1.综述

开始之前，关于Glide缓存请先思考几个问题：

• Glide有几级缓存？
• Glide内存缓存之间是什么关系？
• Glide本地文件IO和网络请求是一个线程吗？如果不是，怎么实现线程切换？
• Glide网络请求回来后数据直接返回给用户还是先存再返回？

加载开始入口从Engine.load()开始，先看下对这个方法的注释,

• 会先检查(Active Resources)，如果有就直接返回，Active Resources没有被引用的资源会放入Memory Cache，如果Active Resources没有，会往下走
• 检查Memory Cache中是否有需要的资源，如果有就返回，Memory Cache中没有就继续往下走
• 检查当前在运行中的job中是否有改资源的下载，有就在现有的job中直接添加callback返回，不重复下载，当然前提是计算得到的key是一致的，如果还是没有，就会构造一个新的job开始新的工作

   * 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, f the source code

2.内存缓存

  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,这一步会从ActiveResources中加载资源，首先判断是否使用内存缓存，否的话返回null；否则到ActiveResources中拿：

  // 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;
  }

接下来看下ActiveResources, 其实是用过弱引用保存使用过的资源。

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<>();
    
  ...
}

成功拿到数据后回调类型也是内存缓存：

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

接着回到Engine.load()中继续看到focus 2,如果在cache中找到就是remove掉，然后返回EngineResource，其中需要EngineResource进行acquire一下，这个后面再看，然后会把资源移到ActiveResources中，也就是上面提到的缓存：

// 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接口的实现，如果没设置，默认在build的时候是LruResourceCache, 也就是熟悉的LRU Cache:

// GlideBuilder.java
if (memoryCache == null) {
   memoryCache = new LruResourceCache(memorySizeCalculator.getMemoryCacheSize());
}

再看下EngineResource，主要是对资源增加了引用计数的功能：

// 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后会判断引用计数是否为0，如果是0就会回调onResourceReleased,在这里就是Engine,然后会把资源从ActiveResources中移除，资源默认是可缓存的，因此会把资源放到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，如果引用计数为0并且还没与回收，就会调用真正的Resource.recycle(),看其中的一个BitmapResource是怎么回收的,就是放到Bitmap池中，也是用的LRU Cache，这个和今天的主题不相关，就不继续往下拓展。

  // BitmapResource.java
  @Override
  public void recycle() {
    bitmapPool.put(bitmap);
  }

思路再拉到Engine.load()的流程中，接下来该看focus 3,这里再贴一下代码,如果job已经在运行了，那么直接添加一个回调后返回LoadStatus,这个可以允许用户取消任务：

// 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, 到这里就需要创建后台任务去拉取磁盘文件或者发起网络请求

3.磁盘缓存

   // 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);

先构造两个job，一个是EngineJob,另外一个DecodeJob,其中DecodeJob会根据需要解码的资源来源分成下面几个阶段:

// 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,
  }

在构造DecodeJob时会把状态置为INITIALIZE。

构造完两个Job后会调用EngineJob.start(DecodeJob)，首先会调用getNextStage来确定下一个阶段，这里面跟DiskCacheStrategy这个传入的磁盘缓存策略有关。

磁盘策略有下面几种：

ALL: 缓存原始数据和转换后的数据
NONE: 不缓存
DATA: 原始数据，未经过解码或者转换
RESOURCE: 缓存经过解码的数据
AUTOMATIC(默认)：根据`EncodeStrategy`和`DataSource`等条件自动选择合适的缓存方式

默认的AUTOMATIC方式是允许解码缓存的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会先返回Stage.RESOURCE_CACHE,然后在start中会返回diskCacheExecutor,然后开始执行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会回调run()开始执行, run()中调用runWrapped执行工作,这里runReason还是RunReason.INITIALIZE ，根据前面的分析指导这里会获得一个ResourceCacheGenerator,然后调用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，会调用startNext,目前currentGenerator是ResourceCacheGenerator, 那么就是调用它的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(), 这里面就是重点逻辑了，首先从Registry中获取支持资源类型的ModelLoader(其中ModelLoader是在构造Glide的时候传进去), 然后从ModelLoader中构造LoadData,接着就能拿到DataFetcher,(关于ModelLoader/LoadData/DataFetcher之间的关系不在本次范围内，后面有机会再另写)通过它的loadData方法加载数据：

  @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中找不到需要的资源，那么startNext就会返回false，在runGenerators中就会进入循环体内：

• 接着会重复上面执行getNextStage,由于现在Stage已经是RESOURCE_CACHE,所以接下来会返回DataCacheGenerator,执行逻辑和上面的ResourceCacheGenerator是一样的，如果还是没有找到需要的，进入循环体内
• 此时getNextStage会根据用于是否设置只从磁盘中获取资源，如果是就会通知失败，回调onLoadFailed；如果不是就设置当前Stage为Stage.SOURCE,接着往下走
• 状态就会进入循环内部的if条件逻辑里面，调用reschedule
• 在reschedule把runReason设置成SWITCH_TO_SOURCE_SERVICE,然后通过callback回调
• DecodeJob中的callback是EngineJob传递过来的，所以现在返回到EngineJob
• 在EngineJob中通过getActiveSourceExecutor切换到网络线程池中，执行DecodeJob，下面就准备开始发起网络请求

4.网络缓存

• 在Stage.SOURCE阶段，通过getNextGenerator返回的是SourceGenerator,所以目前的currentGenerator就是它
• 流程还是一样的，SourceGenerator还是调用startNext方法，获取到对应的DataFetcher，这里其实是HttpUrlFetcher，发起网络请求

// 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);
  }

先缓一缓，本文其实到了上面已经可以结束了，Glide涉及到的五级缓存都已经涉及到了，是真的就可以结束了吗？不是的，网络请求回来和缓存还有关系吗？接着看到HttpUrlFetcher,下载成功后回调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);
  }

• 正常情况会进入if判断逻辑里面，赋值dataToCache，然后回调cb.reschedule，而cb就是DecodeJob构造SourceGenerator的时候传入，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回调EngineJob,最后还是回到SourceGenerator中的startNext()逻辑

// 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);
  }

• 和第一次进来的逻辑不一样，现在dataToCache != null，进入第一个if逻辑
• 在逻辑里面调用cacheData,逻辑很明显，保持数据到本地，然后会构造一个DataCacheGenerator
• 而DataCacheGenerator前面已经分析过了，就是用来加载本地原始数据的，这回会加载成功，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);
  }

接下来就是一系列的回调了：

• DataCacheGenerator的startNext逻辑里面会给DataFetcher传递自身作为callback，在加载本地数据成功后回调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现在是SourceGenerator传递过来,SourceGenerator再回调它自己的cb，是DecodeJob在构造它的时候传过来

// 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切换到ActiveSourceExecutor线程中执行，还记得一开始DecodeJob是在哪启动的吗？在EngineJob中启动，然后是把DecodeJob放到diskCacheExecutor中执行

// 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会走到第一个if逻辑里面，然后赋值runReason = RunReason.DECODE_DATA,再一次回调Engine.reschedule,将工作线程切换到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);
  }

// 

• 然后还是走到DecodeJob, 现在会进入DECODE_DATA分支，在这里面会调用ResourceDecoder把数据解码：

  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);
    }
  }

• 解码成功后调用notifyComplete(result, dataSource);

  private void notifyComplete(Resource<R> resource, DataSource dataSource) {
    setNotifiedOrThrow();
    callback.onResourceReady(resource, dataSource);
  }

5.总结

现在回答一下开头的几个问题。

1. 有几级缓存？五级，分别是

• 活动资源 (Active Resources)
• 内存缓存 (Memory Cache)
• 资源类型（Resource Disk Cache）
• 原始数据 (Data Disk Cache)
• 网络缓存

2. Glide内存缓存之间是什么关系？专门画了一幅图表明这个关系，言简意赅

image

3. Glide本地文件IO和网络请求是一个线程吗？明显不是，本地IO通过diskCacheExecutor,而网络IO通过ActiveSourceExecutor

4. Glide网络请求回来后数据直接返回给用户还是先存再返回？不是直接返回给用户，会在SourceGenerator中构造一个DataCacheGenerator来取数据