執行一個異步任務你還只是以下new Thread嗎?數據庫
new Thread(new Runnable() { @Override public void run() { // TODO Auto-generated method stub } }).start();
那你就out太多了,new Thread的弊端以下:緩存
相比new Thread,Java提供的四種線程池的好處在於:安全
Java經過Executors提供四種線程池,分別爲:併發
建立一個可緩存線程池,若是線程池長度超過處理須要,可靈活回收空閒線程,若無可回收,則新建線程。示例代碼以下:異步
ExecutorService cachedThreadPool = Executors.newCachedThreadPool(); for (int i = 0; i < 10; i++) { final int index = i; try { Thread.sleep(index * 1000); } catch (InterruptedException e) { e.printStackTrace(); } cachedThreadPool.execute(new Runnable() { @Override public void run() { System.out.println(index); } }); }
線程池爲無限大,當執行第二個任務時第一個任務已經完成,會複用執行第一個任務的線程,而不用每次新建線程。ide
建立一個定長線程池,可控制線程最大併發數,超出的線程會在隊列中等待。示例代碼以下:函數
ExecutorService fixedThreadPool = Executors.newFixedThreadPool(3); for (int i = 0; i < 10; i++) { final int index = i; fixedThreadPool.execute(new Runnable() { @Override public void run() { try { System.out.println(index); Thread.sleep(2000); } catch (InterruptedException e) { // TODO Auto-generated catch block e.printStackTrace(); } } }); }
由於線程池大小爲3,每一個任務輸出index後sleep 2秒,因此每兩秒打印3個數字。 定長線程池的大小最好根據系統資源進行設置。如Runtime.getRuntime().availableProcessors()。可參考PreloadDataCache。性能
建立一個定長線程池,支持定時及週期性任務執行。延遲執行示例代碼以下:this
ScheduledExecutorService scheduledThreadPool = Executors.newScheduledThreadPool(5); scheduledThreadPool.schedule(new Runnable() { @Override public void run() { System.out.println("delay 3 seconds"); } }, 3, TimeUnit.SECONDS);
表示延遲3秒執行。線程
按期執行示例代碼以下:
scheduledThreadPool.scheduleAtFixedRate(new Runnable() { @Override public void run() { System.out.println("delay 1 seconds, and excute every 3 seconds"); } }, 1, 3, TimeUnit.SECONDS);
表示延遲1秒後每3秒執行一次。 ScheduledExecutorService比Timer更安全,功能更強大,後面會有一篇單獨進行對比。
建立一個單線程化的線程池,它只會用惟一的工做線程來執行任務,保證全部任務按照指定順序(FIFO, LIFO, 優先級)執行。示例代碼以下:
ExecutorService singleThreadExecutor = Executors.newSingleThreadExecutor(); for (int i = 0; i < 10; i++) { final int index = i; singleThreadExecutor.execute(new Runnable() { @Override public void run() { try { System.out.println(index); Thread.sleep(2000); } catch (InterruptedException e) { // TODO Auto-generated catch block e.printStackTrace(); } } }); }
結果依次輸出,至關於順序執行各個任務。 現行大多數GUI程序都是單線程的。Android中單線程可用於數據庫操做,文件操做,應用批量安裝,應用批量刪除等不適合併發但可能IO阻塞性及影響UI線程響應的操做。
當使用ExecutorService啓動了多個Callable後,每一個Callable會產生一個Future,咱們須要將多個Future存入一個線性表,用於以後處理數據。固然,還有更復雜的狀況,有5個生產者線程,每一個生產者線程都會建立任務,全部任務的Future都存放到同一個線性表中。而後遍歷線性表,經過調用future.get(0, TimeUnit.SECONDS)不斷嘗試獲取完成結果,直到獲取到全部的結果。以下
public class ExecutorServiceTest { static class Task implements Callable<String>{ private int i; public Task(int i){ this.i = i; } @Override public String call() throws Exception { Thread.sleep(10000); return Thread.currentThread().getName() + "執行完任務:" + i; } } public static void main(String[] args){ testUseFuture(); } private static void testUseFuture(){ int numThread = 5; ExecutorService executor = Executors.newFixedThreadPool(numThread); List<Future<String>> futureList = new ArrayList<Future<String>>(); for(int i = 0;i<numThread;i++ ){ Future<String> future = executor.submit(new ExecutorServiceTest.Task(i)); futureList.add(future); } int i=0; while(numThread > 0){ i++; for(Future<String> future : futureList){ String result = null; try { result = future.get(0, TimeUnit.SECONDS); } catch (InterruptedException e) { e.printStackTrace(); } catch (ExecutionException e) { e.printStackTrace(); } catch (TimeoutException e) { //超時異常直接忽略 } if(null != result){ futureList.remove(future); numThread--; System.out.println(result); //此處必須break,不然會拋出併發修改異常。(也能夠經過將futureList聲明爲CopyOnWriteArrayList類型解決) break; } } } System.out.println("共"+i+"次遍歷任務列表"); } }
執行後輸出
pool-1-thread-2執行完任務:1 pool-1-thread-3執行完任務:2 pool-1-thread-4執行完任務:3 pool-1-thread-1執行完任務:0 pool-1-thread-5執行完任務:4 共1265559次遍歷任務列表
根據輸出咱們能夠看到,爲了獲取到5個任務的執行結果,程序一共遍歷了1265559次任務列表,這不是一種很是好的辦法。
CompletionService正是爲此而存在,它是一個更高級的ExecutorService,它自己自帶一個線程安全的線性表,無需用戶額外建立。它提供了3種方法從線性表中取出結果:poll()是非阻塞的,若目前無結果,返回一個null,線程繼續運行不阻塞;poll(long timeout, TimeUnit unit)是阻塞的,若目前無結果,則會等待一段時間;**take()**是阻塞的,若當前無結果,則線程阻塞,直到產生一個結果,被取出返回,線程才繼續運行。 修改後的程序以下:
public class CompletionServiceTest { static class Task implements Callable<String>{ private int i; public Task(int i){ this.i = i; } @Override public String call() throws Exception { Thread.sleep(10000); return Thread.currentThread().getName() + "執行完任務:" + i; } } public static void main(String[] args) throws InterruptedException, ExecutionException{ testExecutorCompletionService(); } private static void testExecutorCompletionService() throws InterruptedException, ExecutionException{ int numThread = 5; ExecutorService executor = Executors.newFixedThreadPool(numThread); CompletionService<String> completionService = new ExecutorCompletionService<String>(executor); for(int i = 0;i<numThread;i++ ){ completionService.submit(new CompletionServiceTest.Task(i)); } for(int i = 0;i<numThread;i++ ){ System.out.println(completionService.take().get()); System.out.println("第"+(i+1)+"次獲取結果"); } } }
使用completionService.take()阻塞方法來獲取已完成Future<>,不須要一直遍歷查詢。
pool-1-thread-2執行完任務:1 第1次獲取結果 pool-1-thread-3執行完任務:2 第2次獲取結果 pool-1-thread-1執行完任務:0 第3次獲取結果 pool-1-thread-5執行完任務:4 第4次獲取結果 pool-1-thread-4執行完任務:3 第5次獲取結果
CompletionService整合了Executor和BlockingQueue的功能。你能夠將Callable任務提交給它去執行,而後使用相似於隊列中的take和poll方法,在結果完整可用時得到這個結果,像一個打包的Future。ExecutorCompletionService是實現CompletionService接口的一個類,並將計算任務委託給一個Executor。
ExecutorCompletionService的實現至關直觀。它在構造函數中建立一個BlockingQueue,用它去保持完成的結果。計算完成時會調用FutureTask中的done方法。當提交一個任務後,首先把這個任務包裝爲一個QueueingFuture,它是FutureTask的一個子類,而後覆寫done方法,將結果置入BlockingQueue中,take和poll方法委託給了BlockingQueue,它會在結果不可用時阻塞。
public class ExecutorCompletionService<V> implements CompletionService<V> { private final Executor executor; private final AbstractExecutorService aes; private final BlockingQueue<Future<V>> completionQueue; /** * FutureTask extension to enqueue upon completion */ private class QueueingFuture extends FutureTask<Void> { QueueingFuture(RunnableFuture<V> task) { super(task, null); this.task = task; } protected void done() { completionQueue.add(task); } private final Future<V> task; } private RunnableFuture<V> newTaskFor(Callable<V> task) { if (aes == null) return new FutureTask<V>(task); else return aes.newTaskFor(task); } private RunnableFuture<V> newTaskFor(Runnable task, V result) { if (aes == null) return new FutureTask<V>(task, result); else return aes.newTaskFor(task, result); } /** * Creates an ExecutorCompletionService using the supplied * executor for base task execution and a * {@link LinkedBlockingQueue} as a completion queue. * * @param executor the executor to use * @throws NullPointerException if executor is <tt>null</tt> */ public ExecutorCompletionService(Executor executor) { if (executor == null) throw new NullPointerException(); this.executor = executor; this.aes = (executor instanceof AbstractExecutorService) ? (AbstractExecutorService) executor : null; this.completionQueue = new LinkedBlockingQueue<Future<V>>(); } /** * Creates an ExecutorCompletionService using the supplied * executor for base task execution and the supplied queue as its * completion queue. * * @param executor the executor to use * @param completionQueue the queue to use as the completion queue * normally one dedicated for use by this service * @throws NullPointerException if executor or completionQueue are <tt>null</tt> */ public ExecutorCompletionService(Executor executor, BlockingQueue<Future<V>> completionQueue) { if (executor == null || completionQueue == null) throw new NullPointerException(); this.executor = executor; this.aes = (executor instanceof AbstractExecutorService) ? (AbstractExecutorService) executor : null; this.completionQueue = completionQueue; } public Future<V> submit(Callable<V> task) { if (task == null) throw new NullPointerException(); RunnableFuture<V> f = newTaskFor(task); executor.execute(new QueueingFuture(f)); return f; } public Future<V> submit(Runnable task, V result) { if (task == null) throw new NullPointerException(); RunnableFuture<V> f = newTaskFor(task, result); executor.execute(new QueueingFuture(f)); return f; } public Future<V> take() throws InterruptedException { return completionQueue.take(); } public Future<V> poll() { return completionQueue.poll(); } public Future<V> poll(long timeout, TimeUnit unit) throws InterruptedException { return completionQueue.poll(timeout, unit); } }