第三課-java線程池的使用

在前面的文章中,我們使用線程的時候就去創建一個線程,這樣實現起來非常簡便,但是就會有一個問題:

  如果併發的線程數量很多,並且每個線程都是執行一個時間很短的任務就結束了,這樣頻繁創建線程就會大大降低系統的效率,因爲頻繁創建線程和銷燬線程需要時間。

  那麼有沒有一種辦法使得線程可以複用,就是執行完一個任務,並不被銷燬,而是可以繼續執行其他的任務?

  在Java中可以通過線程池來達到這樣的效果。今天我們就來詳細講解一下Java的線程池,首先我們從最核心的ThreadPoolExecutor類中的方法講起,然後再講述它的實現原理,接着給出了它的使用示例,最後討論了一下如何合理配置線程池的大小。

  以下是本文的目錄大綱:

     一.java常見的四種線程池的使用

  二.Java中的ThreadPoolExecutor類

 三.深入剖析線程池實現原理

 四.如何合理配置線程池的大小 

java常見的四種線程池的使用

 java常見的四種線程池的使用,這個在Executors定義的非常清晰,我們看源碼


package java.util.concurrent;
import java.util.*;
import java.util.concurrent.atomic.AtomicInteger;
import java.security.AccessControlContext;
import java.security.AccessController;
import java.security.PrivilegedAction;
import java.security.PrivilegedExceptionAction;
import java.security.PrivilegedActionException;
import java.security.AccessControlException;
import sun.security.util.SecurityConstants;
public class Executors {

    /**創建固定大小線程池用完就回收**/
    public static ExecutorService newFixedThreadPool(int nThreads) {
        return new ThreadPoolExecutor(nThreads, nThreads,
                                      0L, TimeUnit.MILLISECONDS,
                                      new LinkedBlockingQueue<Runnable>());
    }
    /**創建固定大小線程池ForkJoinPool**/
    public static ExecutorService newWorkStealingPool(int parallelism) {
        return new ForkJoinPool
            (parallelism,
             ForkJoinPool.defaultForkJoinWorkerThreadFactory,
             null, true);
    }
    /**創建固定大小線程池ForkJoinPool,更具cpu的核心數量**/
    public static ExecutorService newWorkStealingPool() {
        return new ForkJoinPool
            (Runtime.getRuntime().availableProcessors(),
             ForkJoinPool.defaultForkJoinWorkerThreadFactory,
             null, true);
    }
    /**創建固定大小線程池自定義ThreadFactory,使用LinkedBlockingQueue**/
    public static ExecutorService newFixedThreadPool(int nThreads, ThreadFactory threadFactory) {
        return new ThreadPoolExecutor(nThreads, nThreads,
                                      0L, TimeUnit.MILLISECONDS,
                                      new LinkedBlockingQueue<Runnable>(),
                                      threadFactory);
    }
     /**創建單線程線程池**/
    public static ExecutorService newSingleThreadExecutor() {
        return new FinalizableDelegatedExecutorService
            (new ThreadPoolExecutor(1, 1,
                                    0L, TimeUnit.MILLISECONDS,
                                    new LinkedBlockingQueue<Runnable>()));
    }
     /**創建單線程線程池,自定義ThreadFactory **/
    public static ExecutorService newSingleThreadExecutor(ThreadFactory threadFactory) {
        return new FinalizableDelegatedExecutorService
            (new ThreadPoolExecutor(1, 1,
                                    0L, TimeUnit.MILLISECONDS,
                                    new LinkedBlockingQueue<Runnable>(),
                                    threadFactory));
    }
     /**創建無限制線程池(最大整數)**/
    public static ExecutorService newCachedThreadPool() {
        return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
                                      60L, TimeUnit.SECONDS,
                                      new SynchronousQueue<Runnable>());
    }
      /**創建無限制線程池(最大整數),自定義ThreadFactory **/
    public static ExecutorService newCachedThreadPool(ThreadFactory threadFactory) {
        return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
                                      60L, TimeUnit.SECONDS,
                                      new SynchronousQueue<Runnable>(),
                                      threadFactory);
    }

    /**單線程定時線程池**/
    
    public static ScheduledExecutorService newSingleThreadScheduledExecutor() {
        return new DelegatedScheduledExecutorService
            (new ScheduledThreadPoolExecutor(1));
    }

    /**單線程定時線程池,自定義ThreadFactory**/
    public static ScheduledExecutorService newSingleThreadScheduledExecutor(ThreadFactory threadFactory) {
        return new DelegatedScheduledExecutorService
            (new ScheduledThreadPoolExecutor(1, threadFactory));
    }

     /**定時線程池,固定線程數量**/
    public static ScheduledExecutorService newScheduledThreadPool(int corePoolSize) {
        return new ScheduledThreadPoolExecutor(corePoolSize);
    }

    /**定時線程池,固定線程數量,自定義ThreadFactory**/
    public static ScheduledExecutorService newScheduledThreadPool(
            int corePoolSize, ThreadFactory threadFactory) {
        return new ScheduledThreadPoolExecutor(corePoolSize, threadFactory);
    }

    
    private Executors() {}
}

從上面可以看出線程池的四種類型:

1.固定大小的線程池
2.單任務線程池
3.可變尺寸的線程池
4.調度線程池

這四種線程池除了固定大小線程池使用ForJoinPool,還有個很特別的現象就是每個線程池都可以有自定義的ThreadFactory,那麼爲什麼要自定義ThreadFactory,首先看一下DefaultThreadFactory

/**
     * The default thread factory
     */
    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;
        }
    }

默認的ThreadFactory實際做的事情就是創建線程,給線程命名,設置線程優先級這些功能,如果有需要我們可以重寫Thread類,對異常進行捕獲,日誌打印等等業務,所以爲了方便我們處理都所有的線程池都提供了線程工廠的自定義實現

Java中的ThreadPoolExecutor類

java.uitl.concurrent.ThreadPoolExecutor類是線程池中最核心的一個類,因此如果要透徹地瞭解Java中的線程池,必須先了解這個類。下面我們來看一下ThreadPoolExecutor類的具體實現源碼,在ThreadPoolExecutor類中提供了四個構造方法:

public class ThreadPoolExecutor extends AbstractExecutorService {
    .....
    public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
            BlockingQueue<Runnable> workQueue);
 
    public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
            BlockingQueue<Runnable> workQueue,ThreadFactory threadFactory);
 
    public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
            BlockingQueue<Runnable> workQueue,RejectedExecutionHandler handler);
 
    public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
        BlockingQueue<Runnable> workQueue,ThreadFactory threadFactory,RejectedExecutionHandler handler);
    ...
}

從上面的代碼可以得知,ThreadPoolExecutor繼承了AbstractExecutorService類,並提供了四個構造器,事實上,通過觀察每個構造器的源碼具體實現,發現前面三個構造器都是調用的第四個構造器進行的初始化工作。

   下面解釋下一下構造器中各個參數的含義:

  • corePoolSize:核心池的大小,這個參數跟後面講述的線程池的實現原理有非常大的關係。在創建了線程池後,默認情況下,線程池中並沒有任何線程,而是等待有任務到來才創建線程去執行任務,除非調用了prestartAllCoreThreads()或者prestartCoreThread()方法,從這2個方法的名字就可以看出,是預創建線程的意思,即在沒有任務到來之前就創建corePoolSize個線程或者一個線程。默認情況下,在創建了線程池後,線程池中的線程數爲0,當有任務來之後,就會創建一個線程去執行任務,當線程池中的線程數目達到corePoolSize後,就會把到達的任務放到緩存隊列當中;
  • maximumPoolSize:線程池最大線程數,這個參數也是一個非常重要的參數,它表示在線程池中最多能創建多少個線程;
  • keepAliveTime:表示線程沒有任務執行時最多保持多久時間會終止。默認情況下,只有當線程池中的線程數大於corePoolSize時,keepAliveTime纔會起作用,直到線程池中的線程數不大於corePoolSize,即當線程池中的線程數大於corePoolSize時,如果一個線程空閒的時間達到keepAliveTime,則會終止,直到線程池中的線程數不超過corePoolSize。但是如果調用了allowCoreThreadTimeOut(boolean)方法,在線程池中的線程數不大於corePoolSize時,keepAliveTime參數也會起作用,直到線程池中的線程數爲0;
  • unit:參數keepAliveTime的時間單位
  • workQueue:一個阻塞隊列,用來存儲等待執行的任務,這個參數的選擇也很重要,會對線程池的運行過程產生重大影響,一般來說,這裏的阻塞隊列有以下幾種選擇:
ArrayBlockingQueue;
LinkedBlockingQueue;
SynchronousQueue;

ArrayBlockingQueue和PriorityBlockingQueue使用較少,一般使用LinkedBlockingQueue和Synchronous。線程池的排隊策略與BlockingQueue有關。

  • threadFactory:線程工廠,主要用來創建線程;
  • handler:表示當拒絕處理任務時的策略,有以下四種取值:
ThreadPoolExecutor.AbortPolicy:丟棄任務並拋出RejectedExecutionException異常。 
ThreadPoolExecutor.DiscardPolicy:也是丟棄任務,但是不拋出異常。 
ThreadPoolExecutor.DiscardOldestPolicy:丟棄隊列最前面的任務,然後重新嘗試執行任務(重複此過程)
ThreadPoolExecutor.CallerRunsPolicy:由調用線程處理該任務 

  從上面給出的ThreadPoolExecutor類的代碼可以知道,ThreadPoolExecutor繼承了AbstractExecutorService,我們來看一下AbstractExecutorService的實現:

public abstract class AbstractExecutorService implements ExecutorService {
 
     
    protected <T> RunnableFuture<T> newTaskFor(Runnable runnable, T value) { };
    protected <T> RunnableFuture<T> newTaskFor(Callable<T> callable) { };
    public Future<?> submit(Runnable task) {};
    public <T> Future<T> submit(Runnable task, T result) { };
    public <T> Future<T> submit(Callable<T> task) { };
    private <T> T doInvokeAny(Collection<? extends Callable<T>> tasks,
                            boolean timed, long nanos)
        throws InterruptedException, ExecutionException, TimeoutException {
    };
    public <T> T invokeAny(Collection<? extends Callable<T>> tasks)
        throws InterruptedException, ExecutionException {
    };
    public <T> T invokeAny(Collection<? extends Callable<T>> tasks,
                           long timeout, TimeUnit unit)
        throws InterruptedException, ExecutionException, TimeoutException {
    };
    public <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks)
        throws InterruptedException {
    };
    public <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks,
                                         long timeout, TimeUnit unit)
        throws InterruptedException {
    };
}

AbstractExecutorService是一個抽象類,它實現了ExecutorService接口。

  我們接着看ExecutorService接口的實現:

 package java.util.concurrent;
import java.util.List;
import java.util.Collection;
 
public interface ExecutorService extends Executor {
    void shutdown();
    List<Runnable> shutdownNow();

    boolean isShutdown();
    boolean isTerminated();

    boolean awaitTermination(long timeout, TimeUnit unit)
        throws InterruptedException;

    <T> Future<T> submit(Callable<T> task);

    <T> Future<T> submit(Runnable task, T result);


    Future<?> submit(Runnable task);

    <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks)
        throws InterruptedException;


    <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks,
                                  long timeout, TimeUnit unit)
        throws InterruptedException;


    <T> T invokeAny(Collection<? extends Callable<T>> tasks)
        throws InterruptedException, ExecutionException;

    <T> T invokeAny(Collection<? extends Callable<T>> tasks,
                    long timeout, TimeUnit unit)
        throws InterruptedException, ExecutionException, TimeoutException;
}

  而ExecutorService又是繼承了Executor接口,我們看一下Executor接口的實現:

public interface Executor {
    void execute(Runnable command);
}

到這裏,大家應該明白了ThreadPoolExecutor、AbstractExecutorService、ExecutorService和Executor幾個之間的關係了。

  Executor是一個頂層接口,在它裏面只聲明瞭一個方法execute(Runnable),返回值爲void,參數爲Runnable類型,從字面意思可以理解,就是用來執行傳進去的任務的;

  然後ExecutorService接口繼承了Executor接口,並聲明瞭一些方法:submit、invokeAll、invokeAny以及shutDown等;

  抽象類AbstractExecutorService實現了ExecutorService接口,基本實現了ExecutorService中聲明的所有方法;

  然後ThreadPoolExecutor繼承了類AbstractExecutorService。

  在ThreadPoolExecutor類中有幾個非常重要的方法:

execute()
shutdown()
shutdownNow()

execute()方法實際上是Executor中聲明的方法,在ThreadPoolExecutor進行了具體的實現,這個方法是ThreadPoolExecutor的核心方法,通過這個方法可以向線程池提交一個任務,交由線程池去執行。

  submit()方法是在ExecutorService中聲明的方法,在AbstractExecutorService就已經有了具體的實現,在ThreadPoolExecutor中並沒有對其進行重寫,這個方法也是用來向線程池提交任務的,但是它和execute()方法不同,它能夠返回任務執行的結果,去看submit()方法的實現,會發現它實際上還是調用的execute()方法,只不過它利用了Future來獲取任務執行結果(Future相關內容將在下一篇講述)。

 

  shutdown()和shutdownNow()是用來關閉線程池的。

  還有很多其他的方法:

  比如:getQueue() 、getPoolSize() 、getActiveCount()、getCompletedTaskCount()等獲取與線程池相關屬性的方法,有興趣的朋友可以自行查閱API。

深入剖析線程池實現原理

1.線程池的狀態

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;

 runState表示當前線程池的狀態,它是一個volatile變量用來保證線程之間的可見性;

  下面的幾個static final變量表示runState可能的幾個取值。

  當創建線程池後,初始時,線程池處於RUNNING狀態;

  如果調用了shutdown()方法,則線程池處於SHUTDOWN狀態,此時線程池不能夠接受新的任務,它會等待所有任務執行完畢;

  如果調用了shutdownNow()方法,則線程池處於STOP狀態,此時線程池不能接受新的任務,並且會去嘗試終止正在執行的任務;

  當線程池處於SHUTDOWN或STOP狀態,並且所有工作線程已經銷燬,任務緩存隊列已經清空或執行結束後,線程池被設置爲TERMINATED狀態。

2.任務的執行

  在瞭解將任務提交給線程池到任務執行完畢整個過程之前,我們先來看一下ThreadPoolExecutor類中其他的一些比較重要成員變量:

private final BlockingQueue<Runnable> workQueue;              //任務緩存隊列,用來存放等待執行的任務
private final ReentrantLock mainLock = new ReentrantLock();   //線程池的主要狀態鎖,對線程池狀態(比如線程池大小
                                                              //、runState等)的改變都要使用這個鎖
private final HashSet<Worker> workers = new HashSet<Worker>();  //用來存放工作集
 
 private final Condition termination = mainLock.newCondition(); // 細粒度的控制鎖

private volatile long  keepAliveTime;    //線程存貨時間   
private volatile boolean allowCoreThreadTimeOut;   //是否允許爲核心線程設置存活時間
private volatile int   corePoolSize;     //核心池的大小(即線程池中的線程數目大於這個參數時,提交的任務會被放進任務緩存隊列)
private volatile int   maximumPoolSize;   //線程池最大能容忍的線程數
 
private volatile int   poolSize;       //線程池中當前的線程數
 
private volatile RejectedExecutionHandler handler; //任務拒絕策略
 private static final RejectedExecutionHandler defaultHandler = new AbortPolicy();// 默認拒絕策略
 
private volatile ThreadFactory threadFactory;   //線程工廠,用來創建線程
 
private int largestPoolSize;   //用來記錄線程池中曾經出現過的最大線程數
 
private long completedTaskCount;   //用來記錄已經執行完畢的任務個數

  下面我們進入正題,看一下任務從提交到最終執行完畢經歷了哪些過程。

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);
    }

 

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