本章主要記錄近期學習執行緒池的一些知識心得體會，記錄一個通讀原始碼的過程。

一、執行緒池的目的：

在面向物件程式設計中，建立和銷燬物件是很費時間的，因為建立一個物件要獲取記憶體資源或者其它更多資源。在Java中更是如此，虛擬機器將試圖跟蹤每一個物件，以便能夠在物件銷燬後進行垃圾回收。所以提高服務程式效率的一個手段就是儘可能減少建立和銷燬物件的次數，特別是一些很耗資源的物件建立和銷燬。如何利用已有物件來服務就是一個需要解決的關鍵問題，其實這就是一些"池化資源"技術產生的原因。

JVM會為每一個執行緒分配相應的Heap空間，虛擬機器中用-Xss：設定每個執行緒的堆疊大小(也就是說，在相同實體記憶體下，減小這個值能生成更多的執行緒)。當執行緒數量超過空間的限制時會丟擲OutOfMemory異常(OOM)。

二、執行緒池的組成部分：

1、執行緒池管理器(ThreadPoolManager)：用於建立並管理執行緒池；

2、工作執行緒(WorkThread)：執行緒池中的執行緒；

3、任務介面(Task)：每個任務必須實現的介面，以供工作執行緒排程任務的執行；

4、任務佇列(Queue)：用於存放沒有處理的任務，提供一種快取機制。

三、執行緒池實現過程分析：

示例一類常用的執行緒池：ThreadPoolExecutor(Spring可以通過ThreadPoolExecutorFactoryBean載入ThreadPoolExecutor，引數可通過Bean注入)

ThreadPoolExecutor主要引數包括：corePoolSize、 maximumPoolSize、keepAliveTime、Queue、ThreadFactory、RejectedExecutionHandler逐一對分析相關引數。

1、corePoolSize：執行緒池將new出的核心執行緒數。核心執行緒在處理完firstTask的之後，被執行緒池不會回收其資源，而是處於阻塞狀態，等待從任務佇列(Queue)中獲取下一個Task如此迴圈執行(但如果設定有allowCoreThreadTimeOut=true，則如果核心執行緒在等待keepAliveTime時間內沒有從佇列中獲取到新任務，也會被執行緒池回收)。相關原始碼如下：

            while (task != null || (task = getTask()) != null) {
                w.lock();
                // If pool is stopping, ensure thread is interrupted;
                // if not, ensure thread is not interrupted.  This
                // requires a recheck in second case to deal with
                // shutdownNow race while clearing interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    beforeExecute(wt, task);
                    Throwable thrown = null;
                    try {
                        task.run();
                    } catch (RuntimeException x) {
                        thrown = x; throw x;
                    } catch (Error x) {
                        thrown = x; throw x;
                    } catch (Throwable x) {
                        thrown = x; throw new Error(x);
                    } finally {
                        afterExecute(task, thrown);
                    }
                } finally {
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
 

    private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?

        retry:
        for (;;) {
            int c = ctl.get();
            int rs = runStateOf(c);

            // Check if queue empty only if necessary.
            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
                decrementWorkerCount();
                return null;
            }

            boolean timed;      // Are workers subject to culling?

            for (;;) {
                int wc = workerCountOf(c);
                timed = allowCoreThreadTimeOut || wc > corePoolSize;

                if (wc <= maximumPoolSize && ! (timedOut && timed))
                    break;
                if (compareAndDecrementWorkerCount(c))
                    return null;
                c = ctl.get();  // Re-read ctl
                if (runStateOf(c) != rs)
                    continue retry;
                // else CAS failed due to workerCount change; retry inner loop
            }

            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }

    public void execute(Runnable command) {
        if (command == null)
            throw new NullPointerException();
        /*
         * Proceed in 3 steps:
         *
         * 1. If fewer than corePoolSize threads are running, try to
         * start a new thread with the given command as its first
         * task.  The call to addWorker atomically checks runState and
         * workerCount, and so prevents false alarms that would add
         * threads when it shouldn't, by returning false.
         *
         * 2. If a task can be successfully queued, then we still need
         * to double-check whether we should have added a thread
         * (because existing ones died since last checking) or that
         * the pool shut down since entry into this method. So we
         * recheck state and if necessary roll back the enqueuing if
         * stopped, or start a new thread if there are none.
         *
         * 3. If we cannot queue task, then we try to add a new
         * thread.  If it fails, we know we are shut down or saturated
         * and so reject the task.
         */
        int c = ctl.get();
        if (workerCountOf(c) < corePoolSize) {
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
        if (isRunning(c) && workQueue.offer(command)) {
            int recheck = ctl.get();
            if (! isRunning(recheck) && remove(command))
                reject(command);
            else if (workerCountOf(recheck) == 0)
                addWorker(null, false);
        }
        else if (!addWorker(command, false))
            reject(command);
    }

4、BlockingQueue：存放任務的阻塞佇列，一般沒有特殊要求只用兩種，LinkedBlockingQueue 連結串列阻塞佇列與SynchronousQueue 同步阻塞佇列。當期望的佇列深度為0時，則使用後者，否則為前者指定一個佇列大小(預設為Integer.MAX_VALUE作為queueCapacity)作為儲存佇列，除coreThread的firstTask、任務加入佇列失敗這兩種情況，其他的執行緒均從佇列中獲取任務(先進先出)，新新增的任務如果不能被立馬執行，也會被加入到佇列中。其中對同步阻塞佇列的解釋如下：

 /**
* A {@linkplain BlockingQueue blocking queue} in which each insert
 * operation must wait for a corresponding remove operation by another
 * thread, and vice versa.  A synchronous queue does not have any
 * internal capacity, not even a capacity of one.  You cannot
 * <tt>peek</tt> at a synchronous queue because an element is only
 * present when you try to remove it; you cannot insert an element
 * (using any method) unless another thread is trying to remove it;
 * you cannot iterate as there is nothing to iterate.  The
 * <em>head</em> of the queue is the element that the first queued
 * inserting thread is trying to add to the queue; if there is no such
 * queued thread then no element is available for removal and
 * <tt>poll()</tt> will return <tt>null</tt>.  For purposes of other
 * <tt>Collection</tt> methods (for example <tt>contains</tt>), a
 * <tt>SynchronousQueue</tt> acts as an empty collection.  This queue
 * does not permit <tt>null</tt> elements.
*/

    static class DefaultThreadFactory implements ThreadFactory {
        private static final AtomicInteger poolNumber = new AtomicInteger(1);
        private final ThreadGroup group;
        private final AtomicInteger threadNumber = new AtomicInteger(1);
        private final String namePrefix;

        DefaultThreadFactory() {
            SecurityManager s = System.getSecurityManager();
            group = (s != null) ? s.getThreadGroup() :
                                  Thread.currentThread().getThreadGroup();
            namePrefix = "pool-" +
                          poolNumber.getAndIncrement() +
                         "-thread-";
        }

        public Thread newThread(Runnable r) {
            Thread t = new Thread(group, r,
                                  namePrefix + threadNumber.getAndIncrement(),
                                  0);
            if (t.isDaemon())
                t.setDaemon(false);
            if (t.getPriority() != Thread.NORM_PRIORITY)
                t.setPriority(Thread.NORM_PRIORITY);
            return t;
        }
    }

    public static class AbortPolicy implements RejectedExecutionHandler {
        /**
         * Creates an {@code AbortPolicy}.
         */
        public AbortPolicy() { }

        /**
         * Always throws RejectedExecutionException.
         *
         * @param r the runnable task requested to be executed
         * @param e the executor attempting to execute this task
         * @throws RejectedExecutionException always.
         */
        public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
            throw new RejectedExecutionException("Task " + r.toString() +
                                                 " rejected from " +
                                                 e.toString());
        }
    }

1、執行緒池的大小及狀態用一個AtomicInteger變數進行控制：

    private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
    private static final int COUNT_BITS = Integer.SIZE - 3;
    private static final int CAPACITY   = (1 << COUNT_BITS) - 1;

    // runState is stored in the high-order bits
    private static final int RUNNING    = -1 << COUNT_BITS;
    private static final int SHUTDOWN   =  0 << COUNT_BITS;
    private static final int STOP       =  1 << COUNT_BITS;
    private static final int TIDYING    =  2 << COUNT_BITS;
    private static final int TERMINATED =  3 << COUNT_BITS;

    // Packing and unpacking ctl
    private static int runStateOf(int c)     { return c & ~CAPACITY; }
    private static int workerCountOf(int c)  { return c & CAPACITY; }
    private static int ctlOf(int rs, int wc) { return rs | wc; }

2、執行緒池包括5種狀態：Running、ShutDown、Stop、Tidying、Terminated

RUNNING:  Accept new tasks and process queued tasks

SHUTDOWN: Don't accept new tasks, but process queued tasks

STOP:     Don't accept new tasks, don't process queued tasks,and interrupt in-progress tasks

TIDYING:  All tasks have terminated, workerCount is zero,the thread transitioning to state TIDYING will run the terminated() hook method

TERMINATED: terminated() has completed

3、執行緒池鎖 ReentrantLock mainLock = new ReentrantLock();

五、個人總結

線上程池的學習過程中，在瞭解原始碼的同時，也學到了相當多的優化程式設計小技巧，如：

if (isRunning(c) && workQueue.offer(command))

在判斷中執行邏輯。通讀原始碼的收益還是很可觀的。