Glide 快取流程
本文首發於 vivo網際網路技術 微信公眾號
連結： https://mp.weixin.qq.com/s/cPLkefpEb3w12-uoiqzTig
作者：連凌能
Android上圖片載入的解決方案有多種，但是官方認可的是Glide。Glide提供簡潔易用的api，整個框架也方便擴充套件，比如可以替換網路請求庫，同時也提供了完備的快取機制，應用層不需要自己去管理圖片的快取與獲取，框架會分成記憶體快取，檔案快取和遠端快取。本文不會從簡單的使用著手，會把重點放在快取機制的分析上。
一、綜述
開始之前，關於Glide快取請先思考幾個問題：
-
Glide有幾級快取？
-
Glide記憶體快取之間是什麼關係？
-
Glide本地檔案IO和網路請求是一個執行緒嗎？如果不是，怎麼實現執行緒切換？
-
Glide網路請求回來後資料直接返回給使用者還是先存再返回？
載入開始入口從Engine.load()開始，先看下對這個方法的註釋,
-
會先檢查(Active Resources)，如果有就直接返回，Active Resources沒有被引用的資源會放入Memory Cache，如果Active Resources沒有，會往下走。
-
檢查Memory Cache中是否有需要的資源，如果有就返回，Memory Cache中沒有就繼續往下走。
-
檢查當前在執行中的job中是否有改資源的下載，有就在現有的job中直接新增callback返回，不重複下載，當然前提是計算得到的key是一致的，如果還是沒有，就會構造一個新的job開始新的工作。
* Starts a load for the given arguments. * * <p>Must be called on the main thread. * * <p>The flow for any request is as follows: * <ul> * <li>Check the current set of actively used resources, return the active resource if * present, and move any newly inactive resources into the memory cache.</li> * <li>Check the memory cache and provide the cached resource if present.</li> * <li>Check the current set of in progress loads and add the cb to the in progress load if * one is present.</li> * <li>Start a new load.</li>
ok, find the source code.
二、記憶體快取
public <R> LoadStatus load(
GlideContext glideContext,
Object model,
Key signature,
int width,
int height,
Class<?> resourceClass,
Class<R> transcodeClass,
Priority priority,
DiskCacheStrategy diskCacheStrategy,
Map<Class<?>, Transformation<?>> transformations,
boolean isTransformationRequired,
boolean isScaleOnlyOrNoTransform,
Options options,
boolean isMemoryCacheable,
boolean useUnlimitedSourceExecutorPool,
boolean useAnimationPool,
boolean onlyRetrieveFromCache,
ResourceCallback cb) {
Util.assertMainThread();
long startTime = VERBOSE_IS_LOGGABLE ? LogTime.getLogTime() : 0;
EngineKey key = keyFactory.buildKey(model, signature, width, height, transformations,
resourceClass, transcodeClass, options);
// focus 1
EngineResource<?> active = loadFromActiveResources(key, isMemoryCacheable);
if (active != null) {
cb.onResourceReady(active, DataSource.MEMORY_CACHE);
if (VERBOSE_IS_LOGGABLE) {
logWithTimeAndKey("Loaded resource from active resources", startTime, key);
}
return null;
}
// focus 2
EngineResource<?> cached = loadFromCache(key, isMemoryCacheable);
if (cached != null) {
cb.onResourceReady(cached, DataSource.MEMORY_CACHE);
if (VERBOSE_IS_LOGGABLE) {
logWithTimeAndKey("Loaded resource from cache", startTime, key);
}
return null;
}
// focus 3
EngineJob<?> current = jobs.get(key, onlyRetrieveFromCache);
if (current != null) {
current.addCallback(cb);
if (VERBOSE_IS_LOGGABLE) {
logWithTimeAndKey("Added to existing load", startTime, key);
}
return new LoadStatus(cb, current);
}
EngineJob<R> engineJob =
engineJobFactory.build(
key,
isMemoryCacheable,
useUnlimitedSourceExecutorPool,
useAnimationPool,
onlyRetrieveFromCache);
DecodeJob<R> decodeJob =
decodeJobFactory.build(
glideContext,
model,
key,
signature,
width,
height,
resourceClass,
transcodeClass,
priority,
diskCacheStrategy,
transformations,
isTransformationRequired,
isScaleOnlyOrNoTransform,
onlyRetrieveFromCache,
options,
engineJob);
jobs.put(key, engineJob);
engineJob.addCallback(cb);
// focus 4
engineJob.start(decodeJob);
if (VERBOSE_IS_LOGGABLE) {
logWithTimeAndKey("Started new load", startTime, key);
}
return new LoadStatus(cb, engineJob);
}
先看到 focus 1,這一步會從 ActiveResources 中載入資源，首先判斷是否使用記憶體快取，否的話返回null；否則到 ActiveResources 中取資料：
// Engine.java
@Nullable
private EngineResource<?> loadFromActiveResources(Key key, boolean isMemoryCacheable) {
if (!isMemoryCacheable) {
return null;
}
EngineResource<?> active = activeResources.get(key);
if (active != null) {
active.acquire();
}
return active;
}
接下來看下ActiveResources, 其實是用過弱引用儲存使用過的資源。
final class ActiveResources {
...
private final Handler mainHandler = new Handler(Looper.getMainLooper(), new Callback() {
@Override
public boolean handleMessage(Message msg) {
if (msg.what == MSG_CLEAN_REF) {
cleanupActiveReference((ResourceWeakReference) msg.obj);
return true;
}
return false;
}
});
@VisibleForTesting
final Map<Key, ResourceWeakReference> activeEngineResources = new HashMap<>();
...
}
成功取到資料後回撥型別也是記憶體快取：
EngineResource<?> cached = loadFromCache(key, isMemoryCacheable);
if (cached != null) {
cb.onResourceReady(cached, DataSource.MEMORY_CACHE);
return null;
}
接著回到Engine.load()中繼續看到focus 2,如果在cache中找到就是remove掉，然後返回EngineResource，其中需要EngineResource進行acquire一下，這個後面再看，然後會把資源移到ActiveResources中，也就是上面提到的快取：
// Engine.java
private final MemoryCache cache;
private EngineResource<?> loadFromCache(Key key, boolean isMemoryCacheable) {
if (!isMemoryCacheable) {
return null;
}
EngineResource<?> cached = getEngineResourceFromCache(key);
if (cached != null) {
cached.acquire();
activeResources.activate(key, cached);
}
return cached;
}
private EngineResource<?> getEngineResourceFromCache(Key key) {
Resource<?> cached = cache.remove(key);
final EngineResource<?> result;
if (cached == null) {
result = null;
} else if (cached instanceof EngineResource) {
// Save an object allocation if we've cached an EngineResource (the typical case).
result = (EngineResource<?>) cached;
} else {
result = new EngineResource<>(cached, true /*isMemoryCacheable*/, true /*isRecyclable*/);
}
return result;
}
其中cache是MemoryCache介面的實現，如果沒設定，預設在build的時候是LruResourceCache, 也就是熟悉的LRU Cache:
// GlideBuilder.java
if (memoryCache == null) {
memoryCache = new LruResourceCache(memorySizeCalculator.getMemoryCacheSize());
}
再看下EngineResource，主要是對資源增加了引用計數的功能：
// EngineResource.java
private final boolean isCacheable;
private final boolean isRecyclable;
private ResourceListener listener;
private Key key;
private int acquired;
private boolean isRecycled;
private final Resource<Z> resource;
interface ResourceListener {
void onResourceReleased(Key key, EngineResource<?> resource);
}
EngineResource(Resource<Z> toWrap, boolean isCacheable, boolean isRecyclable) {
resource = Preconditions.checkNotNull(toWrap);
this.isCacheable = isCacheable;
this.isRecyclable = isRecyclable;
}
void setResourceListener(Key key, ResourceListener listener) {
this.key = key;
this.listener = listener;
}
Resource<Z> getResource() {
return resource;
}
boolean isCacheable() {
return isCacheable;
}
@NonNull
@Override
public Class<Z> getResourceClass() {
return resource.getResourceClass();
}
@NonNull
@Override
public Z get() {
return resource.get();
}
@Override
public int getSize() {
return resource.getSize();
}
@Override
public void recycle() {
if (acquired > 0) {
throw new IllegalStateException("Cannot recycle a resource while it is still acquired");
}
if (isRecycled) {
throw new IllegalStateException("Cannot recycle a resource that has already been recycled");
}
isRecycled = true;
if (isRecyclable) {
resource.recycle();
}
}
void acquire() {
if (isRecycled) {
throw new IllegalStateException("Cannot acquire a recycled resource");
}
if (!Looper.getMainLooper().equals(Looper.myLooper())) {
throw new IllegalThreadStateException("Must call acquire on the main thread");
}
++acquired;
}
void release() {
if (acquired <= 0) {
throw new IllegalStateException("Cannot release a recycled or not yet acquired resource");
}
if (!Looper.getMainLooper().equals(Looper.myLooper())) {
throw new IllegalThreadStateException("Must call release on the main thread");
}
if (--acquired == 0) {
listener.onResourceReleased(key, this);
}
}
在release後會判斷引用計數是否為0，如果是0就會回撥onResourceReleased,在這裡就是Engine,然後會把資源從ActiveResources中移除，資源預設是可快取的，因此會把資源放到LruCache中。
// Engine.java
@Override
public void onResourceReleased(Key cacheKey, EngineResource<?> resource) {
Util.assertMainThread();
activeResources.deactivate(cacheKey);
if (resource.isCacheable()) {
cache.put(cacheKey, resource);
} else {
resourceRecycler.recycle(resource);
}
}
// ActiveResources.java
void activate(Key key, EngineResource<?> resource) {
ResourceWeakReference toPut =
new ResourceWeakReference(
key,
resource,
getReferenceQueue(),
isActiveResourceRetentionAllowed);
ResourceWeakReference removed = activeEngineResources.put(key, toPut);
if (removed != null) {
removed.reset();
}
}
void deactivate(Key key) {
ResourceWeakReference removed = activeEngineResources.remove(key);
if (removed != null) {
removed.reset();
}
}
如果是回收呢，看看上面的EngineResource，如果引用計數為0並且還沒與回收，就會呼叫真正的Resource.recycle(),看其中的一個BitmapResource是怎麼回收的,就是放到Bitmap池中，也是用的LRU Cache，這個和今天的主題不相關，就不繼續往下擴充。
// BitmapResource.java
@Override
public void recycle() {
bitmapPool.put(bitmap);
}
思路再拉到Engine.load()的流程中，接下來該看focus 3,這裡再貼一下程式碼,如果job已經在執行了，那麼直接新增一個回撥後返回LoadStatus,這個可以允許使用者取消任務：
// Engine.java
EngineJob<?> current = jobs.get(key, onlyRetrieveFromCache);
if (current != null) {
current.addCallback(cb);
if (VERBOSE_IS_LOGGABLE) {
logWithTimeAndKey("Added to existing load", startTime, key);
}
return new LoadStatus(cb, current);
}
// LoadStatus
public static class LoadStatus {
private final EngineJob<?> engineJob;
private final ResourceCallback cb;
LoadStatus(ResourceCallback cb, EngineJob<?> engineJob) {
this.cb = cb;
this.engineJob = engineJob;
}
public void cancel() {
engineJob.removeCallback(cb);
}
}
接著往下看到focus 4, 到這裡就需要建立後臺任務去拉取磁碟檔案或者發起網路請求。
三、磁碟快取
// Engine.java EngineJob<R> engineJob = engineJobFactory.build( key, isMemoryCacheable, useUnlimitedSourceExecutorPool, useAnimationPool, onlyRetrieveFromCache); DecodeJob<R> decodeJob = decodeJobFactory.build( glideContext, model, key, signature, width, height, resourceClass, transcodeClass, priority, diskCacheStrategy, transformations, isTransformationRequired, isScaleOnlyOrNoTransform, onlyRetrieveFromCache, options, engineJob); jobs.put(key, engineJob); engineJob.addCallback(cb); engineJob.start(decodeJob); return new LoadStatus(cb, engineJob);
先構造兩個job，一個是EngineJob,另外一個DecodeJob,其中DecodeJob會根據需要解碼的資源來源分成下面幾個階段:
// DecodeJob.java
/**
* Where we're trying to decode data from.
*/
private enum Stage {
/** The initial stage. */
INITIALIZE,
/** Decode from a cached resource. */
RESOURCE_CACHE,
/** Decode from cached source data. */
DATA_CACHE,
/** Decode from retrieved source. */
SOURCE,
/** Encoding transformed resources after a successful load. */
ENCODE,
/** No more viable stages. */
FINISHED,
}
在構造DecodeJob時會把狀態置為INITIALIZE。
構造完兩個 Job 後會呼叫 EngineJob.start(DecodeJob)，首先會呼叫getNextStage來確定下一個階段，這裡面跟DiskCacheStrategy這個傳入的磁碟快取策略有關。
磁碟策略有下面幾種：
-
**ALL: **快取原始資料和轉換後的資料
-
**NONE: **不快取
-
**DATA: **原始資料，未經過解碼或者轉換
-
**RESOURCE: **快取經過解碼的資料
-
**AUTOMATIC(預設)：**根據`EncodeStrategy`和`DataSource`等條件自動選擇合適的快取方
預設的AUTOMATIC方式是允許解碼快取的RESOURCE：
public static final DiskCacheStrategy AUTOMATIC = new DiskCacheStrategy() {
@Override
public boolean isDataCacheable(DataSource dataSource) {
return dataSource == DataSource.REMOTE;
}
@Override
public boolean isResourceCacheable(boolean isFromAlternateCacheKey, DataSource dataSource,
EncodeStrategy encodeStrategy) {
return ((isFromAlternateCacheKey && dataSource == DataSource.DATA_DISK_CACHE)
|| dataSource == DataSource.LOCAL)
&& encodeStrategy == EncodeStrategy.TRANSFORMED;
}
@Override
public boolean decodeCachedResource() {
return true;
}
@Override
public boolean decodeCachedData() {
return true;
}
};
所以在 getNextStage 會先返回Stage.RESOURCE_CACHE,然後在start中會返回diskCacheExecutor,然後開始執行DecodeJob:
// EngineJob.java
public void start(DecodeJob<R> decodeJob) {
this.decodeJob = decodeJob;
GlideExecutor executor = decodeJob.willDecodeFromCache()
? diskCacheExecutor
: getActiveSourceExecutor();
executor.execute(decodeJob);
}
// DecodeJob.java
boolean willDecodeFromCache() {
Stage firstStage = getNextStage(Stage.INITIALIZE);
return firstStage == Stage.RESOURCE_CACHE || firstStage == Stage.DATA_CACHE;
}
private Stage getNextStage(Stage current) {
switch (current) {
case INITIALIZE:
return diskCacheStrategy.decodeCachedResource()
? Stage.RESOURCE_CACHE : getNextStage(Stage.RESOURCE_CACHE);
case RESOURCE_CACHE:
return diskCacheStrategy.decodeCachedData()
? Stage.DATA_CACHE : getNextStage(Stage.DATA_CACHE);
case DATA_CACHE:
// Skip loading from source if the user opted to only retrieve the resource from cache.
return onlyRetrieveFromCache ? Stage.FINISHED : Stage.SOURCE;
case SOURCE:
case FINISHED:
return Stage.FINISHED;
default:
throw new IllegalArgumentException("Unrecognized stage: " + current);
}
}
DecodeJob會回撥run()開始執行, run()中呼叫runWrapped執行工作,這裡runReason還是RunReason.INITIALIZE ，根據前面的分析指導這裡會獲得一個ResourceCacheGenerator,然後呼叫runGenerators：
// DecodeJob.java
private void runWrapped() {
switch (runReason) {
case INITIALIZE:
stage = getNextStage(Stage.INITIALIZE);
currentGenerator = getNextGenerator();
runGenerators();
break;
case SWITCH_TO_SOURCE_SERVICE:
runGenerators();
break;
case DECODE_DATA:
decodeFromRetrievedData();
break;
default:
throw new IllegalStateException("Unrecognized run reason: " + runReason);
}
}
private DataFetcherGenerator getNextGenerator() {
switch (stage) {
case RESOURCE_CACHE:
return new ResourceCacheGenerator(decodeHelper, this);
case DATA_CACHE:
return new DataCacheGenerator(decodeHelper, this);
case SOURCE:
return new SourceGenerator(decodeHelper, this);
case FINISHED:
return null;
default:
throw new IllegalStateException("Unrecognized stage: " + stage);
}
}
在 runGenerators 中，會呼叫 startNext,目前currentGenerator是ResourceCacheGenerator, 那麼就是呼叫它的startNext方法：
// DecodeJob.java
private void runGenerators() {
currentThread = Thread.currentThread();
startFetchTime = LogTime.getLogTime();
boolean isStarted = false;
while (!isCancelled && currentGenerator != null
&& !(isStarted = currentGenerator.startNext())) {
stage = getNextStage(stage);
currentGenerator = getNextGenerator();
if (stage == Stage.SOURCE) {
reschedule();
return;
}
}
// We've run out of stages and generators, give up.
if ((stage == Stage.FINISHED || isCancelled) && !isStarted) {
notifyFailed();
}
}
看下ResourceCacheGenerator.startNext(), 這裡面就是重點邏輯了，首先從Registry中獲取支援資源型別的ModelLoader(其中ModelLoader是在構造Glide的時候傳進去), 然後從ModelLoader中構造LoadData,接著就能拿到DataFetcher,(關於ModelLoader/LoadData/DataFetcher之間的關係不在本次範圍內，後面有機會再另寫)透過它的loadData方法載入資料：
@Override
public boolean startNext() {
List<Key> sourceIds = helper.getCacheKeys();
if (sourceIds.isEmpty()) {
return false;
}
List<Class<?>> resourceClasses = helper.getRegisteredResourceClasses();
if (resourceClasses.isEmpty()) {
if (File.class.equals(helper.getTranscodeClass())) {
return false;
}
}
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);
currentKey =
new ResourceCacheKey(// NOPMD AvoidInstantiatingObjectsInLoops
helper.getArrayPool(),
sourceId,
helper.getSignature(),
helper.getWidth(),
helper.getHeight(),
transformation,
resourceClass,
helper.getOptions());
cacheFile = helper.getDiskCache().get(currentKey);
if (cacheFile != null) {
sourceKey = sourceId;
modelLoaders = helper.getModelLoaders(cacheFile);
modelLoaderIndex = 0;
}
}
loadData = null;
boolean started = false;
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;
}
如果在Resource中找不到需要的資源，那麼startNext就會返回false，在runGenerators中就會進入迴圈體內：
-
接著會重複上面執行getNextStage,由於現在Stage已經是RESOURCE_CACHE,所以接下來會返回DataCacheGenerator,執行邏輯和上面的ResourceCacheGenerator是一樣的，如果還是沒有找到需要的，進入迴圈體內。
-
此時getNextStage會根據用於是否設定只從磁碟中獲取資源，如果是就會通知失敗，回撥onLoadFailed；如果不是就設定當前Stage為Stage.SOURCE,接著往下走。
-
狀態就會進入迴圈內部的if條件邏輯裡面，呼叫reschedule。
-
在reschedule把runReason設定成SWITCH_TO_SOURCE_SERVICE,然後透過callback回撥。
-
DecodeJob中的callback是EngineJob傳遞過來的，所以現在返回到EngineJob。
-
在EngineJob中透過getActiveSourceExecutor切換到網路執行緒池中，執行DecodeJob，下面就準備開始發起網路請求。
四、網路快取
在Stage.SOURCE階段，透過getNextGenerator返回的是SourceGenerator,所以目前的currentGenerator就是它。
流程還是一樣的，SourceGenerator還是呼叫startNext方法，獲取到對應的DataFetcher，這裡其實是HttpUrlFetcher，發起網路請求。
// DecodeJob.java
private void runGenerators() {
...
while (!isCancelled && currentGenerator != null
&& !(isStarted = currentGenerator.startNext())) {
stage = getNextStage(stage);
currentGenerator = getNextGenerator();
if (stage == Stage.SOURCE) {
reschedule();
return;
}
}
...
}
@Override
public void reschedule() {
runReason = RunReason.SWITCH_TO_SOURCE_SERVICE;
callback.reschedule(this);
}
// EngineJob.java
@Override
public void reschedule(DecodeJob<?> job) {
getActiveSourceExecutor().execute(job);
}
先緩一緩，本文其實到了上面已經可以結束了，Glide涉及到的五級快取都已經涉及到了，是真的就可以結束了嗎？不是的，網路請求回來和快取還有關係嗎？接著看到HttpUrlFetcher,下載成功後回撥onDataReady,其中callback是SourceGenerator:
// HttpUrlFetcher.java
@Override
public void loadData(@NonNull Priority priority,
@NonNull DataCallback<? super InputStream> callback) {
long startTime = LogTime.getLogTime();
try {
InputStream result = loadDataWithRedirects(glideUrl.toURL(), 0, null, glideUrl.getHeaders());
callback.onDataReady(result);
} catch (IOException e) {
if (Log.isLoggable(TAG, Log.DEBUG)) {
Log.d(TAG, "Failed to load data for url", e);
}
callback.onLoadFailed(e);
} finally {
if (Log.isLoggable(TAG, Log.VERBOSE)) {
Log.v(TAG, "Finished http url fetcher fetch in " + LogTime.getElapsedMillis(startTime));
}
}
}
// EngineJob.java
@Override
public void reschedule(DecodeJob<?> job) {
getActiveSourceExecutor().execute(job);
}
正常情況會進入if判斷邏輯裡面，賦值dataToCache，然後回撥cb.reschedule，而cb就是DecodeJob構造SourceGenerator的時候傳入，cb是DecodeJob。
// SourceGenerator.java
@Override
public void onDataReady(Object data) {
DiskCacheStrategy diskCacheStrategy = helper.getDiskCacheStrategy();
if (data != null && diskCacheStrategy.isDataCacheable(loadData.fetcher.getDataSource())) {
dataToCache = data;
cb.reschedule();
} else {
cb.onDataFetcherReady(loadData.sourceKey, data, loadData.fetcher,
loadData.fetcher.getDataSource(), originalKey);
}
}
DecodeJob在reschedule回撥EngineJob,最後還是回到SourceGenerator中的startNext()邏輯。
// DecodeJob.java
private DataFetcherGenerator getNextGenerator() {
switch (stage) {
case RESOURCE_CACHE:
return new ResourceCacheGenerator(decodeHelper, this);
case DATA_CACHE:
return new DataCacheGenerator(decodeHelper, this);
case SOURCE:
return new SourceGenerator(decodeHelper, this);
case FINISHED:
return null;
default:
throw new IllegalStateException("Unrecognized stage: " + stage);
}
}
@Override
public void reschedule() {
runReason = RunReason.SWITCH_TO_SOURCE_SERVICE;
callback.reschedule(this);
}
和第一次進來的邏輯不一樣，現在dataToCache != null，進入第一個if邏輯。
在邏輯裡面呼叫cacheData,邏輯很明顯，保持資料到本地，然後會構造一個DataCacheGenerator。
而DataCacheGenerator前面已經分析過了，就是用來載入本地原始資料的，這回會載入成功，返回true。
// SourceGenerator.java
@Override
public boolean startNext() {
if (dataToCache != null) {
Object data = dataToCache;
dataToCache = null;
cacheData(data);
}
if (sourceCacheGenerator != null && sourceCacheGenerator.startNext()) {
return true;
}
...
}
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);
}
接下來就是一系列的回撥了：
DataCacheGenerator的startNext邏輯裡面會給DataFetcher傳遞自身作為callback，在載入本地資料成功後回撥onDataReady。
// DataCacheGenerator
@Override
public boolean startNext() {
...
loadData = null;
boolean started = false;
while (!started && hasNextModelLoader()) {
...
if (loadData != null && helper.hasLoadPath(loadData.fetcher.getDataClass())) {
started = true;
loadData.fetcher.loadData(helper.getPriority(), this);
}
}
return started;
}
@Override
public void onDataReady(Object data) {
cb.onDataFetcherReady(sourceKey, data, loadData.fetcher, DataSource.DATA_DISK_CACHE, sourceKey);
}
而cb現在是SourceGenerator傳遞過來,SourceGenerator再回撥它自己的cb，是DecodeJob在構造它的時候傳過來。
// SourceGenerator.java
@Override
public void onDataFetcherReady(Key sourceKey, Object data, DataFetcher<?> fetcher,
DataSource dataSource, Key attemptedKey) {
cb.onDataFetcherReady(sourceKey, data, fetcher, loadData.fetcher.getDataSource(), sourceKey);
}
// DecodeJob.java
@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 {
try {
decodeFromRetrievedData();
} finally {
GlideTrace.endSection();
}
}
}
在上面SourceGenerator把DecodeJob切換到ActiveSourceExecutor執行緒中執行，還記得一開始DecodeJob是在哪啟動的嗎？在EngineJob中啟動，然後是把DecodeJob放到diskCacheExecutor中執行。
// EngineJob.java
public void start(DecodeJob<R> decodeJob) {
this.decodeJob = decodeJob;
GlideExecutor executor = decodeJob.willDecodeFromCache()
? diskCacheExecutor
: getActiveSourceExecutor();
executor.execute(decodeJob);
}
所以上面在DecodeJob的onDataFetcherReady會走到第一個if邏輯裡面，然後賦值runReason = RunReason.DECODE_DATA,再一次回撥Engine.reschedule,將工作執行緒切換到ActiveSourceExecutor。
// Engine.java
@Override
public void reschedule(DecodeJob<?> job) {
// Even if the job is cancelled here, it still needs to be scheduled so that it can clean itself
// up.
getActiveSourceExecutor().execute(job);
}
//
然後還是走到DecodeJob, 現在會進入DECODE_DATA分支，在這裡面會呼叫ResourceDecoder把資料解碼：
private void runWrapped() {
switch (runReason) {
case INITIALIZE:
stage = getNextStage(Stage.INITIALIZE);
currentGenerator = getNextGenerator();
runGenerators();
break;
case SWITCH_TO_SOURCE_SERVICE:
runGenerators();
break;
case DECODE_DATA:
decodeFromRetrievedData();
break;
default:
throw new IllegalStateException("Unrecognized run reason: " + runReason);
}
}
解碼成功後呼叫notifyComplete(result, dataSource);
private void notifyComplete(Resource<R> resource, DataSource dataSource) {
setNotifiedOrThrow();
callback.onResourceReady(resource, dataSource);
}
五、總結
現在回答一下開頭的幾個問題。
1、有幾級快取？五級，分別是什麼？
-
活動資源 (Active Resources)
-
記憶體快取 (Memory Cache)
-
資源型別（Resource Disk Cache）
-
原始資料 (Data Disk Cache)
-
網路快取
2、Glide記憶體快取之間是什麼關係？
專門畫了一幅圖表明這個關係，言簡意賅。
3、Glide本地檔案IO和網路請求是一個執行緒嗎？
明顯不是，本地IO透過diskCacheExecutor,而網路IO透過ActiveSourceExecutor
4、Glide網路請求回來後資料直接返回給使用者還是先存再返回？
不是直接返回給使用者，會在SourceGenerator中構造一個DataCacheGenerator來取資料。
來自 “ ITPUB部落格 ” ，連結：http://blog.itpub.net/69912579/viewspace-2659292/，如需轉載，請註明出處，否則將追究法律責任。
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