Volley学习(RequestQueue分析)_移动开发_编程开发_程序员俱乐部

      Volley的RequestQueue用来缓存请求处理器CacheDispatch和网络请求处理器NetworkDispatch来处理Request的。当我们调用RequestQueue.start()是，两个处理器开始运行起来，等待Request的到来。

       

class="brush:java;gutter:true;"> public void start() {
        stop();  // Make sure any currently running dispatchers are stopped.
        // Create the cache dispatcher and start it.
        mCacheDispatcher = new CacheDispatcher(mCacheQueue, mNetworkQueue, mCache, mDelivery);
        mCacheDispatcher.start();

        // Create network dispatchers (and corresponding threads) up to the pool size.
        for (int i = 0; i < mDispatchers.length; i++) {
            NetworkDispatcher networkDispatcher = new NetworkDispatcher(mNetworkQueue, mNetwork,
                    mCache, mDelivery);
            mDispatchers[i] = networkDispatcher;
            networkDispatcher.start();
        }
    }

　 Volley先读缓存然后，没有cache hit的话再从网络上获取，所以先启动CacheDispatcher，然后启动NetworkDispatcher。不过在启动处理器前先调用stop()函数清除掉以前RequestQueue里的过期的Dispatcher(Dispatcher都是继承Thread)。以防影响性能。Volley启动一个CacheDispatcher和4个NetworkDispatcher,之所以这样设计，个人人为是主要考虑到网络图片的下载，所以利用多个NetworkDispatcher来处理网络请求。然后看一下stop()函数。

   

   public void stop() {
        if (mCacheDispatcher != null) {
            mCacheDispatcher.quit();
        }
        for (int i = 0; i < mDispatchers.length; i++) {
            if (mDispatchers[i] != null) {
                mDispatchers[i].quit();
            }
        }
    }

　　 调用Dispatcher的quit()函数来结束线程。以NetworkDispatcher.quit()为例：

 public void quit() {
        mQuit = true;
        interrupt();
    }

　　函数将mQuit变量置为true。为什么要这样做，因为在networkdispatcher线程中的中断异常处理中，判断mQuit的值，如果真，则退出循环，结束线程。否则continue,继续从Queue中去取Request处理。

 try {
                // Take a request from the queue.
                request = mQueue.take();
            } catch (InterruptedException e) {
                // We may have been interrupted because it was time to quit.
                if (mQuit) {
                    return;
                }
                continue;
            }

　　接下来，看下RequestQueue的add函数。

   

 public Request add(Request request) {
        // Tag the request as belonging to this queue and add it to the set of current requests.
        request.setRequestQueue(this);
        synchronized (mCurrentRequests) {
            mCurrentRequests.add(request);
        }

        // Process requests in the order they are added.
        request.setSequence(getSequenceNumber());
        request.addMarker("add-to-queue");

        // If the request is uncacheable, skip the cache queue and go straight to the network.
        if (!request.shouldCache()) {
            mNetworkQueue.add(request);
            return request;
        }

        // Insert request into stage if there's already a request with the same cache key in flight.
        synchronized (mWaitingRequests) {
            String cacheKey = request.getCacheKey();
            if (mWaitingRequests.containsKey(cacheKey)) {
                // There is already a request in flight. Queue up.
                Queue<Request> stagedRequests = mWaitingRequests.get(cacheKey);
                if (stagedRequests == null) {
                    stagedRequests = new LinkedList<Request>();
                }
                stagedRequests.add(request);
                mWaitingRequests.put(cacheKey, stagedRequests);
                if (VolleyLog.DEBUG) {
                    VolleyLog.v("Request for cacheKey=%s is in flight, putting on hold.", cacheKey);
                }
            } else {
                // Insert 'null' queue for this cacheKey, indicating there is now a request in
                // flight.
                mWaitingRequests.put(cacheKey, null);
                mCacheQueue.add(request);
            }
            return request;
        }
    }

　　首先将Request加入到mCurrentRequests中，因为存在多个线程竞争的问题，在这个代码块上进行了同步。然后request.setSequence().为当前Request分配一个序列号，为什么这样做，因为我们下面要将Request放到NetworkQueue中或者CacheQueue中，这两个队列都是PriorityBlockingQueue，里面的元素是根据自定义的权重来排序的。PriorityBlockingQueue里的元素须实现Comparable接口，来看下我们这里的Requeset的实现：

    

 @Override
    public int compareTo(Request<T> other) {
        Priority left = this.getPriority();
        Priority right = other.getPriority();

        // High-priority requests are "lesser" so they are sorted to the front.
        // Equal priorities are sorted by sequence number to provide FIFO ordering.
        return left == right ?
                this.mSequence - other.mSequence :
                right.ordinal() - left.ordinal();
    }

　　Request的策略是现根据每个Request的Priority来判断，如果两个Request的Priority相同，那么载根据两个Request的Sequence来进行判断队列里的先后顺序。

     

logs_code_hide('eaa0c23c-c62f-49d3-905c-bd7fe200f7d0',event)" src="/Upload/Images/2015050416/2B1B950FA3DF188F.gif" alt="" />

1 public enum Priority {
2         LOW,
3         NORMAL,
4         HIGH,
5         IMMEDIATE
6     }

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     给当前Request加上序列后，判断一下当前Request是否需要缓存，如果不需要则直接把Request加入到NetworkQueue队列里。如果需要缓存，取出Request的缓存键，从mWaitingRequests里看下有没有Request的缓存键.在RequestQueue中有四个队列。mCurrentRequests，mWaitingRequests，mCacheQueue，mNetworkQueue。每当一个请求到来时，先加入到mCurrentRequests,然后判断当前Request是否需要缓存，如果不用缓存的Request，则直接加入到mNetworkQueue队列中等待网络处理器(NetWorkDispatcher)去处理。如果需要缓存的话，根据Request获取相应的cacheKey,如果cacheKey不存在的话，说明这个需要缓存的Request是第一次请求。那么将cacheKey放入到mWaitingRequests队列里。(这里插播一下，mCurrentRequests存放的是所有交由RequestQueue处理的Request,mWaitingRequests里存放的是mCacheQueue里已经有相同url的Request,mWatiingRequests的出现就是为了避免不必要的网络数据获取)，并将Request放入到mCacheQueue中以做处理。

1   // Insert 'null' queue for this cacheKey, indicating there is now a request in
2                 // flight.
3                 mWaitingRequests.put(cacheKey, null);
4                 mCacheQueue.add(request);

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    如果cacheKey存在的话，说明已经有相同的Request正在处理（这里的cacheKey是通过getUrl()得到的,也就是创建Request时的url)。这时将此Request放入到mWaitingRequest队列中等待In-flight Request的处理结果。

    add完然后看finish(Request req);

 1  void finish(Request request) {
 2         // Remove from the set of requests currently being processed.
 3         synchronized (mCurrentRequests) {
 4             mCurrentRequests.remove(request);
 5         }
 6 
 7         if (request.shouldCache()) {
 8             synchronized (mWaitingRequests) {
 9                 String cacheKey = request.getCacheKey();
10                 Queue<Request> waitingRequests = mWaitingRequests.remove(cacheKey);
11                 if (waitingRequests != null) {
12                     if (VolleyLog.DEBUG) {
13                         VolleyLog.v("Releasing %d waiting requests for cacheKey=%s.",
14                                 waitingRequests.size(), cacheKey);
15                     }
16                     // Process all queued up requests. They won't be considered as in flight, but
17                     // that's not a problem as the cache has been primed by 'request'.
18                     mCacheQueue.addAll(waitingRequests);
19                 }
20             }
21         }
22     }

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     首先先从mCurrentRequests集合中remove掉当前Request,然后在mWaitingRequests中去掉当前的Request.然后将此Request对应的mWaitingRequest中存储的Request放到mCacheQueue中等待处理（因为此时对应的url的网络数据已经加载到本地，所以这些mWaitingRequests里的Request被处理时直接从本地解析，不用耗时的网络获取一遍）。

    RequestQueue类中还有一个CancelAll()函数，它的作用是根据指定的Request tag来删除响应的Request.

    public void cancelAll(RequestFilter filter) {
        synchronized (mCurrentRequests) {
            for (Request<?> request : mCurrentRequests) {
                if (filter.apply(request)) {
                    request.cancel();
                }
            }
        }
    }

    /**
     * Cancels all requests in this queue with the given tag. Tag must be non-null
     * and equality is by identity.
     */
    public void cancelAll(final Object tag) {
        if (tag == null) {
            throw new IllegalArgumentException("Cannot cancelAll with a null tag");
        }
        cancelAll(new RequestFilter() {
            @Override
            public boolean apply(Request<?> request) {
                return request.getTag() == tag;
            }
        });
    }