Glide 緩存流程

本文首發於 vivo互聯網技術 微信公衆號 
鏈接：https://mp.weixin.qq.com/s/cPLkefpEb3w12-uoiqzTig
作者：連凌能

Android上圖片加載的解決方案有多種，但是官方認可的是Glide。Glide提供簡潔易用的api，整個框架也方便擴展，比如可以替換網絡請求庫，同時也提供了完備的緩存機制，應用層不需要自己去管理圖片的緩存與獲取，框架會分成內存緩存，文件緩存和遠程緩存。本文不會從簡單的使用着手，會把重點放在緩存機制的分析上。

一、綜述

開始之前，關於Glide緩存請先思考幾個問題：

• Glide有幾級緩存？

• Glide內存緩存之間是什麼關係？

• Glide本地文件IO和網絡請求是一個線程嗎？如果不是，怎麼實現線程切換？

• Glide網絡請求回來後數據直接返回給用戶還是先存再返回？

加載開始入口從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。

• 檢查當前在運行中的job中是否有改資源的下載，有就在現有的job中直接添加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>
* </ul>

ok, find the source code.

二、內存緩存

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 中加載資源，首先判斷是否使用內存緩存，否的話返回null；否則到 ActiveResources 中取數據：

// 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, 其實是用過弱引用保存使用過的資源。

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<>();

  ...
}

成功取到數據後回調類型也是內存緩存：

EngineResource<?> cached = loadFromCache(key, isMemoryCacheable);
if (cached != null) {
   cb.onResourceReady(cached, DataSource.MEMORY_CACHE);
   return null;
}

接着回到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，也就是上面提到的緩存：

// 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接口的實現，如果沒設置，默認在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爲0，如果是0就會回調onResourceReleased,在這裏就是Engine,然後會把資源從ActiveResources中移除，資源默認是可緩存的，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，如果引用計數爲0並且還沒與回收，就會調用真正的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，就不繼續往下拓展。

// 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,這裏再貼一下代碼,如果job已經在運行了，那麼直接添加一個回調後返回LoadStatus,這個可以允許用戶取消任務：

// 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);
    }
  }

接着往下看到focus 4, 到這裏就需要創建後臺任務去拉取磁盤文件或者發起網絡請求。

三、磁盤緩存

// 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時會把狀態置爲INITIALIZE。

構造完兩個 Job 後會調用 EngineJob.start(DecodeJob)，首先會調用getNextStage來確定下一個階段，這裏面跟DiskCacheStrategy這個傳入的磁盤緩存策略有關。

磁盤策略有下面幾種：

• **ALL: **緩存原始數據和轉換後的數據

• **NONE: **不緩存

• **DATA: **原始數據，未經過解碼或者轉換

• **RESOURCE: **緩存經過解碼的數據

• **AUTOMATIC(默認)：**根據`EncodeStrategy`和`DataSource`等條件自動選擇合適的緩存方

默認的AUTOMATIC方式是允許解碼緩存的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會回調run()開始執行, run()中調用runWrapped執行工作,這裏runReason還是RunReason.INITIALIZE ，根據前面的分析指導這裏會獲得一個ResourceCacheGenerator,然後調用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，會調用 startNext,目前currentGenerator是ResourceCacheGenerator, 那麼就是調用它的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(), 這裏面就是重點邏輯了，首先從Registry中獲取支持資源類型的ModelLoader(其中ModelLoader是在構造Glide的時候傳進去), 然後從ModelLoader中構造LoadData,接着就能拿到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)通過它的loadData方法加載數據：

@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中就會進入循環體內：

• 接着會重複上面執行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，進入循環體內。

• 此時getNextStage會根據用於是否設置只從磁盤中獲取資源，如果是就會通知失敗，回調onLoadFailed；如果不是就設置當前Stage爲Stage.SOURCE,接着往下走。

• 狀態就會進入循環內部的if條件邏輯裏面，調用reschedule。

• 在reschedule把runReason設置成SWITCH_TO_SOURCE_SERVICE,然後通過callback回調。

• DecodeJob中的callback是EngineJob傳遞過來的，所以現在返回到EngineJob。

• 在EngineJob中通過getActiveSourceExecutor切換到網絡線程池中，執行DecodeJob，下面就準備開始發起網絡請求。

四、網絡緩存

在Stage.SOURCE階段，通過getNextGenerator返回的是SourceGenerator,所以目前的currentGenerator就是它。

流程還是一樣的，SourceGenerator還是調用startNext方法，獲取到對應的DataFetcher，這裏其實是HttpUrlFetcher，發起網絡請求。

// 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涉及到的五級緩存都已經涉及到了，是真的就可以結束了嗎？不是的，網絡請求回來和緩存還有關係嗎？接着看到HttpUrlFetcher,下載成功後回調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判斷邏輯裏面，賦值dataToCache，然後回調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回調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。

在邏輯裏面調用cacheData,邏輯很明顯，保持數據到本地，然後會構造一個DataCacheGenerator。

而DataCacheGenerator前面已經分析過了，就是用來加載本地原始數據的，這回會加載成功，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調了：

DataCacheGenerator的startNext邏輯裏面會給DataFetcher傳遞自身作爲callback，在加載本地數據成功後回調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再回調它自己的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線程中執行，還記得一開始DecodeJob是在哪啓動的嗎？在EngineJob中啓動，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邏輯裏面，然後賦值runReason = RunReason.DECODE_DATA,再一次回調Engine.reschedule,將工作線程切換到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，在這裏面會調用ResourceDecoder把數據解碼：

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);
    }
  }

解碼成功後調用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、有幾級緩存？五級，分別是什麼？

• 活動資源 (Active Resources)

• 內存緩存 (Memory Cache)

• 資源類型（Resource Disk Cache）

• 原始數據 (Data Disk Cache)

• 網絡緩存

2、Glide內存緩存之間是什麼關係？

專門畫了一幅圖表明這個關係，言簡意賅。

3、Glide本地文件IO和網絡請求是一個線程嗎？

明顯不是，本地IO通過diskCacheExecutor,而網絡IO通過ActiveSourceExecutor

4、Glide網絡請求回來後數據直接返回給用戶還是先存再返回？

不是直接返回給用戶，會在SourceGenerator中構造一個DataCacheGenerator來取數據。