几个概念区分：Executor、ExecutorService、Executors、ThreadPoolExecutor

Published: Creative Commons Licence

概览

这几个概念很容易弄混，这里简单从概念层面区分一下。

一句话概括：

  • Executor：任务（Runnable）执行器，调用者只需要提交任务，而无需关心任务执行细节。

  • ExecutorService：扩展了Executor接口，增加了诸如任务生命周期管理、执行有返回值的任务（Callable）、批量执行任务等方法。

  • Executors：提供了创建Executor、ExecutorService、ThreadFactory、Callable等的工厂方法和一些其他工具方法。

  • ThreadPoolExecutor：ExecutorService的具体线程池实现。

关系图示：

详细分析

主要参考了JDK里的注释，不得不说写得真的好，值得多读几遍，当然能读源码就更好了。

Executor

An object that executes submitted Runnable tasks. This interface provides a way of decoupling task submission from the mechanics of how each task will be run, including details of thread use, scheduling, etc. An Executor is normally used instead of explicitly creating threads. For example, rather than invoking new Thread(new(RunnableTask())).start() for each of a set of tasks, you might use:

   Executor executor = anExecutor;
   executor.execute(new RunnableTask1());
   executor.execute(new RunnableTask2());
   ...

However, the Executor interface does not strictly require that execution be asynchronous. In the simplest case, an executor can run the submitted task immediately in the caller's thread:

class DirectExecutor implements Executor {
   public void execute(Runnable r) {
     r.run();
   }
}

More typically, tasks are executed in some thread other than the caller's thread. The executor below spawns a new thread for each task.

class ThreadPerTaskExecutor implements Executor {
   public void execute(Runnable r) {
     new Thread(r).start();
   }
}

The Executor implementations provided in this package implement ExecutorService, which is a more extensive interface.

The ThreadPoolExecutor class provides an extensible thread pool implementation.

The Executors class provides convenient factory methods for these Executors.

ExecutorService

An Executor that provides methods to manage termination and methods that can produce a Future for tracking progress of one or more asynchronous tasks.

An ExecutorService can be shut down, which will cause it to reject new tasks. Two different methods are provided for shutting down an ExecutorService. The shutdown method will allow previously submitted tasks to execute before terminating, while the shutdownNow method prevents waiting tasks from starting and attempts to stop currently executing tasks. Upon termination, an executor has no tasks actively executing, no tasks awaiting execution, and no new tasks can be submitted. An unused ExecutorService should be shut down to allow reclamation of its resources.

Method submit extends base method Executor.execute(Runnable) by creating and returning a Future that can be used to cancel execution and/or wait for completion. Methods invokeAny and invokeAll perform the most commonly useful forms of bulk execution, executing a collection of tasks and then waiting for at least one, or all, to complete. (Class ExecutorCompletionService can be used to write customized variants of these methods.)

The Executors class provides factory methods for the executor services provided in this package.

Memory consistency effects: Actions in a thread prior to the submission of a Runnable or Callable task to an ExecutorService happen-before any actions taken by that task, which in turn happen-before the result is retrieved via Future.get().

JDK还很贴心的给了两个实例：

1.一个多线程的网络服务器：

Here is a sketch of a network service in which threads in a thread pool service incoming requests. It uses the preconfigured Executors.newFixedThreadPool factory method:

class NetworkService implements Runnable {
   private final ServerSocket serverSocket;
   private final ExecutorService pool;

   public NetworkService(int port, int poolSize) throws IOException {
     serverSocket = new ServerSocket(port);
     pool = Executors.newFixedThreadPool(poolSize);
   }

   public void run() { // run the service
     try {
       for (;;) {
         pool.execute(new Handler(serverSocket.accept()));
       }
     } catch (IOException ex) {
       pool.shutdown();
     }
   }
}

class Handler implements Runnable {
   private final Socket socket;

   Handler(Socket socket) { this.socket = socket; }

   public void run() {
     // read and service request on socket
   }
}

2.终止ExecutorService

The following method shuts down an ExecutorService in two phases, first by calling shutdown to reject incoming tasks, and then calling shutdownNow, if necessary, to cancel any lingering tasks:

void shutdownAndAwaitTermination(ExecutorService pool) {
   pool.shutdown(); // Disable new tasks from being submitted
   try {
     // Wait a while for existing tasks to terminate
     if (!pool.awaitTermination(60, TimeUnit.SECONDS)) {
       pool.shutdownNow(); // Cancel currently executing tasks
       // Wait a while for tasks to respond to being cancelled
       if (!pool.awaitTermination(60, TimeUnit.SECONDS))
           System.err.println("Pool did not terminate");
     }
   } catch (InterruptedException ie) {
     // (Re-)Cancel if current thread also interrupted
     pool.shutdownNow();
     // Preserve interrupt status
     Thread.currentThread().interrupt();
   }
}

Executors

Factory and utility methods for Executor, ExecutorService, ScheduledExecutorService, ThreadFactory, and Callable classes defined in this package. This class supports the following kinds of methods:

Methods that create and return an ExecutorService set up with commonly useful configuration settings.

Methods that create and return a ScheduledExecutorService set up with commonly useful configuration settings.

Methods that create and return a "wrapped" ExecutorService, that disables reconfiguration by making implementation-specific methods inaccessible.

Methods that create and return a ThreadFactory that sets newly created threads to a known state.

Methods that create and return a Callable out of other closure-like forms, so they can be used in execution methods requiring Callable.

ThreadPoolExecutor

An ExecutorService that executes each submitted task using one of possibly several pooled threads, normally configured using Executors factory methods.

Thread pools address two different problems: they usually provide improved performance when executing large numbers of asynchronous tasks, due to reduced per-task invocation overhead, and they provide a means of bounding and managing the resources, including threads, consumed when executing a collection of tasks. Each ThreadPoolExecutor also maintains some basic statistics, such as the number of completed tasks.

To be useful across a wide range of contexts, this class provides many adjustable parameters and extensibility hooks. However, programmers are urged to use the more convenient Executors factory methods Executors.newCachedThreadPool (unbounded thread pool, with automatic thread reclamation), Executors.newFixedThreadPool (fixed size thread pool) and Executors.newSingleThreadExecutor (single background thread), that preconfigure settings for the most common usage scenarios. Otherwise, use the following guide when manually configuring and tuning this class:

  • Core and maximum pool sizes

A ThreadPoolExecutor will automatically adjust the pool size (see getPoolSize) according to the bounds set by corePoolSize (see getCorePoolSize) and maximumPoolSize (see getMaximumPoolSize). When a new task is submitted in method execute(Runnable), and fewer than corePoolSize threads are running, a new thread is created to handle the request, even if other worker threads are idle. If there are more than corePoolSize but less than maximumPoolSize threads running, a new thread will be created only if the queue is full. By setting corePoolSize and maximumPoolSize the same, you create a fixed-size thread pool. By setting maximumPoolSize to an essentially unbounded value such as Integer.MAX_VALUE, you allow the pool to accommodate an arbitrary number of concurrent tasks. Most typically, core and maximum pool sizes are set only upon construction, but they may also be changed dynamically using setCorePoolSize and setMaximumPoolSize.

  • On-demand construction

By default, even core threads are initially created and started only when new tasks arrive, but this can be overridden dynamically using method prestartCoreThread or prestartAllCoreThreads. You probably want to prestart threads if you construct the pool with a non-empty queue.

  • Creating new threads

New threads are created using a ThreadFactory. If not otherwise specified, a Executors.defaultThreadFactory is used, that creates threads to all be in the same ThreadGroup and with the same NORM_PRIORITY priority and non-daemon status. By supplying a different ThreadFactory, you can alter the thread's name, thread group, priority, daemon status, etc. If a ThreadFactory fails to create a thread when asked by returning null from newThread, the executor will continue, but might not be able to execute any tasks. Threads should possess the "modifyThread" RuntimePermission. If worker threads or other threads using the pool do not possess this permission, service may be degraded: configuration changes may not take effect in a timely manner, and a shutdown pool may remain in a state in which termination is possible but not completed.

  • Keep-alive times

If the pool currently has more than corePoolSize threads, excess threads will be terminated if they have been idle for more than the keepAliveTime (see getKeepAliveTime(TimeUnit)). This provides a means of reducing resource consumption when the pool is not being actively used. If the pool becomes more active later, new threads will be constructed. This parameter can also be changed dynamically using method setKeepAliveTime(long, TimeUnit). Using a value of Long.MAX_VALUE TimeUnit.NANOSECONDS effectively disables idle threads from ever terminating prior to shut down. By default, the keep-alive policy applies only when there are more than corePoolSize threads. But method allowCoreThreadTimeOut(boolean) can be used to apply this time-out policy to core threads as well, so long as the keepAliveTime value is non-zero.

  • Queuing

Any BlockingQueue may be used to transfer and hold submitted tasks. The use of this queue interacts with pool sizing:

If fewer than corePoolSize threads are running, the Executor always prefers adding a new thread rather than queuing.

If corePoolSize or more threads are running, the Executor always prefers queuing a request rather than adding a new thread.

If a request cannot be queued, a new thread is created unless this would exceed maximumPoolSize, in which case, the task will be rejected.

There are three general strategies for queuing:

  1. Direct handoffs. A good default choice for a work queue is a SynchronousQueue that hands off tasks to threads without otherwise holding them. Here, an attempt to queue a task will fail if no threads are immediately available to run it, so a new thread will be constructed. This policy avoids lockups when handling sets of requests that might have internal dependencies. Direct handoffs generally require unbounded maximumPoolSizes to avoid rejection of new submitted tasks. This in turn admits the possibility of unbounded thread growth when commands continue to arrive on average faster than they can be processed.

  2. Unbounded queues. Using an unbounded queue (for example a LinkedBlockingQueue without a predefined capacity) will cause new tasks to wait in the queue when all corePoolSize threads are busy. Thus, no more than corePoolSize threads will ever be created. (And the value of the maximumPoolSize therefore doesn't have any effect.) This may be appropriate when each task is completely independent of others, so tasks cannot affect each others execution; for example, in a web page server. While this style of queuing can be useful in smoothing out transient bursts of requests, it admits the possibility of unbounded work queue growth when commands continue to arrive on average faster than they can be processed.

  3. Bounded queues. A bounded queue (for example, an ArrayBlockingQueue) helps prevent resource exhaustion when used with finite maximumPoolSizes, but can be more difficult to tune and control. Queue sizes and maximum pool sizes may be traded off for each other: Using large queues and small pools minimizes CPU usage, OS resources, and context-switching overhead, but can lead to artificially low throughput. If tasks frequently block (for example if they are I/O bound), a system may be able to schedule time for more threads than you otherwise allow. Use of small queues generally requires larger pool sizes, which keeps CPUs busier but may encounter unacceptable scheduling overhead, which also decreases throughput.

  • Rejected tasks

New tasks submitted in method execute(Runnable) will be rejected when the Executor has been shut down, and also when the Executor uses finite bounds for both maximum threads and work queue capacity, and is saturated. In either case, the execute method invokes the RejectedExecutionHandler.rejectedExecution(Runnable, ThreadPoolExecutor) method of its RejectedExecutionHandler. Four predefined handler policies are provided:

  1. In the default ThreadPoolExecutor.AbortPolicy, the handler throws a runtime RejectedExecutionException upon rejection.

  2. In ThreadPoolExecutor.CallerRunsPolicy, the thread that invokes execute itself runs the task. This provides a simple feedback control mechanism that will slow down the rate that new tasks are submitted.

  3. In ThreadPoolExecutor.DiscardPolicy, a task that cannot be executed is simply dropped.

  4. In ThreadPoolExecutor.DiscardOldestPolicy, if the executor is not shut down, the task at the head of the work queue is dropped, and then execution is retried (which can fail again, causing this to be repeated.)

It is possible to define and use other kinds of RejectedExecutionHandler classes. Doing so requires some care especially when policies are designed to work only under particular capacity or queuing policies.

  • Hook methods

This class provides protected overridable beforeExecute(Thread, Runnable) and afterExecute(Runnable, Throwable) methods that are called before and after execution of each task. These can be used to manipulate the execution environment; for example, reinitializing ThreadLocals, gathering statistics, or adding log entries. Additionally, method terminated can be overridden to perform any special processing that needs to be done once the Executor has fully terminated.

If hook or callback methods throw exceptions, internal worker threads may in turn fail and abruptly terminate.

JDK里也给了一个扩展Hook Methods的例子：

Extension example. Most extensions of this class override one or more of the protected hook methods. For example, here is a subclass that adds a simple pause/resume feature:

class PausableThreadPoolExecutor extends ThreadPoolExecutor {
   private boolean isPaused;
   private ReentrantLock pauseLock = new ReentrantLock();
   private Condition unpaused = pauseLock.newCondition();

   public PausableThreadPoolExecutor(...) { super(...); }

   protected void beforeExecute(Thread t, Runnable r) {
     super.beforeExecute(t, r);
     pauseLock.lock();
     try {
       while (isPaused) unpaused.await();
     } catch (InterruptedException ie) {
       t.interrupt();
     } finally {
       pauseLock.unlock();
     }
   }

   public void pause() {
     pauseLock.lock();
     try {
       isPaused = true;
     } finally {
       pauseLock.unlock();
     }
   }

   public void resume() {
     pauseLock.lock();
     try {
       isPaused = false;
       unpaused.signalAll();
     } finally {
       pauseLock.unlock();
     }
   }
}
  • Queue maintenance

Method getQueue() allows access to the work queue for purposes of monitoring and debugging. Use of this method for any other purpose is strongly discouraged. Two supplied methods, remove(Runnable) and purge are available to assist in storage reclamation when large numbers of queued tasks become cancelled.

  • Finalization

A pool that is no longer referenced in a program AND has no remaining threads will be shutdown automatically. If you would like to ensure that unreferenced pools are reclaimed even if users forget to call shutdown, then you must arrange that unused threads eventually die, by setting appropriate keep-alive times, using a lower bound of zero core threads and/or setting allowCoreThreadTimeOut(boolean).