synchronized (mDiskCacheLock) { File cacheDir = params[0]; mDiskLruCache = DiskLruCache.open(cacheDir, DISK_CACHE_SIZE); mDiskCacheStarting = false; // Finished initialization mDiskCacheLock.notifyAll(); // Wake any waiting threads } return null; } } class BitmapWorkerTask extends AsyncTask<Integer, Void, Bitmap> { ... // Decode image in background. @Override protected Bitmap doInBackground(Integer... params) { final String imageKey = String.valueOf(params[0]); // Check disk cache in background thread Bitmap bitmap = getBitmapFromDiskCache(imageKey); if (bitmap == null) { // Not found in disk cache // Process as normal final Bitmap bitmap = decodeSampledBitmapFromResource( getResources(), params[0], 100, 100)); } // Add final bitmap to caches addBitmapToCache(imageKey, bitmap); return bitmap; } ... } public void addBitmapToCache(String key, Bitmap bitmap) { // Add to memory cache as before if (getBitmapFromMemCache(key) == null) { mMemoryCache.put(key, bitmap); } // Also add to disk cache synchronized (mDiskCacheLock) { if (mDiskLruCache != null && mDiskLruCache.get(key) == null) { mDiskLruCache.put(key, bitmap); } } } public Bitmap getBitmapFromDiskCache(String key) { synchronized (mDiskCacheLock) { // Wait while disk cache is started from background thread while (mDiskCacheStarting) { try { mDiskCacheLock.wait(); } catch (InterruptedException e) {} } if (mDiskLruCache != null) { return mDiskLruCache.get(key); } } return null; } // Creates a unique subdirectory of the designated app cache directory. Tries to use external // but if not mounted, falls back on internal storage. public static File getDiskCacheDir(Context context, String uniqueName) {<pre name="code" class="java">private LruCache<String, Bitmap> mMemoryCache; @Override protected void onCreate(Bundle savedInstanceState) { ... RetainFragment retainFragment = RetainFragment.findOrCreateRetainFragment(getFragmentManager()); mMemoryCache = retainFragment.mRetainedCache; if (mMemoryCache == null) { mMemoryCache = new LruCache<String, Bitmap>(cacheSize) { ... // Initialize cache here as usual } retainFragment.mRetainedCache = mMemoryCache; } ... } class RetainFragment extends Fragment { private static final String TAG = "RetainFragment"; public LruCache<String, Bitmap> mRetainedCache; public RetainFragment() {} public static RetainFragment findOrCreateRetainFragment(FragmentManager fm) { RetainFragment fragment = (RetainFragment) fm.findFragmentByTag(TAG); if (fragment == null) { fragment = new RetainFragment(); fm.beginTransaction().add(fragment, TAG).commit(); } return fragment; } @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setRetainInstance(true); } }Note: Even initializing the disk cache requires disk operations and therefore should not take place on the main thread. However, this does mean there‘s a chance the cache is accessed before initialization. To address this, in the above implementation, a lock object ensures that the app does not read from the disk cache until the cache has been initialized.
内存缓存在UI线程里面检測。本地缓存须要在后台使用,本地缓存不能代替内存缓存在UI线程里面的地位,终于,为了以后的使用bitmap同事被放到内存和本地
处理配置的变化
执行时的配置变化。比方屏幕方向的变化会引起Android摧毁和重新启动Activity(For more information about this behavior, see Handling
Runtime Changes),你想避免再次process你的图片,为了更快的体验。
幸运的是,你有一个非常好的内存缓存机制,你能够使用Fragment来忽略这些通过使用
setRetainInstance(true),
当Activity被又一次创建的时候,该保留的Fragment相同会被又一次附着到你的应用上面。以下是一个应对配置改变时的样例:
class RetainFragment extends Fragment { private static final String TAG = "RetainFragment"; public LruCache<String, Bitmap> mRetainedCache; public RetainFragment() {} public static RetainFragment findOrCreateRetainFragment(FragmentManager fm) { RetainFragment fragment = (RetainFragment) fm.findFragmentByTag(TAG); if (fragment == null) { fragment = new RetainFragment(); fm.beginTransaction().add(fragment, TAG).commit(); } return fragment; } @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setRetainInstance(true); } }为了測试它,我们能够旋转屏幕在保留和不保留Fragment的情况下。你应该会注意到。当你保留Fragment的时候。你会注意到图片会毫无滞留的从内存缓存载入。内存中没有找到的会被缓存到本地。假设不这种话,和常规一样。
缓存的图片的优化请看上一篇:多线程处理Bitmaps
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