标签:功能 imp 对象 schedule processor 接口 依次 分享 unit
Executor框架是指java 5中引入的一系列并发库中与executor相关的一些功能类,其中包括线程池,Executor,Executors,ExecutorService,CompletionService,Future,Callable等。
他们的关系为:
并发编程的一种编程方式是把任务拆分为一些列的小任务,即Runnable,然后在提交给一个Executor执行,Executor.execute(Runnalbe) 。Executor在执行时使用内部的线程池完成操作。
Executors类,提供了一系列工厂方法用于创先线程池,返回的线程池都实现了ExecutorService接口。
public static ExecutorService newFixedThreadPool(int nThreads)
创建固定数目线程的线程池。
public static ExecutorService newCachedThreadPool()
创建一个可缓存的线程池,调用execute 将重用以前构造的线程(如果线程可用)。如果现有线程没有可用的,则创建一个新线程并添加到池中。终止并从缓存中移除那些已有 60 秒钟未被使用的线程。
public static ExecutorService newSingleThreadExecutor()
创建一个单线程化的Executor。
public static ScheduledExecutorService newScheduledThreadPool(int corePoolSize)
创建一个支持定时及周期性的任务执行的线程池,多数情况下可用来替代Timer类。
Executor executor = Executors.newFixedThreadPool(10); Runnable task = new Runnable() { @Override public void run() { System.out.println("task over"); } }; executor.execute(task); executor = Executors.newScheduledThreadPool(10); ScheduledExecutorService scheduler = (ScheduledExecutorService) executor; scheduler.scheduleAtFixedRate(task, 10, 10, TimeUnit.SECONDS);
ExecutorService扩展了Executor并添加了一些生命周期管理的方法。一个Executor的生命周期有三种状态,运行 ,关闭 ,终止。Executor创建时处于运行状态。当调用ExecutorService.shutdown()后,处于关闭状态,isShutdown()方法返回true。这时,不应该再想Executor中添加任务,所有已添加的任务执行完毕后,Executor处于终止状态,isTerminated()返回true。
如果Executor处于关闭状态,往Executor提交任务会抛出unchecked exception RejectedExecutionException。
ExecutorService executorService = (ExecutorService) executor; while (!executorService.isShutdown()) { try { executorService.execute(task); } catch (RejectedExecutionException ignored) { } } executorService.shutdown();
Future<V>代表一个异步执行的操作,通过get()方法可以获得操作的结果,如果异步操作还没有完成,则,get()会使当前线程阻塞。FutureTask<V>实现了Future<V>和Runable<V>。Callable代表一个有返回值得操作。
Callable<Integer> func = new Callable<Integer>(){ public Integer call() throws Exception { System.out.println("inside callable"); Thread.sleep(1000); return new Integer(8); } }; FutureTask<Integer> futureTask = new FutureTask<Integer>(func); Thread newThread = new Thread(futureTask); newThread.start(); try { System.out.println("blocking here"); Integer result = futureTask.get(); System.out.println(result); } catch (InterruptedException ignored) { } catch (ExecutionException ignored) { } ExecutoreService提供了submit()方法,传递一个Callable,或Runnable,返回Future。如果Executor后台线程池还没有完成Callable的计算,这调用返回Future对象的get()方法,会阻塞直到计算完成。 例子:并行计算数组的和。 Java代码 收藏代码 package executorservice; import java.util.ArrayList; import java.util.List; import java.util.concurrent.Callable; import java.util.concurrent.ExecutionException; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.util.concurrent.Future; import java.util.concurrent.FutureTask; public class ConcurrentCalculator { private ExecutorService exec; private int cpuCoreNumber; private List<Future<Long>> tasks = new ArrayList<Future<Long>>(); // 内部类 class SumCalculator implements Callable<Long> { private int[] numbers; private int start; private int end; public SumCalculator(final int[] numbers, int start, int end) { this.numbers = numbers; this.start = start; this.end = end; } public Long call() throws Exception { Long sum = 0l; for (int i = start; i < end; i++) { sum += numbers[i]; } return sum; } } public ConcurrentCalculator() { cpuCoreNumber = Runtime.getRuntime().availableProcessors(); exec = Executors.newFixedThreadPool(cpuCoreNumber); } public Long sum(final int[] numbers) { // 根据CPU核心个数拆分任务,创建FutureTask并提交到Executor for (int i = 0; i < cpuCoreNumber; i++) { int increment = numbers.length / cpuCoreNumber + 1; int start = increment * i; int end = increment * i + increment; if (end > numbers.length) end = numbers.length; SumCalculator subCalc = new SumCalculator(numbers, start, end); FutureTask<Long> task = new FutureTask<Long>(subCalc); tasks.add(task); if (!exec.isShutdown()) { exec.submit(task); } } return getResult(); } /** * 迭代每个只任务,获得部分和,相加返回 * * @return */ public Long getResult() { Long result = 0l; for (Future<Long> task : tasks) { try { // 如果计算未完成则阻塞 Long subSum = task.get(); result += subSum; } catch (InterruptedException e) { e.printStackTrace(); } catch (ExecutionException e) { e.printStackTrace(); } } return result; } public void close() { exec.shutdown(); } }
Main
int[] numbers = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 10, 11 }; ConcurrentCalculator calc = new ConcurrentCalculator(); Long sum = calc.sum(numbers); System.out.println(sum); calc.close();
在刚在的例子中,getResult()方法的实现过程中,迭代了FutureTask的数组,如果任务还没有完成则当前线程会阻塞,如果我们希望任意字任务完成后就把其结果加到result中,而不用依次等待每个任务完成,可以使CompletionService。生产者submit()执行的任务。使用者take()已完成的任务,并按照完成这些任务的顺序处理它们的结果 。也就是调用CompletionService的take方法是,会返回按完成顺序放回任务的结果,CompletionService内部维护了一个阻塞队列BlockingQueue,如果没有任务完成,take()方法也会阻塞。修改刚才的例子使用CompletionService:
public class ConcurrentCalculator2 { private ExecutorService exec; private CompletionService<Long> completionService; private int cpuCoreNumber; // 内部类 class SumCalculator implements Callable<Long> { ...... } public ConcurrentCalculator2() { cpuCoreNumber = Runtime.getRuntime().availableProcessors(); exec = Executors.newFixedThreadPool(cpuCoreNumber); completionService = new ExecutorCompletionService<Long>(exec); } public Long sum(final int[] numbers) { // 根据CPU核心个数拆分任务,创建FutureTask并提交到Executor for (int i = 0; i < cpuCoreNumber; i++) { int increment = numbers.length / cpuCoreNumber + 1; int start = increment * i; int end = increment * i + increment; if (end > numbers.length) end = numbers.length; SumCalculator subCalc = new SumCalculator(numbers, start, end); if (!exec.isShutdown()) { completionService.submit(subCalc); } } return getResult(); } /** * 迭代每个只任务,获得部分和,相加返回 * * @return */ public Long getResult() { Long result = 0l; for (int i = 0; i < cpuCoreNumber; i++) { try { Long subSum = completionService.take().get(); result += subSum; } catch (InterruptedException e) { e.printStackTrace(); } catch (ExecutionException e) { e.printStackTrace(); } } return result; } public void close() { exec.shutdown(); } }
1.可用于替代timer做定时任务
2.改造项目中原先运行慢的代码,切割成多个块,在多个线程中运行,最后结果再整合在一起
3.代码异步执行,先返回主要部分
等等
标签:功能 imp 对象 schedule processor 接口 依次 分享 unit
原文地址:http://www.cnblogs.com/Mr-Rocker/p/7871986.html