Gituhb项目
Volley源码中文注释项目我已经上传到github,欢迎大家fork和start.
为什么写这篇博客
本来文章是维护在github上的,但是我在分析ImageLoader源码过程中与到了一个问题,希望大家能帮助解答.
Volley获取网络图片
本来想分析Universal Image Loader的源码,但是发现Volley已经实现了网络图片的加载功能.其实,网络图片的加载也是分几个步骤:
1. 获取网络图片的url.
2. 判断该url对应的图片是否有本地缓存.
3. 有本地缓存,直接使用本地缓存图片,通过异步回调给ImageView进行设置.
4. 无本地缓存,就先从网络拉取,保存在本地后,再通过异步回调给ImageView进行设置.
我们通过Volley源码,看一下Volley是否是按照这个步骤实现网络图片加载的.
ImageRequest.java
按照Volley的架构,我们首先需要构造一个网络图片请求,Volley帮我们封装了ImageRequest类,我们来看一下它的具体实现:
/** 网络图片请求类. */ @SuppressWarnings("unused") public class ImageRequest extends Request<Bitmap> { /** 默认图片获取的超时时间(单位:毫秒) */ public static final int DEFAULT_IMAGE_REQUEST_MS = 1000; /** 默认图片获取的重试次数. */ public static final int DEFAULT_IMAGE_MAX_RETRIES = 2; private final Response.Listener<Bitmap> mListener; private final Bitmap.Config mDecodeConfig; private final int mMaxWidth; private final int mMaxHeight; private ImageView.ScaleType mScaleType; /** Bitmap解析同步锁,保证同一时间只有一个Bitmap被load到内存进行解析,防止OOM. */ private static final Object sDecodeLock = new Object(); /** * 构造一个网络图片请求. * @param url 图片的url地址. * @param listener 请求成功用户设置的回调接口. * @param maxWidth 图片的最大宽度. * @param maxHeight 图片的最大高度. * @param scaleType 图片缩放类型. * @param decodeConfig 解析bitmap的配置. * @param errorListener 请求失败用户设置的回调接口. */ public ImageRequest(String url, Response.Listener<Bitmap> listener, int maxWidth, int maxHeight, ImageView.ScaleType scaleType, Bitmap.Config decodeConfig, Response.ErrorListener errorListener) { super(Method.GET, url, errorListener); mListener = listener; mDecodeConfig = decodeConfig; mMaxWidth = maxWidth; mMaxHeight = maxHeight; mScaleType = scaleType; } /** 设置网络图片请求的优先级. */ @Override public Priority getPriority() { return Priority.LOW; } @Override protected Response<Bitmap> parseNetworkResponse(NetworkResponse response) { synchronized (sDecodeLock) { try { return doParse(response); } catch (OutOfMemoryError e) { return Response.error(new VolleyError(e)); } } } private Response<Bitmap> doParse(NetworkResponse response) { byte[] data = response.data; BitmapFactory.Options decodeOptions = new BitmapFactory.Options(); Bitmap bitmap; if (mMaxWidth == 0 && mMaxHeight == 0) { decodeOptions.inPreferredConfig = mDecodeConfig; bitmap = BitmapFactory.decodeByteArray(data, 0, data.length, decodeOptions); } else { // 获取网络图片的真实尺寸. decodeOptions.inJustDecodeBounds = true; BitmapFactory.decodeByteArray(data, 0, data.length, decodeOptions); int actualWidth = decodeOptions.outWidth; int actualHeight = decodeOptions.outHeight; int desiredWidth = getResizedDimension(mMaxWidth, mMaxHeight, actualWidth, actualHeight, mScaleType); int desireHeight = getResizedDimension(mMaxWidth, mMaxHeight, actualWidth, actualHeight, mScaleType); decodeOptions.inJustDecodeBounds = false; decodeOptions.inSampleSize = findBestSampleSize(actualWidth, actualHeight, desiredWidth, desireHeight); Bitmap tempBitmap = BitmapFactory.decodeByteArray(data, 0, data.length, decodeOptions); if (tempBitmap != null && (tempBitmap.getWidth() > desiredWidth || tempBitmap.getHeight() > desireHeight)) { bitmap = Bitmap.createScaledBitmap(tempBitmap, desiredWidth, desireHeight, true); tempBitmap.recycle(); } else { bitmap = tempBitmap; } } if (bitmap == null) { return Response.error(new VolleyError(response)); } else { return Response.success(bitmap, HttpHeaderParser.parseCacheHeaders(response)); } } static int findBestSampleSize( int actualWidth, int actualHeight, int desiredWidth, int desireHeight) { double wr = (double) actualWidth / desiredWidth; double hr = (double) actualHeight / desireHeight; double ratio = Math.min(wr, hr); float n = 1.0f; while ((n * 2) <= ratio) { n *= 2; } return (int) n; } /** 根据ImageView的ScaleType设置图片的大小. */ private static int getResizedDimension(int maxPrimary, int maxSecondary, int actualPrimary, int actualSecondary, ImageView.ScaleType scaleType) { // 如果没有设置ImageView的最大值,则直接返回网络图片的真实大小. if ((maxPrimary == 0) && (maxSecondary == 0)) { return actualPrimary; } // 如果ImageView的ScaleType为FIX_XY,则将其设置为图片最值. if (scaleType == ImageView.ScaleType.FIT_XY) { if (maxPrimary == 0) { return actualPrimary; } return maxPrimary; } if (maxPrimary == 0) { double ratio = (double)maxSecondary / (double)actualSecondary; return (int)(actualPrimary * ratio); } if (maxSecondary == 0) { return maxPrimary; } double ratio = (double) actualSecondary / (double) actualPrimary; int resized = maxPrimary; if (scaleType == ImageView.ScaleType.CENTER_CROP) { if ((resized * ratio) < maxSecondary) { resized = (int)(maxSecondary / ratio); } return resized; } if ((resized * ratio) > maxSecondary) { resized = (int)(maxSecondary / ratio); } return resized; } @Override protected void deliverResponse(Bitmap response) { mListener.onResponse(response); } }
因为Volley本身框架已经实现了对网络请求的本地缓存,所以ImageRequest做的主要事情就是解析字节流为Bitmap,再解析过程中,通过静态变量保证每次只解析一个Bitmap防止OOM,使用ScaleType和用户设置的MaxWidth和MaxHeight来设置图片大小.
总体来说,ImageRequest的实现非常简单,这里不做过多的讲解.ImageRequest的缺陷在于:
1.需要用户进行过多的设置,包括图片的大小的最大值.
2.没有图片的内存缓存,因为Volley的缓存是基于Disk的缓存,有对象反序列化的过程.
ImageLoader.java
鉴于以上两个缺点，Volley又提供了一个更牛逼的ImageLoader类.其中,最关键的就是增加了内存缓存.
再讲解ImageLoader的源码之前,需要先介绍一下ImageLoader的使用方法.和之前的Request请求不同,ImageLoader并不是new出来直接扔给RequestQueue进行调度,它的使用方法大体分为4步:
•创建一个RequestQueue对象.
RequestQueue queue = Volley.newRequestQueue(context);
•创建一个ImageLoader对象.
ImageLoader构造函数接收两个参数,第一个是RequestQueue对象,第二个是ImageCache对象(也就是内存缓存类,我们先不给出具体实现,讲解完ImageLoader源码之后,我会提供一个利用LRU算法的ImageCache实现类)
ImageLoader imageLoader = new ImageLoader(queue, new ImageCache() { @Override public void putBitmap(String url, Bitmap bitmap) {} @Override public Bitmap getBitmap(String url) { return null; } });
•获取一个ImageListener对象.
ImageListener listener = ImageLoader.getImageListener(imageView, R.drawable.default_imgage, R.drawable.failed_image);
•调用ImageLoader的get方法加载网络图片.
imageLoader.get(mImageUrl, listener, maxWidth, maxHeight, scaleType);
有了ImageLoader的使用方法,我们结合使用方法来看一下ImageLoader的源码:
@SuppressWarnings({"unused", "StringBufferReplaceableByString"}) public class ImageLoader { /** * 关联用来调用ImageLoader的RequestQueue. */ private final RequestQueue mRequestQueue; /** 图片内存缓存接口实现类. */ private final ImageCache mCache; /** 存储同一时间执行的相同CacheKey的BatchedImageRequest集合. */ private final HashMap<String, BatchedImageRequest> mInFlightRequests = new HashMap<String, BatchedImageRequest>(); private final HashMap<String, BatchedImageRequest> mBatchedResponses = new HashMap<String, BatchedImageRequest>(); /** 获取主线程的Handler. */ private final Handler mHandler = new Handler(Looper.getMainLooper()); private Runnable mRunnable; /** 定义图片K1缓存接口,即将图片的内存缓存工作交给用户来实现. */ public interface ImageCache { Bitmap getBitmap(String url); void putBitmap(String url, Bitmap bitmap); } /** 构造一个ImageLoader. */ public ImageLoader(RequestQueue queue, ImageCache imageCache) { mRequestQueue = queue; mCache = imageCache; } /** 构造网络图片请求成功和失败的回调接口. */ public static ImageListener getImageListener(final ImageView view, final int defaultImageResId, final int errorImageResId) { return new ImageListener() { @Override public void onResponse(ImageContainer response, boolean isImmediate) { if (response.getBitmap() != null) { view.setImageBitmap(response.getBitmap()); } else if (defaultImageResId != 0) { view.setImageResource(defaultImageResId); } } @Override public void onErrorResponse(VolleyError error) { if (errorImageResId != 0) { view.setImageResource(errorImageResId); } } }; } public ImageContainer get(String requestUrl, ImageListener imageListener, int maxWidth, int maxHeight, ScaleType scaleType) { // 判断当前方法是否在UI线程中执行.如果不是,则抛出异常. throwIfNotOnMainThread(); final String cacheKey = getCacheKey(requestUrl, maxWidth, maxHeight, scaleType); // 从L1级缓存中根据key获取对应的Bitmap. Bitmap cacheBitmap = mCache.getBitmap(cacheKey); if (cacheBitmap != null) { // L1缓存命中,通过缓存命中的Bitmap构造ImageContainer,并调用imageListener的响应成功接口. ImageContainer container = new ImageContainer(cacheBitmap, requestUrl, null, null); // 注意:因为目前是在UI线程中,因此这里是调用onResponse方法,并非回调. imageListener.onResponse(container, true); return container; } ImageContainer imageContainer = new ImageContainer(null, requestUrl, cacheKey, imageListener); // L1缓存命中失败,则先需要对ImageView设置默认图片.然后通过子线程拉取网络图片,进行显示. imageListener.onResponse(imageContainer, true); // 检查cacheKey对应的ImageRequest请求是否正在运行. BatchedImageRequest request = mInFlightRequests.get(cacheKey); if (request != null) { // 相同的ImageRequest正在运行,不需要同时运行相同的ImageRequest. // 只需要将其对应的ImageContainer加入到BatchedImageRequest的mContainers集合中. // 当正在执行的ImageRequest结束后,会查看当前有多少正在阻塞的ImageRequest, // 然后对其mContainers集合进行回调. request.addContainer(imageContainer); return imageContainer; } // L1缓存没命中,还是需要构造ImageRequest,通过RequestQueue的调度来获取网络图片 // 获取方法可能是:L2缓存(ps:Disk缓存)或者HTTP网络请求. Request<Bitmap> newRequest = makeImageRequest(requestUrl, maxWidth, maxHeight, scaleType, cacheKey); mRequestQueue.add(newRequest); mInFlightRequests.put(cacheKey, new BatchedImageRequest(newRequest, imageContainer)); return imageContainer; } /** 构造L1缓存的key值. */ private String getCacheKey(String url, int maxWidth, int maxHeight, ScaleType scaleType) { return new StringBuilder(url.length() + 12).append("#W").append(maxWidth) .append("#H").append(maxHeight).append("#S").append(scaleType.ordinal()).append(url) .toString(); } public boolean isCached(String requestUrl, int maxWidth, int maxHeight) { return isCached(requestUrl, maxWidth, maxHeight, ScaleType.CENTER_INSIDE); } private boolean isCached(String requestUrl, int maxWidth, int maxHeight, ScaleType scaleType) { throwIfNotOnMainThread(); String cacheKey = getCacheKey(requestUrl, maxWidth, maxHeight, scaleType); return mCache.getBitmap(cacheKey) != null; } /** 当L1缓存没有命中时,构造ImageRequest,通过ImageRequest和RequestQueue获取图片. */ protected Request<Bitmap> makeImageRequest(final String requestUrl, int maxWidth, int maxHeight, ScaleType scaleType, final String cacheKey) { return new ImageRequest(requestUrl, new Response.Listener<Bitmap>() { @Override public void onResponse(Bitmap response) { onGetImageSuccess(cacheKey, response); } }, maxWidth, maxHeight, scaleType, Bitmap.Config.RGB_565, new Response.ErrorListener() { @Override public void onErrorResponse(VolleyError error) { onGetImageError(cacheKey, error); } }); } /** 图片请求失败回调.运行在UI线程中. */ private void onGetImageError(String cacheKey, VolleyError error) { BatchedImageRequest request = mInFlightRequests.remove(cacheKey); if (request != null) { request.setError(error); batchResponse(cacheKey, request); } } /** 图片请求成功回调.运行在UI线程中. */ protected void onGetImageSuccess(String cacheKey, Bitmap response) { // 增加L1缓存的键值对. mCache.putBitmap(cacheKey, response); // 同一时间内最初的ImageRequest执行成功后,回调这段时间阻塞的相同ImageRequest对应的成功回调接口. BatchedImageRequest request = mInFlightRequests.remove(cacheKey); if (request != null) { request.mResponseBitmap = response; // 将阻塞的ImageRequest进行结果分发. batchResponse(cacheKey, request); } } private void batchResponse(String cacheKey, BatchedImageRequest request) { mBatchedResponses.put(cacheKey, request); if (mRunnable == null) { mRunnable = new Runnable() { @Override public void run() { for (BatchedImageRequest bir : mBatchedResponses.values()) { for (ImageContainer container : bir.mContainers) { if (container.mListener == null) { continue; } if (bir.getError() == null) { container.mBitmap = bir.mResponseBitmap; container.mListener.onResponse(container, false); } else { container.mListener.onErrorResponse(bir.getError()); } } } mBatchedResponses.clear(); mRunnable = null; } }; // Post the runnable mHandler.postDelayed(mRunnable, 100); } } private void throwIfNotOnMainThread() { if (Looper.myLooper() != Looper.getMainLooper()) { throw new IllegalStateException("ImageLoader must be invoked from the main thread."); } } /** 抽象出请求成功和失败的回调接口.默认可以使用Volley提供的ImageListener. */ public interface ImageListener extends Response.ErrorListener { void onResponse(ImageContainer response, boolean isImmediate); } /** 网络图片请求的承载对象. */ public class ImageContainer { /** ImageView需要加载的Bitmap. */ private Bitmap mBitmap; /** L1缓存的key */ private final String mCacheKey; /** ImageRequest请求的url. */ private final String mRequestUrl; /** 图片请求成功或失败的回调接口类. */ private final ImageListener mListener; public ImageContainer(Bitmap bitmap, String requestUrl, String cacheKey, ImageListener listener) { mBitmap = bitmap; mRequestUrl = requestUrl; mCacheKey = cacheKey; mListener = listener; } public void cancelRequest() { if (mListener == null) { return; } BatchedImageRequest request = mInFlightRequests.get(mCacheKey); if (request != null) { boolean canceled = request.removeContainerAndCancelIfNecessary(this); if (canceled) { mInFlightRequests.remove(mCacheKey); } } else { request = mBatchedResponses.get(mCacheKey); if (request != null) { request.removeContainerAndCancelIfNecessary(this); if (request.mContainers.size() == 0) { mBatchedResponses.remove(mCacheKey); } } } } public Bitmap getBitmap() { return mBitmap; } public String getRequestUrl() { return mRequestUrl; } } /** * CacheKey相同的ImageRequest请求抽象类. * 判定两个ImageRequest相同包括: * 1. url相同. * 2. maxWidth和maxHeight相同. * 3. 显示的scaleType相同. * 同一时间可能有多个相同CacheKey的ImageRequest请求,由于需要返回的Bitmap都一样,所以用BatchedImageRequest * 来实现该功能.同一时间相同CacheKey的ImageRequest只能有一个. * 为什么不使用RequestQueue的mWaitingRequestQueue来实现该功能? * 答:是因为仅靠URL是没法判断两个ImageRequest相等的. */ private class BatchedImageRequest { /** 对应的ImageRequest请求. */ private final Request<?> mRequest; /** 请求结果的Bitmap对象. */ private Bitmap mResponseBitmap; /** ImageRequest的错误. */ private VolleyError mError; /** 所有相同ImageRequest请求结果的封装集合. */ private final LinkedList<ImageContainer> mContainers = new LinkedList<ImageContainer>(); public BatchedImageRequest(Request<?> request, ImageContainer container) { mRequest = request; mContainers.add(container); } public VolleyError getError() { return mError; } public void setError(VolleyError error) { mError = error; } public void addContainer(ImageContainer container) { mContainers.add(container); } public boolean removeContainerAndCancelIfNecessary(ImageContainer container) { mContainers.remove(container); if (mContainers.size() == 0) { mRequest.cancel(); return true; } return false; } } }
重大疑问
个人对Imageloader的源码有两个重大疑问?
•batchResponse方法的实现.
我很奇怪,为什么ImageLoader类里面要有一个HashMap来保存BatchedImageRequest集合呢?
private final HashMap<String, BatchedImageRequest> mBatchedResponses = new HashMap<String, BatchedImageRequest>();
毕竟batchResponse是在特定的ImageRequest执行成功的回调中被调用的,调用代码如下:
protected void onGetImageSuccess(String cacheKey, Bitmap response) { // 增加L1缓存的键值对. mCache.putBitmap(cacheKey, response); // 同一时间内最初的ImageRequest执行成功后,回调这段时间阻塞的相同ImageRequest对应的成功回调接口. BatchedImageRequest request = mInFlightRequests.remove(cacheKey); if (request != null) { request.mResponseBitmap = response; // 将阻塞的ImageRequest进行结果分发. batchResponse(cacheKey, request); } }
从上述代码可以看出,ImageRequest请求成功后,已经从mInFlightRequests中获取了对应的BatchedImageRequest对象.而同一时间被阻塞的相同的ImageRequest对应的ImageContainer都在BatchedImageRequest的mContainers集合中.
那我认为,batchResponse方法只需要遍历对应BatchedImageRequest的mContainers集合即可.
但是,ImageLoader源码中,我认为多余的构造了一个HashMap对象mBatchedResponses来保存BatchedImageRequest集合,然后在batchResponse方法中又对集合进行两层for循环各种遍历,实在是非常诡异,求指导.
诡异代码如下:
private void batchResponse(String cacheKey, BatchedImageRequest request) { mBatchedResponses.put(cacheKey, request); if (mRunnable == null) { mRunnable = new Runnable() { @Override public void run() { for (BatchedImageRequest bir : mBatchedResponses.values()) { for (ImageContainer container : bir.mContainers) { if (container.mListener == null) { continue; } if (bir.getError() == null) { container.mBitmap = bir.mResponseBitmap; container.mListener.onResponse(container, false); } else { container.mListener.onErrorResponse(bir.getError()); } } } mBatchedResponses.clear(); mRunnable = null; } }; // Post the runnable mHandler.postDelayed(mRunnable, 100); } }
我认为的代码实现应该是:
private void batchResponse(String cacheKey, BatchedImageRequest request) { if (mRunnable == null) { mRunnable = new Runnable() { @Override public void run() { for (ImageContainer container : request.mContainers) { if (container.mListener == null) { continue; } if (request.getError() == null) { container.mBitmap = request.mResponseBitmap; container.mListener.onResponse(container, false); } else { container.mListener.onErrorResponse(request.getError()); } } mRunnable = null; } }; // Post the runnable mHandler.postDelayed(mRunnable, 100); } }
•使用ImageLoader默认提供的ImageListener,我认为存在一个缺陷,即图片闪现问题.当为ListView的item设置图片时,需要增加TAG判断.因为对应的ImageView可能已经被回收利用了.
自定义L1缓存类
首先说明一下,所谓的L1和L2缓存分别指的是内存缓存和硬盘缓存.
实现L1缓存,我们可以使用Android提供的Lru缓存类,示例代码如下:
import android.graphics.Bitmap; import android.support.v4.util.LruCache; /** Lru算法的L1缓存实现类. */ @SuppressWarnings("unused") public class ImageLruCache implements ImageLoader.ImageCache { private LruCache<String, Bitmap> mLruCache; public ImageLruCache() { this((int) Runtime.getRuntime().maxMemory() / 8); } public ImageLruCache(final int cacheSize) { createLruCache(cacheSize); } private void createLruCache(final int cacheSize) { mLruCache = new LruCache<String, Bitmap>(cacheSize) { @Override protected int sizeOf(String key, Bitmap value) { return value.getRowBytes() * value.getHeight(); } }; } @Override public Bitmap getBitmap(String url) { return mLruCache.get(url); } @Override public void putBitmap(String url, Bitmap bitmap) { mLruCache.put(url, bitmap); } }
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。