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你真的了解AsyncTask吗?AsyncTask源码分析

1,概述

Android UI是线程不安全的,如果想要在子线程很好的访问ui, 就要借助Android中的异步消息处理机制

http://blog.csdn.net/yianemail/article/details/50233373

通过Thread 执行耗时操作,通常利用Handler 发送消息给ui线程。

这种方式代码相对臃肿,并且不能对多任务执行很好的控制。

为了简化操作,Android 1.5提供了更加轻量级的AsyncTask异步工具类,使创建异步任务变得异常简单。

2,AsyncTask 的使用

看一个最典型的AsyncTask 简单使用场景

package com.listenread.luhuanju.helloword; import android.os.AsyncTask; import android.support.v7.app.AppCompatActivity; import android.os.Bundle;  public class MainActivity extends AppCompatActivity {      @Override     protected void onCreate(Bundle savedInstanceState) {         super.onCreate(savedInstanceState);         setContentView(R.layout.activity_main);         //AsyncTask 开始执行异步任务         new MyAsyncTask().execute();     }      class MyAsyncTask extends AsyncTask<Void, Void, String> {         @Override         protected String doInBackground(Void... params) {             //Commen is request resurce from http and return to onPostExecute             //模拟数据返回             return "mStr";         }          @Override         protected void onPostExecute(String s) {             super.onPostExecute(s);             //获取数据         }     } }

3,源码解析

既然代码入口

new MyAsyncTask().execute();

我们就从它的构造函数分析,

/**      * Creates a new asynchronous task. This constructor must be invoked on the UI thread.      * 方法注释就说明了必须要在ui thread 进行AsyncTask调用      */     public AsyncTask() {         mWorker = new WorkerRunnable<Params, Result>() {             public Result call() throws Exception {                 mTaskInvoked.set(true);                  Process.setThreadPriority(Process.THREAD_PRIORITY_BACKGROUND);                 //noinspection unchecked                 Result result = doInBackground(mParams);                 Binder.flushPendingCommands();                 return postResult(result);             }         };          mFuture = new FutureTask<Result>(mWorker) {             @Override             protected void done() {                 try {                     postResultIfNotInvoked(get());                 } catch (InterruptedException e) {                     android.util.Log.w(LOG_TAG, e);                 } catch (ExecutionException e) {                     throw new RuntimeException("An error occurred while executing doInBackground()",                             e.getCause());                 } catch (CancellationException e) {                     postResultIfNotInvoked(null);                 }             }         };

来分析一下构造函数实例化的两个变量mWorker 以及 mFuture

private static abstract class WorkerRunnable<Params, Result> implements Callable<Result> {         Params[] mParams;     }

可以看到mWorker 是实现了参数是泛型的 Callable接口,看下Callable接口的声明

public interface Callable<V> {     /**      * Computes a result, or throws an exception if unable to do so.      *      * @return computed result      * @throws Exception if unable to compute a result      */     V call() throws Exception; }

只有一个返回类型为泛型的 Call() 方法。

这里介绍一下Callable 这个接口,在java中,实现多线程的方法除了Runnable之外,还有Callable,Future 以及FutureTask(没错,就是一会要分析的这货),与Runnable不同的是,这几个类型都只能在线程池当中实现。Callable 与 Runnable 最关键的异点是Callable 可以有返回值。然而Runnable 是拿不到执行的返回值的。这也就再一次解释了

public interface Callable<V> {     V call() throws Exception; //返回值泛型v }

对比Runnable的接口声明

public interface Runnable {     public void run(); //无返回值 }

再来看一下mFuture 这货,可以看到把mWorker当作参数

public class FutureTask<V> implements RunnableFuture<V> {

可以看到FutureTask 实现了RunnableFuture< V>接口

public interface RunnableFuture<V> extends Runnable, Future<V> {     /**      * Sets this Future to the result of its computation      * unless it has been cancelled.      */     void run(); }

而RunnableFuture 继承了Runnable 以及Future终于到了Future了,继续看Future 的声明

public interface Future<V> {  /**   * ...忽略方法的注释声明   */     boolean cancel(boolean mayInterruptIfRunning);     boolean isCancelled();     boolean isDone();     V get() throws InterruptedException, ExecutionException;     V get(long timeout, TimeUnit unit)         throws InterruptedException, ExecutionException, TimeoutException; }

看到这 我们大概明白了AsyncTask的一大优势所在,没错,就是可控。总结一下FutureTask的作用,FutureTask作为一个可管理的异步任务,使得在线程池中执行的异步任务可以被更精准的控制。

分析完构造函数中 两个实例化的变量,在继续看execute()方法

public final AsyncTask<Params, Progress, Result> execute(Params... params) {         return executeOnExecutor(sDefaultExecutor, params);     }

execute()继续调用了executeOnExecutor(sDefaultExecutor, params) ,并且传递两个参数sDefaultExecutor以及params

我们看下sDefaultExecutor

private static volatile Executor sDefaultExecutor = SERIAL_EXECUTOR;    public static final Executor SERIAL_EXECUTOR = new SerialExecutor();

所以我们只需要看下SerialExecutor 的实现即可;

private static class SerialExecutor implements Executor {         final ArrayDeque<Runnable> mTasks = new ArrayDeque<Runnable>();         Runnable mActive;          public synchronized void execute(final Runnable r) {             mTasks.offer(new Runnable() {                 public void run() {                     try {                         r.run();                     } finally {                         scheduleNext();                     }                 }             });             if (mActive == null) {                 scheduleNext();             }         }          protected synchronized void scheduleNext() {             if ((mActive = mTasks.poll()) != null) {                 THREAD_POOL_EXECUTOR.execute(mActive);             }         }     }

SerialExecutor就是一个线程池, AsyncTask 的内部类,实现了Executor 接口

public interface Executor {      /**      * Executes the given command at some time in the future.  The command      * may execute in a new thread, in a pooled thread, or in the calling      * thread, at the discretion of the {@code Executor} implementation.      *      * @param command the runnable task      * @throws RejectedExecutionException if this task cannot be      * accepted for execution      * @throws NullPointerException if command is null      */     void execute(Runnable command); }

我们看下这句方法的注释就能明白execute()的作用就是在线程池中分配线程执行异步任务。那么execute()方法在AsyncTask 到底执行什么任务呢?没错,就是

public synchronized void execute(final Runnable r) {             mTasks.offer(new Runnable() {                 public void run() {                     try {                         r.run();                     } finally {                         scheduleNext();                     }                 }             });             if (mActive == null) {                 scheduleNext();             }         }

我们发现了 mTasks.offer 这个方法,看下mTasks

final ArrayDeque<Runnable> mTasks = new ArrayDeque<Runnable>();

简单说一下ArrayDeque

ArrayDeque是一个双端队列,它具有:

数组双端队列没有容量限制,使他们增长为必要支持使用。

不支持多线程并发访问。

它们要比堆栈Stack和LinkedList快。

看下它的offer()

/**      * Inserts the specified element at the end of this deque.      * 这句注释的意思就是说添加特定的元素(就是Runnable)到队尾      * <p>This method is equivalent to {@link #offerLast}.      *      * @param e the element to add      * @return <tt>true</tt> (as specified by {@link Queue#offer})      * @throws NullPointerException if the specified element is null      */     public boolean offer(E e) {         return offerLast(e);     }

调用的 offerLast(e)

public boolean offerLast(E e) {         addLast(e);         return true;     }

继续addLast(e)

public void addLast(E e) {         if (e == null)             throw new NullPointerException("e == null");         elements[tail] = e;         if ( (tail = (tail + 1) & (elements.length - 1)) == head)             doubleCapacity();     }   /**      * Double the capacity of this deque.  Call only when full, i.e.,      * when head and tail have wrapped around to become equal.      */     private void doubleCapacity() {         // assert head == tail;         int p = head;         int n = elements.length;         int r = n - p; // number of elements to the right of p         int newCapacity = n << 1;         if (newCapacity < 0)             throw new IllegalStateException("Sorry, deque too big");         Object[] a = new Object[newCapacity];         System.arraycopy(elements, p, a, 0, r);         System.arraycopy(elements, 0, a, r, p);         elements = a;         head = 0;         tail = n;     }

简单分析一下addLast(e) 的作用吧,如果传入参数为空,抛出异常如果此时队列已满,就执行doubleCapacity();而这个方法就是把ArrayDeque扩容的,通过

...         int r = n - p; // number of elements to the right of p         int newCapacity = n << 1;//二进制,左移         ...         Object[] a = new Object[newCapacity];         System.arraycopy(elements, p, a, 0, r);         System.arraycopy(elements, 0, a, r, p);        ...

我们可知,满了就要扩容一倍的

说了这么多,我们重新回顾一下SerialExecutor

private static class SerialExecutor implements Executor {         final ArrayDeque<Runnable> mTasks = new ArrayDeque<Runnable>();         Runnable mActive;          public synchronized void execute(final Runnable r) {             mTasks.offer(new Runnable() {                 public void run() {                     try {                         r.run();                     } finally {                         scheduleNext();                     }                 }             });             if (mActive == null) {                 scheduleNext();             }         }          protected synchronized void scheduleNext() {             if ((mActive = mTasks.poll()) != null) {                 THREAD_POOL_EXECUTOR.execute(mActive);             }         }     }

分析一下它的执行过程第一次运行的时候,毫无疑问,局部变量mActive为null,执行scheduleNext()方法

protected synchronized void scheduleNext() {             if ((mActive = mTasks.poll()) != null) {                 THREAD_POOL_EXECUTOR.execute(mActive);             }         }

又看到了 THREAD_POOL_EXECUTOR

public static final Executor THREAD_POOL_EXECUTOR             = new ThreadPoolExecutor(CORE_POOL_SIZE, MAXIMUM_POOL_SIZE, KEEP_ALIVE,                     TimeUnit.SECONDS, sPoolWorkQueue, sThreadFactory);

THREAD_POOL_EXECUTOR 也是一个线程池,通过构造函数初始化了核心线程数,超时时长,所容纳的最大线程数,等一系类配置。在我的sdk版本好像对之前4.x做了优化,并没有固定写死,因为是这样的

private static final int CPU_COUNT = Runtime.getRuntime().availableProcessors();     private static final int CORE_POOL_SIZE = CPU_COUNT + 1;     private static final int MAXIMUM_POOL_SIZE = CPU_COUNT * 2 + 1;     private static final int KEEP_ALIVE = 1;

sDefaultExecutor 线程池内部维护一个任务队列(ArrayDeque),execute()方法,将Runnable放入队尾,第一次执行 走scheduleNext(),此时 mTasks.poll() 取出队首任务,不为空则传入THREAD_POOL_EXECUTOR进行执行。

4,执行过程回顾

再来看一下 AsyncTask.execute()的执行过程

@MainThread     public final AsyncTask<Params, Progress, Result> executeOnExecutor(Executor exec,             Params... params) {         if (mStatus != Status.PENDING) {             switch (mStatus) {                 case RUNNING:                     throw new IllegalStateException("Cannot execute task:"                             + " the task is already running.");                 case FINISHED:                     throw new IllegalStateException("Cannot execute task:"                             + " the task has already been executed "                             + "(a task can be executed only once)");             }         }          mStatus = Status.RUNNING; //设置当前执行状态         onPreExecute();  //熟悉这个onPreExecute()方法吗?         mWorker.mParams = params;//外部参数赋值给mWorker局部变量         //最主要的逻辑就在这个方法了,提交mFuture执行,封装了worker,         exec.execute(mFuture);         return this;     }

mFuture 是需要mWorker 作为参数,而mWorker的执行

mWorker = new WorkerRunnable<Params, Result>() {             public Result call() throws Exception {                 mTaskInvoked.set(true);                  //提升线程的优先级               Process.setThreadPriority(Process.THREAD_PRIORITY_BACKGROUND);                 //noinspection unchecked                 //看到了吗?这里的doInBackground 执行的就是你外部调用的 doInBackground()的逻辑。                 Result result = doInBackground(mParams);                 Binder.flushPendingCommands();                 return postResult(result);             }         };

拿到结果调用postResult(result)

private Result postResult(Result result) {         @SuppressWarnings("unchecked")         //getHandler()实际上就是 super(Looper.getMainLooper());,也就是Main 中的looper         Message message = getHandler().obtainMessage(MESSAGE_POST_RESULT,                 new AsyncTaskResult<Result>(this, result));         message.sendToTarget();         return result;     }

AsyncTaskResult就是一个简单的携带参数的对象。

看到Messager 肯定会有Handler,于是找到

private static class InternalHandler extends Handler {         public InternalHandler() {             super(Looper.getMainLooper());         }          @SuppressWarnings({"unchecked", "RawUseOfParameterizedType"})         @Override         public void handleMessage(Message msg) {             AsyncTaskResult<?> result = (AsyncTaskResult<?>) msg.obj;             switch (msg.what) {                 case MESSAGE_POST_RESULT:                     // There is only one result                     result.mTask.finish(result.mData[0]);                     break;                 case MESSAGE_POST_PROGRESS:                     result.mTask.onProgressUpdate(result.mData);                     break;             }         }     }

result.mTask.finish(result.mData[0]) 其实就是调用了AsyncTask类中的finish方法

private void finish(Result result) {         if (isCancelled()) {             onCancelled(result);         } else {             onPostExecute(result);         }         mStatus = Status.FINISHED;     }

调用了cancel()则执行onCancelled回调;正常执行的情况下调用我们的onPostExecute(result);最后将状态置为FINISHED。

再回到mFuture

mFuture = new FutureTask<Result>(mWorker) {             @Override             protected void done() {                 try {                     postResultIfNotInvoked(get());                 } catch (InterruptedException e) {                     android.util.Log.w(LOG_TAG, e);                 } catch (ExecutionException e) {                     throw new RuntimeException("An error occurred while executing doInBackground()",                             e.getCause());                 } catch (CancellationException e) {                     postResultIfNotInvoked(null);                 }             }         };

执行 postResultIfNotInvoked(get());

private void postResultIfNotInvoked(Result result) {         final boolean wasTaskInvoked = mTaskInvoked.get();         if (!wasTaskInvoked) {             postResult(result);         }     }

根据 wasTaskInvoked状态判断是否执行postResult(result);

在mWorker 中我们已经知道 wasTaskInvoked.set(true)

所以该方法不会执行。

至此,AsyncTask源码分析完毕,相信大家对AsyncTask有了更深的理解~~~

转载请注明出处: http://blog.csdn.net/yianemail/article/details/51611326

原文  http://www.androidchina.net/5048.html
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