所谓生产者消费者模式,就是一个地方无脑生产,一个地方无脑消费,通过一个中间缓冲区建立的一种模式。这样的解耦是不是很多人所向往的,而解耦的关键是如何使用中间的缓冲区。生活中的例子也有很多,像卖手机的,他们只负责生产,而我们只负责消费,中间的缓冲区便是他们的库存。再比如邮局,我们只负责写信,收信人只负责收信,中间的缓冲区便是邮局。还有,坐地铁,上班打卡。。。生活中处处充满着这个模型。
生产者和消费者模型
有了生产和消费,但是世界永远唯一不变的是变化,于是就产生了各种问题,生产者和消费者的量不一致,时间的把控,效率的高低,都是问题出现的因素。在美丽的大Android中很多地方也运用到了这个模型,同样的,也会出现这个问题,那么Android中是如何处理这些问题的呢?他的缓冲区是如何做的呢?
首先,看看Android中常用到这个模型的有哪些应用?
曾经面试的问题,Android中有几种方式可以在子线程中更新UI? 初学者看到这里,应该会自豪的说:
1,runOnUiThread 2,view.post() 3,handlerrunOnUiThread
view.post()
前两种方式的源码 其内部都实现了mHandler.post(action)方法,说明这三种方式其实,就是一种方式,通过Handler机制实现,关于Handler机制实现,请听下回分解。
另外还有最熟悉的Toast
Toast内部源码
其内部也是Handler:mHandler.obtainMessage(0, windowToken).sendToTarget();
内部的实现都是Hander机制,其实Android消息机制的核心便是Handler机制,而实现消息机制模型就是生产者消费者模型。那么,Handler机制是如何实现的呢?
查看源码一路追踪,拨开层层迷雾,可以在MessageQueue,Message中查看得到生产者消费者模型的影子,Message就是生产出来的事物,而MessageQueue实现了生产和消费操作功能。
MeesageQueue,具体查看代码如下:enqueueMessage()
boolean enqueueMessage(Message msg, long when) { if (msg.target == null) { throw new IllegalArgumentException("Message must have a target."); } if (msg.isInUse()) { throw new IllegalStateException(msg + " This message is already in use."); } synchronized (this) { if (mQuitting) { IllegalStateException e = new IllegalStateException( msg.target + " sending message to a Handler on a dead thread"); Log.w(TAG, e.getMessage(), e); msg.recycle(); return false; } msg.markInUse(); msg.when = when; Message p = mMessages; boolean needWake; if (p == null || when == 0 || when < p.when) { // New head, wake up the event queue if blocked. msg.next = p; mMessages = msg; needWake = mBlocked; } else { // Inserted within the middle of the queue. Usually we don't have to wake // up the event queue unless there is a barrier at the head of the queue // and the message is the earliest asynchronous message in the queue. needWake = mBlocked && p.target == null && msg.isAsynchronous(); Message prev; for (;;) { prev = p; p = p.next; if (p == null || when < p.when) { break; } if (needWake && p.isAsynchronous()) { needWake = false; } } msg.next = p; // invariant: p == prev.next prev.next = msg; } // We can assume mPtr != 0 because mQuitting is false. if (needWake) { nativeWake(mPtr); } } return true; }next()
Message next() { // Return here if the message loop has already quit and been disposed. // This can happen if the application tries to restart a looper after quit // which is not supported. final long ptr = mPtr; if (ptr == 0) { return null; } int pendingIdleHandlerCount = -1; // -1 only during first iteration int nextPollTimeoutMillis = 0; for (;;) { if (nextPollTimeoutMillis != 0) { Binder.flushPendingCommands(); } nativePollOnce(ptr, nextPollTimeoutMillis); synchronized (this) { // Try to retrieve the next message. Return if found. final long now = SystemClock.uptimeMillis(); Message prevMsg = null; Message msg = mMessages; if (msg != null && msg.target == null) { // Stalled by a barrier. Find the next asynchronous message in the queue. do { prevMsg = msg; msg = msg.next; } while (msg != null && !msg.isAsynchronous()); } if (msg != null) { if (now < msg.when) { // Next message is not ready. Set a timeout to wake up when it is ready. nextPollTimeoutMillis = (int) Math.min(msg.when - now, Integer.MAX_VALUE); } else { // Got a message. mBlocked = false; if (prevMsg != null) { prevMsg.next = msg.next; } else { mMessages = msg.next; } msg.next = null; if (DEBUG) Log.v(TAG, "Returning message: " + msg); msg.markInUse(); return msg; } } else { // No more messages. nextPollTimeoutMillis = -1; } // Process the quit message now that all pending messages have been handled. if (mQuitting) { dispose(); return null; } // If first time idle, then get the number of idlers to run. // Idle handles only run if the queue is empty or if the first message // in the queue (possibly a barrier) is due to be handled in the future. if (pendingIdleHandlerCount < 0 && (mMessages == null || now < mMessages.when)) { pendingIdleHandlerCount = mIdleHandlers.size(); } if (pendingIdleHandlerCount <= 0) { // No idle handlers to run. Loop and wait some more. mBlocked = true; continue; } if (mPendingIdleHandlers == null) { mPendingIdleHandlers = new IdleHandler[Math.max(pendingIdleHandlerCount, 4)]; } mPendingIdleHandlers = mIdleHandlers.toArray(mPendingIdleHandlers); } // Run the idle handlers. // We only ever reach this code block during the first iteration. for (int i = 0; i < pendingIdleHandlerCount; i++) { final IdleHandler idler = mPendingIdleHandlers[i]; mPendingIdleHandlers[i] = null; // release the reference to the handler boolean keep = false; try { keep = idler.queueIdle(); } catch (Throwable t) { Log.wtf(TAG, "IdleHandler threw exception", t); } if (!keep) { synchronized (this) { mIdleHandlers.remove(idler); } } } // Reset the idle handler count to 0 so we do not run them again. pendingIdleHandlerCount = 0; // While calling an idle handler, a new message could have been delivered // so go back and look again for a pending message without waiting. nextPollTimeoutMillis = 0; }分析如下:
生产物
Message链表.png
生产者:
enqueueMessage() 生产的对象为Message if(beforeMessag==null||when=0||when<beforeMessag.when){ initMessage; }else{//新消息,是入队操作 prevMsg.next=curMsg; } Message p=Message mMessage; Message prev; loop //循环取出当前链表最后一个message,赋值给prev; ->prev =p; ->p=p.next; //赋值给Next msg.next=p=null; prev.next =msg;消费者:
next() loop ->Message prevMsg=null; Message msg=mMessages; //将下一个Msg上移,for loop 将剩下来的msg一一往前移动 -> if(prevMsg!=null) prevMsg.next=msg.next; -> else mMessages=msg.next;// 主链表上移一个msg -> return msg;1,enqueueMessage() 为生产线程执行,入队一个Message ,return true。
2,next() 为消费线程执行,出队:在Looper.loop()中不断取, 而在next()中也是loop 只要取到了便return msg 否则wait。next加了一个同步锁,保证了与enqueue的互斥。enqueue 同样也添加了同步锁,从而保证了与next的互斥:将message添加到Message链表中去,判断,如果出现阻塞了,需要进行唤醒操作。妥妥的生产者消费者模型。
生产者和消费者的精髓是:
不同线程操作同一对象的不同方法,但是要保持其互斥,也不能出现死锁的情况,条件满足就通知其他等待的线程 ,条件不满足,就休眠等待。
在Thread-1的生产者只负责生产,在Thread-2的消费者则只负责消费,操作互斥,当生产者达到上限则进行等待,反之消费者达到上限所有线程就等待。
【引用】1,模式解释灵感:戳这里看大神的解释2,MessageQueue源码解析3,Toast源码解析,艾玛,和我看的顺序一样一样的
作者:袋袋_Deken 链接:https://www.jianshu.com/p/3ad28eccd6f9 来源:简书 简书著作权归作者所有,任何形式的转载都请联系作者获得授权并注明出处。