欢迎大家来到IT世界,在知识的湖畔探索吧!
前言
Android缓存机制:如果没有缓存,在大量的网络请求从远程获取图片时会造成网络流量的浪费,加载速度较慢,用户体验不好;
今天我们就来聊聊Glide的缓存机制
一、Glide中缓存概念简述
Glide将它分成了两个模块,一个是内存缓存,一个是硬盘缓存;
1、内存缓存
- 内存缓存又分为两级,一级是LruCache缓存,一级是弱引用缓存
- 内存缓存的作用:防止应用重复将图片数据读取到内存当中。
- LruCache缓存:不在使用中的图片使用LruCache来进行缓存。
- 弱引用缓存:把正在使用中的图片使用弱引用来进行缓存,这样的目的保护正在使用的资源不会被LruCache算法回收。
2、硬盘缓存
硬盘缓存的作用:防止应用重复从网络或其他地方重复下载和读取数据;
3、图片请求步骤
开始一个新的图片请求之前检查以下多级的缓存:
- 内存缓存:该图片是否最近被加载过并仍存在于内存中?即LruCache缓存;
- 活动资源:现在是否有另一个 View 正在展示这张图片?也就是弱引用缓存;
- 资源类型:该图片是否之前曾被解码、转换并写入过磁盘缓存?
- 数据来源:构建这个图片的资源是否之前曾被写入过文件缓存?
- 前两步检查图片是否在内存中,如果是则直接返回图片。后两步则检查图片是否在磁盘上,以便快速但异步地返回图片;
- 如果四个步骤都未能找到图片,则Glide会返回到原始资源以取回数据(原始文件,Uri, Url等);
- 图片存的顺序是:弱引用、内存、磁盘;
- 图片取的顺序是:内存、弱引用、磁盘;
4、Glide中Bitmap复用机制
- Bitmap复用机制:将已经不需要使用的数据空间重新拿来使用,减少内存抖动(指在短时间内有大量的对象被创建或者被回收的现象);
- BitmapFactory.Options.inMutable是Glide能够复用Bitmap的基石,是BitmapFactory提供的一个参数,表示该Bitmap是可变的,支持复用的。BitmapFactory.Options中提供了两个属性:inMutable、inBitmap。当进行Bitmap复用时,需要设置inMutable为true,inBitmap设置被复用的已经存在的Bitmap。Bitmap复用池使用LRU算法实现;
二、缓存源码流程
memory cache和disk cache在Glide创建的时候也被创建了,Glide创建的代码在GlideBuilder.build(Context)方法
@NonNull
Glide build(@NonNull Context context) {
if (memoryCache == null) {
memoryCache = new LruResourceCache(memorySizeCalculator.getMemoryCacheSize());
}
if (diskCacheFactory == null) {
diskCacheFactory = new InternalCacheDiskCacheFactory(context);
}
if (engine == null) {
engine =
new Engine(
memoryCache,
diskCacheFactory,
...);
}
return new Glide(
...
memoryCache,
...);
}
欢迎大家来到IT世界,在知识的湖畔探索吧!
1、内存缓存-memoryCache
通过代码可以看到 memoryCache 被放入 Engine 和 Glide 实例中。在Engine中利用memoryCache进行存取操作,Glide 实例中的memoryCache是用来在内存紧张的时候,通知memoryCache释放内存。Glide实现了ComponentCallbacks2接口,在Glide创建完成后,通过applicationContext.registerComponentCallbacks(glide)似的 Glide 实例可以监听内存紧张的信号。
欢迎大家来到IT世界,在知识的湖畔探索吧!// Glide
@Override
public void onTrimMemory(int level) {
trimMemory(level);
}
public void trimMemory(int level) {
// Engine asserts this anyway when removing resources, fail faster and consistently
Util.assertMainThread();
// memory cache needs to be trimmed before bitmap pool to trim re-pooled Bitmaps too. See #687.
memoryCache.trimMemory(level);
bitmapPool.trimMemory(level);
arrayPool.trimMemory(level);
}
memoryCache是一个使用LRU(least recently used)算法实现的内存缓存类LruResourceCache,继承至LruCache类,并实现了MemoryCache接口。LruCache定义了LRU算法实现相关的操作,而MemoryCache定义的是内存缓存相关的操作。
LruCache 的实现是利用了 LinkedHashMap 的这种数据结构的一个特性( accessOrder=true 基于访问顺序 )再加上对 LinkedHashMap 的数据操作上锁实现的缓存策略。
当调用 put()方法时,就会在集合中添加元素,并调用
trimToSize()判断缓存是否已满,如果满了就用 LinkedHashMap 的迭代器删除队尾元素,即近期最少访问的元素。
当调用 get()方法访问缓存对象时,就会调用 LinkedHashMap 的 get()方法获得对应集合元素,同时会更新该元素到队头
2、磁盘缓存
diskCacheFactory是创建DiskCache的Factory,DiskCache接口定义
public interface DiskCache {
interface Factory {
/** 250 MB of cache. */
int DEFAULT_DISK_CACHE_SIZE = 250 * 1024 * 1024;
String DEFAULT_DISK_CACHE_DIR = "image_manager_disk_cache";
@Nullable
DiskCache build();
}
interface Writer {
boolean write(@NonNull File file);
}
@Nullable
File get(Key key);
void put(Key key, Writer writer);
@SuppressWarnings("unused")
void delete(Key key);
void clear();
}
接着再来看下DiskCache.Factory的默认实现:InternalCacheDiskCacheFactory
欢迎大家来到IT世界,在知识的湖畔探索吧!public final class InternalCacheDiskCacheFactory extends DiskLruCacheFactory {
public InternalCacheDiskCacheFactory(Context context) {
this(context, DiskCache.Factory.DEFAULT_DISK_CACHE_DIR,
DiskCache.Factory.DEFAULT_DISK_CACHE_SIZE);
}
public InternalCacheDiskCacheFactory(Context context, long diskCacheSize) {
this(context, DiskCache.Factory.DEFAULT_DISK_CACHE_DIR, diskCacheSize);
}
public InternalCacheDiskCacheFactory(final Context context, final String diskCacheName,
long diskCacheSize) {
super(new CacheDirectoryGetter() {
@Override
public File getCacheDirectory() {
File cacheDirectory = context.getCacheDir();
if (cacheDirectory == null) {
return null;
}
if (diskCacheName != null) {
return new File(cacheDirectory, diskCacheName);
}
return cacheDirectory;
}
}, diskCacheSize);
}
}
由以上代码可以看出:默认会创建一个250M的缓存目录,其路径为/data/data/{package}/cache/image_manager_disk_cache/
继续看其父类DiskLruCacheFactory的代码
public class DiskLruCacheFactory implements DiskCache.Factory {
private final long diskCacheSize;
private final CacheDirectoryGetter cacheDirectoryGetter;
public interface CacheDirectoryGetter {
File getCacheDirectory();
}
...
public DiskLruCacheFactory(CacheDirectoryGetter cacheDirectoryGetter, long diskCacheSize) {
this.diskCacheSize = diskCacheSize;
this.cacheDirectoryGetter = cacheDirectoryGetter;
}
@Override
public DiskCache build() {
File cacheDir = cacheDirectoryGetter.getCacheDirectory();
if (cacheDir == null) {
return null;
}
if (!cacheDir.mkdirs() && (!cacheDir.exists() || !cacheDir.isDirectory())) {
return null;
}
return DiskLruCacheWrapper.create(cacheDir, diskCacheSize);
}
}
DiskLruCacheFactory.build()方法会返回一个DiskLruCacheWrapper类的实例,看下DiskLruCacheWrapper的实现
public class DiskLruCacheWrapper implements DiskCache {
private static final String TAG = "DiskLruCacheWrapper";
private static final int APP_VERSION = 1;
private static final int VALUE_COUNT = 1;
private static DiskLruCacheWrapper wrapper;
private final SafeKeyGenerator safeKeyGenerator;
private final File directory;
private final long maxSize;
private final DiskCacheWriteLocker writeLocker = new DiskCacheWriteLocker();
private DiskLruCache diskLruCache;
@SuppressWarnings("deprecation")
public static DiskCache create(File directory, long maxSize) {
return new DiskLruCacheWrapper(directory, maxSize);
}
@Deprecated
@SuppressWarnings({"WeakerAccess", "DeprecatedIsStillUsed"})
protected DiskLruCacheWrapper(File directory, long maxSize) {
this.directory = directory;
this.maxSize = maxSize;
this.safeKeyGenerator = new SafeKeyGenerator();
}
private synchronized DiskLruCache getDiskCache() throws IOException {
if (diskLruCache == null) {
diskLruCache = DiskLruCache.open(directory, APP_VERSION, VALUE_COUNT, maxSize);
}
return diskLruCache;
}
@Override
public File get(Key key) {
String safeKey = safeKeyGenerator.getSafeKey(key);
File result = null;
try {
final DiskLruCache.Value value = getDiskCache().get(safeKey);
if (value != null) {
result = value.getFile(0);
}
} catch (IOException e) {
...
}
return result;
}
@Override
public void put(Key key, Writer writer) {
String safeKey = safeKeyGenerator.getSafeKey(key);
writeLocker.acquire(safeKey);
try {
try {
DiskLruCache diskCache = getDiskCache();
Value current = diskCache.get(safeKey);
...
DiskLruCache.Editor editor = diskCache.edit(safeKey);
...
try {
File file = editor.getFile(0);
if (writer.write(file)) {
editor.commit();
}
} finally {
editor.abortUnlessCommitted();
}
} catch (IOException e) {
...
}
} finally {
writeLocker.release(safeKey);
}
}
...
}
里面包装了一个DiskLruCache,该类主要是为DiskLruCache提供了一个根据Key生成safeKey的SafeKeyGenerator以及写锁DiskCacheWriteLocker。
回到GlideBuilder.build(Context)中,diskCacheFactory会被传进Engine中,在Engine的构造方法中会被包装成为一个LazyDiskCacheProvider,在被需要的时候调用getDiskCache()方法,这样就会调用factory的build()方法返回一个DiskCache。代码如下:
private static class LazyDiskCacheProvider implements DecodeJob.DiskCacheProvider {
private final DiskCache.Factory factory;
private volatile DiskCache diskCache;
LazyDiskCacheProvider(DiskCache.Factory factory) {
this.factory = factory;
}
...
@Override
public DiskCache getDiskCache() {
if (diskCache == null) {
synchronized (this) {
if (diskCache == null) {
diskCache = factory.build();
}
if (diskCache == null) {
diskCache = new DiskCacheAdapter();
}
}
}
return diskCache;
}
}
LazyDiskCacheProvider会在Engine后面的初始化流程中作为入参传到DecodeJobFactory的构造器。在DecodeJobFactory创建DecodeJob时也会作为入参会传进去,DecodeJob中会以全局变量保存此LazyDiskCacheProvider,在资源加载完毕并展示后,会进行缓存的存储。同时,DecodeJob也会在DecodeHelper初始化时,将此DiskCacheProvider设置进去,供ResourceCacheGenerator、DataCacheGenerator读取缓存,供SourceGenerator写入缓存
3、 ActiveResources
ActiveResources在Engine的构造器中被创建,在ActiveResources的构造器中会启动一个后台优先级级别(THREAD_PRIORITY_BACKGROUND)的线程,在该线程中会调用cleanReferenceQueue()方法一直循环清除ReferenceQueue中的将要被GC的Resource。
final class ActiveResources {
private final boolean isActiveResourceRetentionAllowed;
private final Executor monitorClearedResourcesExecutor;
@VisibleForTesting
final Map<Key, ResourceWeakReference> activeEngineResources = new HashMap<>();
private final ReferenceQueue<EngineResource<?>> resourceReferenceQueue = new ReferenceQueue<>();
private volatile boolean isShutdown;
ActiveResources(boolean isActiveResourceRetentionAllowed) {
this(
isActiveResourceRetentionAllowed,
java.util.concurrent.Executors.newSingleThreadExecutor(
new ThreadFactory() {
@Override
public Thread newThread(@NonNull final Runnable r) {
return new Thread(
new Runnable() {
@Override
public void run() {
Process.setThreadPriority(Process.THREAD_PRIORITY_BACKGROUND);
r.run();
}
},
"glide-active-resources");
}
}));
}
@VisibleForTesting
ActiveResources(
boolean isActiveResourceRetentionAllowed, Executor monitorClearedResourcesExecutor) {
this.isActiveResourceRetentionAllowed = isActiveResourceRetentionAllowed;
this.monitorClearedResourcesExecutor = monitorClearedResourcesExecutor;
monitorClearedResourcesExecutor.execute(
new Runnable() {
@Override
public void run() {
cleanReferenceQueue();
}
});
}
@SuppressWarnings("WeakerAccess")
@Synthetic void cleanReferenceQueue() {
while (!isShutdown) {
try {
ResourceWeakReference ref = (ResourceWeakReference) resourceReferenceQueue.remove();
cleanupActiveReference(ref);
// This section for testing only.
DequeuedResourceCallback current = cb;
if (current != null) {
current.onResourceDequeued();
}
// End for testing only.
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
}
}
}
先来看看ActiveResources的activate方法(保存)、deactivate方法(删除)的方法
synchronized void activate(Key key, EngineResource<?> resource) {
ResourceWeakReference toPut =
new ResourceWeakReference(
key, resource, resourceReferenceQueue, isActiveResourceRetentionAllowed);
ResourceWeakReference removed = activeEngineResources.put(key, toPut);
if (removed != null) {
removed.reset();
}
}
synchronized void deactivate(Key key) {
ResourceWeakReference removed = activeEngineResources.remove(key);
if (removed != null) {
removed.reset();
}
}
activate方法会将参数封装成为一个ResourceWeakReference,然后放入map中,如果对应的key之前有值,那么调用之前值的reset方法进行清除。deactivate方法先在map中移除,然后调用resource的reset方法进行清除。ResourceWeakReference继承WeakReference,内部只是保存了Resource的一些属性。
static final class ResourceWeakReference extends WeakReference<EngineResource<?>> {
@SuppressWarnings("WeakerAccess") @Synthetic final Key key;
@SuppressWarnings("WeakerAccess") @Synthetic final boolean isCacheable;
@Nullable @SuppressWarnings("WeakerAccess") @Synthetic Resource<?> resource;
@Synthetic
@SuppressWarnings("WeakerAccess")
ResourceWeakReference(
@NonNull Key key,
@NonNull EngineResource<?> referent,
@NonNull ReferenceQueue<? super EngineResource<?>> queue,
boolean isActiveResourceRetentionAllowed) {
super(referent, queue);
this.key = Preconditions.checkNotNull(key);
this.resource =
referent.isCacheable() && isActiveResourceRetentionAllowed
? Preconditions.checkNotNull(referent.getResource()) : null;
isCacheable = referent.isCacheable();
}
}
构造方法中调用了super(referent, queue),这样做可以让将要被GC的对象放入到ReferenceQueue中。而ActiveResources.cleanReferenceQueue()方法会一直尝试从queue中获取将要被GC的resource,然后调用cleanupActiveReference方法将resource从activeEngineResources中移除。cleanupActiveReference源码如下:
void cleanupActiveReference(@NonNull ResourceWeakReference ref) {
synchronized (listener) {
synchronized (this) {
// 移除active资源
activeEngineResources.remove(ref.key);
if (!ref.isCacheable || ref.resource == null) {
return;
}
// 构造新的 Resource
EngineResource<?> newResource =
new EngineResource<>(ref.resource, /*isCacheable=*/ true, /*isRecyclable=*/ false);
newResource.setResourceListener(ref.key, listener);
// 回调Engine的onResourceReleased方法
// 这会导致此资源从active变成memory cache状态
listener.onResourceReleased(ref.key, newResource);
}
}
}
Engine实现了EngineResource.ResourceListener,此处的listener就是Engine,最终会回调Engine.onResourceReleased
@Override
public synchronized void onResourceReleased(Key cacheKey, EngineResource<?> resource) {
activeResources.deactivate(cacheKey);
if (resource.isCacheable()) {
cache.put(cacheKey, resource);
} else {
resourceRecycler.recycle(resource);
}
}
如果资源可以被缓存,则缓存到 memory cache,否则对资源进行回收
4、磁盘缓存读取
我们分析下缓存的存取代码。我们看下
public synchronized <R> LoadStatus load(...) {
EngineKey key = keyFactory.buildKey(model, signature, width, height, transformations,
resourceClass, transcodeClass, options);
EngineResource<?> active = loadFromActiveResources(key, isMemoryCacheable);
if (active != null) {
cb.onResourceReady(active, DataSource.MEMORY_CACHE);
return null;
}
EngineResource<?> cached = loadFromCache(key, isMemoryCacheable);
if (cached != null) {
cb.onResourceReady(cached, DataSource.MEMORY_CACHE);
return null;
}
EngineJob<?> current = jobs.get(key, onlyRetrieveFromCache);
if (current != null) {
current.addCallback(cb, callbackExecutor);
return new LoadStatus(cb, current);
}
EngineJob<R> engineJob =
engineJobFactory.build(...);
DecodeJob<R> decodeJob =
decodeJobFactory.build(...);
jobs.put(key, engineJob);
engineJob.addCallback(cb, callbackExecutor);
engineJob.start(decodeJob);
return new LoadStatus(cb, engineJob);
}
缓存需要根据EngineKey去存取,先看下EngineKey的构造方法
EngineKey(
Object model,
Key signature,
int width
int height,
Map<Class<?>, Transformation<?>> transformations,
Class<?> resourceClass,
Class<?> transcodeClass,
Options options)
- model:load方法传的参数;
- signature:BaseRequestOptions的成员变量,默认会是EmptySignature.obtain()
- 在加载本地resource资源时会变成ApplicationVersionSignature.obtain(context);
- width、height:如果没有指定override(int size),那么将得到view的size;
- transformations:默认会基于ImageView的scaleType设置对应的四个Transformation;
- 如果指定了transform,那么就基于该值进行设置;
- resourceClass:解码后的资源,如果没有asBitmap、asGif,一般会是Object;
- transcodeClass:最终要转换成的数据类型,根据as方法确定,加载本地res或者网络URL,都会调用asDrawable,所以为Drawable
- options:如果没有设置过transform,此处会根据ImageView的scaleType默认指定一个option;
- 所以,在多次加载同一个model的过程中,只要上述任何一个参数有改变,都不会认为是同一个key;
回到Engine.load方法,从缓存加载成功后的回调cb.onResourceReady(cached, DataSource.MEMORY_CACHE);可以看到:active状态的资源和memory cache状态的资源都是DataSource.MEMORY_CACHE,并且加载的资源都是 EngineResource 对象,该对象内部采用了引用计数去判断资源是否被释放,如果引用计数为0,那么会调用listener.onResourceReleased(key, this)方法通知外界此资源已经释放了。这里的listener是ResourceListener类型的接口,只有一个onResourceReleased(Key key, EngineResource<?> resource)方法,Engine实现了该接口,此处的listener就是Engine。在Engine.onResourceReleased方法中会判断资源是否可缓存,可缓存则将此资源放入memory cache中,否则回收掉该资源,代码如下:
public synchronized void onResourceReleased(Key cacheKey, EngineResource<?> resource) {
// 从activeResources中移除
activeResources.deactivate(cacheKey);
if (resource.isCacheable()) {
// 存入 MemoryCache
cache.put(cacheKey, resource);
} else {
resourceRecycler.recycle(resource);
}
}
继续回到Engine.load方法,先来看下active资源获取的方法
@Nullable
private EngineResource<?> loadFromActiveResources(Key key, boolean isMemoryCacheable) {
// 设置skipMemoryCache(true),则isMemoryCacheable为false,跳过ActiveResources
if (!isMemoryCacheable) {
return null;
}
EngineResource<?> active = activeResources.get(key);
if (active != null) {
// 命中缓存,引用计数+1
active.acquire();
}
return active;
}
继续分析cached资源获取的方法,如果从active资源中没有获取到缓存,则继续从内存缓存中查找
private EngineResource<?> loadFromCache(Key key, boolean isMemoryCacheable) {
// 设置skipMemoryCache(true),则isMemoryCacheable为false,跳过ActiveResources
if (!isMemoryCacheable) {
return null;
}
EngineResource<?> cached = getEngineResourceFromCache(key);
if (cached != null) {
// 命中缓存,引用计数+1
cached.acquire();
// 将此资源从memoryCache中移到activeResources中
activeResources.activate(key, cached);
}
return cached;
}
如果从memoryCache中获取到资源则将此资源从memoryCache中移到activeResources中。第一次加载的时候activeResources和memoryCache中都没有缓存的,后面继续通过DecodeJob和EngineJob去加载资源。DecoceJob实现了Runnable接口,然后会被EngineJob.start方法提交到对应的线程池中去执行。在DecoceJob的run方法中,会依次从ResourceCacheGenerator和DataCacheGenerator中去取缓存数据,当这两者都取不到的情况下,会交给SourceGenerator加载网络图片或者本地资源。resource资源和data资源都是磁盘缓存中的资源。
先看下 ResourceCacheGenerator.startNext
@Override
public boolean startNext() {
// list里面只有一个GlideUrl对象
List<Key> sourceIds = helper.getCacheKeys();
if (sourceIds.isEmpty()) {
return false;
}
// 获得了三个可以到达的registeredResourceClasses
// GifDrawable、Bitmap、BitmapDrawable
List<Class<?>> resourceClasses = helper.getRegisteredResourceClasses();
if (resourceClasses.isEmpty()) {
if (File.class.equals(helper.getTranscodeClass())) {
return false;
}
throw new IllegalStateException(
"Failed to find any load path from " + helper.getModelClass() + " to "
+ helper.getTranscodeClass());
}
// 遍历sourceIds中的每一个key、resourceClasses中每一个class,以及其他的一些值组成key
// 尝试在磁盘缓存中以key找到缓存文件
while (modelLoaders == null || !hasNextModelLoader()) {
resourceClassIndex++;
if (resourceClassIndex >= resourceClasses.size()) {
sourceIdIndex++;
if (sourceIdIndex >= sourceIds.size()) {
return false;
}
resourceClassIndex = 0;
}
Key sourceId = sourceIds.get(sourceIdIndex);
Class<?> resourceClass = resourceClasses.get(resourceClassIndex);
Transformation<?> transformation = helper.getTransformation(resourceClass);
// PMD.AvoidInstantiatingObjectsInLoops Each iteration is comparatively expensive anyway,
// we only run until the first one succeeds, the loop runs for only a limited
// number of iterations on the order of 10-20 in the worst case.
// 构造key
currentKey =
new ResourceCacheKey(// NOPMD AvoidInstantiatingObjectsInLoops
helper.getArrayPool(),
sourceId,
helper.getSignature(),
helper.getWidth(),
helper.getHeight(),
transformation,
resourceClass,
helper.getOptions());
// 查找缓存文件
cacheFile = helper.getDiskCache().get(currentKey);
// 如果找到了缓存文件,循环条件则会为false,退出循环
if (cacheFile != null) {
sourceKey = sourceId;
// 1\. 找出注入时以File.class为modelClass的注入代码
// 2\. 调用所有注入的factory.build方法得到ModelLoader
// 3 .过滤掉不可能处理model的ModelLoader
// 此时的modelLoaders值为:
// [ByteBufferFileLoader, FileLoader, FileLoader, UnitModelLoader]
modelLoaders = helper.getModelLoaders(cacheFile);
modelLoaderIndex = 0;
}
}
// 如果找到了缓存文件,hasNextModelLoader()方法则会为true,可以执行循环
// 没有找到缓存文件,则不会进入循环,会直接返回false
loadData = null;
boolean started = false;
while (!started && hasNextModelLoader()) {
ModelLoader<File, ?> modelLoader = modelLoaders.get(modelLoaderIndex++);
// 在循环中会依次判断某个ModelLoader能不能加载此文件
loadData = modelLoader.buildLoadData(cacheFile,
helper.getWidth(), helper.getHeight(), helper.getOptions());
if (loadData != null && helper.hasLoadPath(loadData.fetcher.getDataClass())) {
started = true;
// 如果某个ModelLoader可以,那么就调用其fetcher进行加载数据
// 加载成功或失败会通知自身
loadData.fetcher.loadData(helper.getPriority(), this);
}
}
return started;
}
该方法的相关注释代码里都有标明。找缓存时key的类型为ResourceCacheKey,我们先来看下ResourceCacheKey的构成
currentKey =
new ResourceCacheKey(// NOPMD AvoidInstantiatingObjectsInLoops
helper.getArrayPool(),
sourceId,
helper.getSignature(),
helper.getWidth(),
helper.getHeight(),
transformation,
resourceClass,
helper.getOptions());
ResourceCacheKey(
ArrayPool arrayPool,
Key sourceKey,
Key signature,
int width,
int height,
Transformation<?> appliedTransformation,
Class<?> decodedResourceClass,
Options options)
- arrayPool:默认值是LruArrayPool,不参与key的equals方法;
- sourceKey:如果请求的是URL,此处就是GlideUrl(GlideUrl implements Key);
- signature:BaseRequestOptions的成员变量,默认会是EmptySignature.obtain(),
- 在加载本地resource资源时会变成ApplicationVersionSignature.obtain(context);
- width、height:如果没有指定override(int size),那么将得到view的size;
- appliedTransformation:默认会根据ImageView的scaleType设置对应的BitmapTransformation;
- 如果指定了transform,那么就会是指定的值;
- decodedResourceClass:可以被编码成的资源类型,如BitmapDrawable等;
- options:如果没有设置过transform,此处会根据ImageView的scaleType默认指定一个option;
在ResourceCacheKey中,arrayPool并没有参与equals方法;
生成ResourceCacheKey之后会根据key去磁盘缓存中查找cacheFile = helper.getDiskCache().get(currentKey);
helper.getDiskCache()返回DiskCache接口,它的实现类是DiskLruCacheWrapper,看下DiskLruCacheWrapper.get方法
@Override
public File get(Key key) {
String safeKey = safeKeyGenerator.getSafeKey(key);
...
File result = null;
try {
final DiskLruCache.Value value = getDiskCache().get(safeKey);
if (value != null) {
result = value.getFile(0);
}
} catch (IOException e) {
...
}
return result;
}
这里调用SafeKeyGenerator生成了一个String类型的SafeKey,实际上就是对原始key中每个字段都使用SHA-256加密,然后将得到的字节数组转换为16进制的字符串。生成SafeKey后,接着根据SafeKey去DiskCache里面找对应的缓存文件,然后返回文件。
回到ResourceCacheGenerator.startNext方法中,如果找到了缓存会调用loadData.fetcher.loadData(helper.getPriority(), this);这里的 fetcher 是 ByteBufferFetcher,ByteBufferFetcher的loadData方法中最终会执行callback.onDataReady(result)这里callback是ResourceCacheGenerator
public void onDataReady(Object data) {
cb.onDataFetcherReady(sourceKey, data, loadData.fetcher, DataSource.RESOURCE_DISK_CACHE,
currentKey);
}
ResourceCacheGenerator的onDataReady方法又会回调DecodeJob的onDataFetcherReady方法进行后续的解码操作。
如果ResourceCacheGenerator没有找到缓存,就会交给DataCacheGenerator继续查找缓存。该类大体流程和ResourceCacheGenerator一样,有点不同的是,DataCacheGenerator的构造器有两个构造器,其中的DataCacheGenerator(List<key style=”box-sizing: border-box;”>, DecodeHelper<?>, FetcherReadyCallback)构造器是给SourceGenerator准备的。因为如果没有磁盘缓存,那么从源头加载后,肯定需要进行磁盘缓存操作的。所以,SourceGenerator会将加载后的资源保存到磁盘中,然后转交给DataCacheGenerator从磁盘中取出交给ImageView展示。</key>
看下DataCacheGenerator.startNext
public boolean startNext() {
while (modelLoaders == null || !hasNextModelLoader()) {
sourceIdIndex++;
if (sourceIdIndex >= cacheKeys.size()) {
return false;
}
Key sourceId = cacheKeys.get(sourceIdIndex);
...
Key originalKey = new DataCacheKey(sourceId, helper.getSignature());
cacheFile = helper.getDiskCache().get(originalKey);
...
while (!started && hasNextModelLoader()) {
ModelLoader<File, ?> modelLoader = modelLoaders.get(modelLoaderIndex++);
loadData =
modelLoader.buildLoadData(cacheFile, helper.getWidth(), helper.getHeight(),
helper.getOptions());
if (loadData != null && helper.hasLoadPath(loadData.fetcher.getDataClass())) {
started = true;
loadData.fetcher.loadData(helper.getPriority(), this);
}
}
return started;
}
这里的originalKey是DataCacheKey类型的,DataCacheKey构造方法如下
DataCacheKey(Key sourceKey, Key signature)
这里的sourceKey和signature与ResourceCacheKey中的两个变量一致,从这里就可以看出:DataCache缓存的是原始的数据,ResourceCache缓存的是是被解码、转换后的数据。
如果DataCacheGenerator没有取到缓存,那么会交给SourceGenerator从源头加载。看下SourceGenerator的startNext方法
@Override
public boolean startNext() {
// 首次运行dataToCache为null
if (dataToCache != null) {
Object data = dataToCache;
dataToCache = null;
cacheData(data);
}
// 首次运行sourceCacheGenerator为null
if (sourceCacheGenerator != null && sourceCacheGenerator.startNext()) {
return true;
}
sourceCacheGenerator = null;
loadData = null;
boolean started = false;
while (!started && hasNextModelLoader()) {
loadData = helper.getLoadData().get(loadDataListIndex++);
if (loadData != null
&& (helper.getDiskCacheStrategy().isDataCacheable(loadData.fetcher.getDataSource())
|| helper.hasLoadPath(loadData.fetcher.getDataClass()))) {
started = true;
loadData.fetcher.loadData(helper.getPriority(), this);
}
}
return started;
}
加载成功后依然会回调SourceGenerator的onDataReady方法
@Override
public void onDataReady(Object data) {
DiskCacheStrategy diskCacheStrategy = helper.getDiskCacheStrategy();
if (data != null && diskCacheStrategy.isDataCacheable(loadData.fetcher.getDataSource())) {
dataToCache = data;
// cb 为 DecodeJob
cb.reschedule();
} else {
// cb 为 DecodeJob
cb.onDataFetcherReady(loadData.sourceKey, data, loadData.fetcher,
loadData.fetcher.getDataSource(), originalKey);
}
}
先判断获取到的数据是否需要进行磁盘缓存,如果需要磁盘缓存,则经过DecodeJob、EngineJob的调度,重新调用SourceGenerator.startNext方法,此时dataToCache已经被赋值,则会调用cacheData(data);进行磁盘缓存的写入,并转交给DataCacheGenerator完成后续的处理;否则就通知DecodeJob已经加载成功。
先看下SourceGenerator的startNext方法中调用的SourceGenerator.cacheData(data)
private void cacheData(Object dataToCache) {
long startTime = LogTime.getLogTime();
try {
Encoder<Object> encoder = helper.getSourceEncoder(dataToCache);
DataCacheWriter<Object> writer =
new DataCacheWriter<>(encoder, dataToCache, helper.getOptions());
originalKey = new DataCacheKey(loadData.sourceKey, helper.getSignature());
helper.getDiskCache().put(originalKey, writer);
...
} finally {
loadData.fetcher.cleanup();
}
sourceCacheGenerator =
new DataCacheGenerator(Collections.singletonList(loadData.sourceKey), helper, this);
}
cacheData方法先构建了一个DataCacheKey将data写入了磁盘,然后new了一个DataCacheGenerator赋值给sourceCacheGenerator。回到startNext继续向下执行,此时sourceCacheGenerator不为空,就调用其startNext()方法从磁盘中加载刚写入磁盘的数据,并返回true让DecodeJob停止尝试获取数据。此时,从磁盘缓存中读取数据的逻辑已经完成,接下来是写磁盘缓存。
假如SourceGenerator的onDataReady方法中的磁盘缓存策略不可用,则会回调DecodeJob.onDataFetcherReady方法
// DecodeJob
@Override
public void onDataFetcherReady(Key sourceKey, Object data, DataFetcher<?> fetcher,
DataSource dataSource, Key attemptedKey) {
this.currentSourceKey = sourceKey;
this.currentData = data;
this.currentFetcher = fetcher;
this.currentDataSource = dataSource;
this.currentAttemptingKey = attemptedKey;
if (Thread.currentThread() != currentThread) {
runReason = RunReason.DECODE_DATA;
callback.reschedule(this);
} else {
GlideTrace.beginSection("DecodeJob.decodeFromRetrievedData");
try {
decodeFromRetrievedData();
} finally {
GlideTrace.endSection();
}
}
}
private void decodeFromRetrievedData() {
...
Resource<R> resource = null;
try {
resource = decodeFromData(currentFetcher, currentData, currentDataSource);
} catch (GlideException e) {
e.setLoggingDetails(currentAttemptingKey, currentDataSource);
throwables.add(e);
}
if (resource != null) {
notifyEncodeAndRelease(resource, currentDataSource);
} else {
runGenerators();
}
}
decodeFromRetrievedData();后续的方法调用链在之前的文章中分析过,主要做的事情就是:将原始的data数据转变为可以供ImageView显示的resource数据并将其显示在ImageView上。
将原始的data数据转变为resource数据后,会调用DecodeJob.onResourceDecoded(dataSource, decoded)
@Synthetic
@NonNull
<Z> Resource<Z> onResourceDecoded(DataSource dataSource,
@NonNull Resource<Z> decoded) {
@SuppressWarnings("unchecked")
Class<Z> resourceSubClass = (Class<Z>) decoded.get().getClass();
Transformation<Z> appliedTransformation = null;
Resource<Z> transformed = decoded;
// 不是 resource cache时要transform
if (dataSource != DataSource.RESOURCE_DISK_CACHE) {
appliedTransformation = decodeHelper.getTransformation(resourceSubClass);
transformed = appliedTransformation.transform(glideContext, decoded, width, height);
}
// TODO: Make this the responsibility of the Transformation.
if (!decoded.equals(transformed)) {
decoded.recycle();
}
final EncodeStrategy encodeStrategy;
final ResourceEncoder<Z> encoder;
if (decodeHelper.isResourceEncoderAvailable(transformed)) {
encoder = decodeHelper.getResultEncoder(transformed);
encodeStrategy = encoder.getEncodeStrategy(options);
} else {
encoder = null;
encodeStrategy = EncodeStrategy.NONE;
}
Resource<Z> result = transformed;
boolean isFromAlternateCacheKey = !decodeHelper.isSourceKey(currentSourceKey);
if (diskCacheStrategy.isResourceCacheable(isFromAlternateCacheKey, dataSource,
encodeStrategy)) {
if (encoder == null) {
throw new Registry.NoResultEncoderAvailableException(transformed.get().getClass());
}
final Key key;
switch (encodeStrategy) {
case SOURCE:
key = new DataCacheKey(currentSourceKey, signature);
break;
case TRANSFORMED:
key =
new ResourceCacheKey(
decodeHelper.getArrayPool(),
currentSourceKey,
signature,
width,
height,
appliedTransformation,
resourceSubClass,
options);
break;
default:
throw new IllegalArgumentException("Unknown strategy: " + encodeStrategy);
}
LockedResource<Z> lockedResult = LockedResource.obtain(transformed);
deferredEncodeManager.init(key, encoder, lockedResult);
result = lockedResult;
}
return result;
}
然后是此过程中的磁盘缓存过程,影响的因素有encodeStrategy、DiskCacheStrategy.isResourceCacheable。encodeStrategy根据resource数据的类型来判断,如果是Bitmap或BitmapDrawable,那么就是TRANSFORMED;如果是GifDrawable,那么就是SOURCE。磁盘缓存策略默认是DiskCacheStrategy.AUTOMATIC。源码如下:
public static final DiskCacheStrategy AUTOMATIC = new DiskCacheStrategy() {
public boolean isDataCacheable(DataSource dataSource) {
return dataSource == DataSource.REMOTE;
}
public boolean isResourceCacheable(boolean isFromAlternateCacheKey, DataSource dataSource, EncodeStrategy encodeStrategy) {
return (isFromAlternateCacheKey && dataSource == DataSource.DATA_DISK_CACHE || dataSource == DataSource.LOCAL) && encodeStrategy == EncodeStrategy.TRANSFORMED;
}
public boolean decodeCachedResource() {
return true;
}
public boolean decodeCachedData() {
return true;
}
};
- 只有dataSource为DataSource.LOCAL且encodeStrategy为EncodeStrategy.TRANSFORMED时,才允许缓存。也就是只有本地的resource数据为Bitmap或BitmapDrawable的资源才可以缓存。
- 在DecodeJob.onResourceDecoded中会调用deferredEncodeManager.init(key, encoder, lockedResult);去初始化deferredEncodeManager。
在DecodeJob的decodeFromRetrievedData();中拿到resource数据后会调用notifyEncodeAndRelease(resource, currentDataSource)利用deferredEncodeManager对象进行磁盘缓存的写入;
otifyEncodeAndRelease(Resource<R> resource, DataSource dataSource) {
...
// 通知回调,资源已经就绪
notifyComplete(result, dataSource);
stage = Stage.ENCODE;
try {
if (deferredEncodeManager.hasResourceToEncode()) {
deferredEncodeManager.encode(diskCacheProvider, options);
}
} finally {
if (lockedResource != null) {
lockedResource.unlock();
}
}
onEncodeComplete();
}
deferredEncodeManager.encode行磁盘缓存的写入
// DecodeJob
private static class DeferredEncodeManager<Z> {
private Key key;
private ResourceEncoder<Z> encoder;
private LockedResource<Z> toEncode;
@Synthetic
DeferredEncodeManager() { }
// We just need the encoder and resource type to match, which this will enforce.
@SuppressWarnings("unchecked")
<X> void init(Key key, ResourceEncoder<X> encoder, LockedResource<X> toEncode) {
this.key = key;
this.encoder = (ResourceEncoder<Z>) encoder;
this.toEncode = (LockedResource<Z>) toEncode;
}
void encode(DiskCacheProvider diskCacheProvider, Options options) {
GlideTrace.beginSection("DecodeJob.encode");
try {
// 存入磁盘缓存
diskCacheProvider.getDiskCache().put(key,
new DataCacheWriter<>(encoder, toEncode, options));
} finally {
toEncode.unlock();
GlideTrace.endSection();
}
}
boolean hasResourceToEncode() {
return toEncode != null;
}
void clear() {
key = null;
encoder = null;
toEncode = null;
}
}
diskCacheProvider.getDiskCache()获取到DiskLruCacheWrapper,并调用DiskLruCacheWrapper的put写入。DiskLruCacheWrapper在写入的时候会使用到写锁DiskCacheWriteLocker,锁对象由对象池WriteLockPool创建,写锁WriteLock实现是一个不公平锁ReentrantLock。
在缓存写入前,会判断key对应的value存不存在,若存在则不写入。缓存的真正写入会由DataCacheWriter交给ByteBufferEncoder和StreamEncoder两个具体类来写入,前者负责将ByteBuffer写入到文件,后者负责将InputStream写入到文件。
目前为止,磁盘缓存的读写流程都已分析完成;
5、内存缓存:ActiveResource与MemoryCache读取
回到DecodeJob.notifyEncodeAndRelease方法中,经过notifyComplete、EngineJob.onResourceReady、notifyCallbacksOfResult方法中。
在该方法中一方面会将原始的resource包装成一个EngineResource,然后通过回调传给Engine.onEngineJobComplete
@Override
public synchronized void onEngineJobComplete(
EngineJob<?> engineJob, Key key, EngineResource<?> resource) {
// 设置资源的回调为自己,这样在资源释放时会通知自己的回调方法
if (resource != null) {
resource.setResourceListener(key, this);
// 将资源放入activeResources中,资源变为active状态
if (resource.isCacheable()) {
activeResources.activate(key, resource);
}
}
// 将engineJob从Jobs中移除
jobs.removeIfCurrent(key, engineJob);
}
在这里会将资源放入activeResources中,资源变为active状态。后面会使用Executors.mainThreadExecutor()调用SingleRequest.onResourceReady回调进行资源的显示。在触发回调前后各有一个地方会对engineResource进行acquire()和release()操作,这两个操作分别发生在notifyCallbacksOfResult()方法的incrementPendingCallbacks、decrementPendingCallbacks()调用中
@Synthetic
void notifyCallbacksOfResult() {
ResourceCallbacksAndExecutors copy;
Key localKey;
EngineResource<?> localResource;
synchronized (this) {
...
engineResource = engineResourceFactory.build(resource, isCacheable);
...
hasResource = true;
copy = cbs.copy();
incrementPendingCallbacks(copy.size() + 1);
localKey = key;
localResource = engineResource;
}
listener.onEngineJobComplete(this, localKey, localResource);
for (final ResourceCallbackAndExecutor entry : copy) {
entry.executor.execute(new CallResourceReady(entry.cb));
}
decrementPendingCallbacks();
}
synchronized void incrementPendingCallbacks(int count) {
...
if (pendingCallbacks.getAndAdd(count) == 0 && engineResource != null) {
engineResource.acquire();
}
}
synchronized void decrementPendingCallbacks() {
...
int decremented = pendingCallbacks.decrementAndGet();
if (decremented == 0) {
if (engineResource != null) {
engineResource.release();
}
release();
}
}
private class CallResourceReady implements Runnable {
private final ResourceCallback cb;
CallResourceReady(ResourceCallback cb) {
this.cb = cb;
}
@Override
public void run() {
synchronized (EngineJob.this) {
if (cbs.contains(cb)) {
// Acquire for this particular callback.
engineResource.acquire();
callCallbackOnResourceReady(cb);
removeCallback(cb);
}
decrementPendingCallbacks();
}
}
}
CallResourceReady的run方法中也会调用engineResource.acquire(),上面的代码调用结束后,engineResource的引用计数为1。engineResource的引用计数会在RequestManager.onDestory方法中最终调用SingleRequest.clear()方法,SingleRequest.clear()内部调用releaseResource()、Engine.release 进行释放,这样引用计数就变为0。引用计数就变为0后会通知Engine将此资源从active状态变成memory cache状态。如果我们再次加载资源时可以从memory cache中加载,那么资源又会从memory cache状态变成active状态。也就是说,在资源第一次显示后,我们关闭页面,资源会由active变成memory cache;然后我们再次进入页面,加载时会命中memory cache,从而又变成active状态
总结
- 读取内存缓存时,先从LruCache算法机制的内存缓存读取,再从弱引用机制的内存缓存读取;
- 写入内存缓存时,先写入 弱引用机制 的内存缓存,等到图片不再被使用时,再写入到 LruCache算法机制的内存缓存;
- 读取磁盘缓存时,先读取转换后图片的缓存,再读取原始图片的缓存;
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