RxJava之Schedulers源码介绍

103style

发布于 2022-12-19 13:24:20

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Base on RxJava 2.X

简介

RxJava 的 Schedulers 提供了以下五种 Scheduler（调度器）：

static {
    SINGLE = RxJavaPlugins.initSingleScheduler(new SingleTask());
    COMPUTATION = RxJavaPlugins.initComputationScheduler(new ComputationTask());
    IO = RxJavaPlugins.initIoScheduler(new IOTask());
    NEW_THREAD = RxJavaPlugins.initNewThreadScheduler(new NewThreadTask());
    TRAMPOLINE = TrampolineScheduler.instance();
}

以 `Schedulers.single()` 为例介绍

如果我们没有调用 setInitXXSchedulerHandler 或者 setXXSchedulerHandler 自己实现调度器的话(XX 代表上面除了 TRAMPOLINE 的四种调度器的名字)，我们开发中用到的 Schedulers.io(); Schedulers.computation(); Schedulers.newThread(); Schedulers.single(); 实际上就是对应的 XXTask 的 call()方法返回的 Scheduler 对象，即对应的 XXScheduler 对象。

public static void setInitSingleSchedulerHandler(@Nullable Function<? super Callable<Scheduler>, ? extends Scheduler> handler) {
    if (lockdown) {
        throw new IllegalStateException("Plugins can't be changed anymore");
    }
    onInitSingleHandler = handler;
}

public static void setSingleSchedulerHandler(@Nullable Function<? super Scheduler, ? extends Scheduler> handler) {
    if (lockdown) {
        throw new IllegalStateException("Plugins can't be changed anymore");
    }
    onSingleHandler = handler;
}

以下是 Schedulers.single() 的源码介绍：

onSingleScheduler() 中的 onSingleHandler 是通过 setSingleSchedulerHandler() 设置的，默认为 Null ，所以即返回 SINGLE。

public static Scheduler single() {
    return RxJavaPlugins.onSingleScheduler(SINGLE);
}

public static Scheduler onSingleScheduler(@NonNull Scheduler defaultScheduler) {
  Function<? super Scheduler, ? extends Scheduler> f = onSingleHandler;
    if (f == null) {
        return defaultScheduler;
    }
    return apply(f, defaultScheduler);
}

SINGLE 是静态常量，通过 RxJavaPlugins.initSingleScheduler(new SingleTask()); 初始化。

static final Scheduler SINGLE;

static {
    SINGLE = RxJavaPlugins.initSingleScheduler(new SingleTask());
    ...
}

initSingleScheduler() 中的 onInitSingleHandler 是通过 setInitSingleSchedulerHandler() 设置的，默认为 Null ，所以即调用 callRequireNonNull(new SingleTask())。

public static Scheduler initSingleScheduler(@NonNull Callable<Scheduler> defaultScheduler) {
    ObjectHelper.requireNonNull(defaultScheduler, "Scheduler Callable can't be null");
    Function<? super Callable<Scheduler>, ? extends Scheduler> f = onInitSingleHandler;
    if (f == null) {
        return callRequireNonNull(defaultScheduler);
    }
    return applyRequireNonNull(f, defaultScheduler);
}

callRequireNonNull(new SingleTask()) 即返回 SingleTask对象的 call 方法。

static Scheduler callRequireNonNull(@NonNull Callable<Scheduler> s) {
    try {
        return ObjectHelper.requireNonNull(s.call(), "Scheduler Callable result can't be null");
    } catch (Throwable ex) {
        throw ExceptionHelper.wrapOrThrow(ex);
    }
}

static final class SingleTask implements Callable<Scheduler> {
    @Override
    public Scheduler call() throws Exception {
        return SingleHolder.DEFAULT;
    }
}

即创建了一个 SingleScheduler 对象。

static final class SingleHolder {
    static final Scheduler DEFAULT = new SingleScheduler();
}

所以 Schedulers.single() 实际返回的是 SingleScheduler 对象. 同样的： Schedulers.io(); 实际返回的是 IoScheduler 对象 Schedulers.computation(); 实际返回的是 ComputationScheduler 对象 Schedulers.newThread(); 实际返回的是 NewThreadScheduler 对象

`SingleScheduler` 源码介绍

public final class SingleScheduler extends Scheduler {
    final ThreadFactory threadFactory;
    final AtomicReference<ScheduledExecutorService> executor = new AtomicReference<ScheduledExecutorService>();

    private static final String KEY_SINGLE_PRIORITY = "rx2.single-priority";
    private static final String THREAD_NAME_PREFIX = "RxSingleScheduler";

    static final RxThreadFactory SINGLE_THREAD_FACTORY;

    static final ScheduledExecutorService SHUTDOWN;
    static {
        SHUTDOWN = Executors.newScheduledThreadPool(0);
        SHUTDOWN.shutdown();

        int priority = Math.max(Thread.MIN_PRIORITY, Math.min(Thread.MAX_PRIORITY,
                Integer.getInteger(KEY_SINGLE_PRIORITY, Thread.NORM_PRIORITY)));

        SINGLE_THREAD_FACTORY = new RxThreadFactory(THREAD_NAME_PREFIX, priority, true);//1.1
    }

    public SingleScheduler() { //1.0
        this(SINGLE_THREAD_FACTORY);
    }

    public SingleScheduler(ThreadFactory threadFactory) {//2.0
        this.threadFactory = threadFactory;
        executor.lazySet(createExecutor(threadFactory));//4.0
    }

    static ScheduledExecutorService createExecutor(ThreadFactory threadFactory) {//3.0
        return SchedulerPoolFactory.create(threadFactory);
    }
    ...
}

(1.0)默认的构造方法，传入了一个 SINGLE_THREAD_FACTORY的静态常量。(1.1)我们可以看到它是在初始化为 new RxThreadFactory("RxSingleScheduler", 5 , true); 即为 线程名称前缀 为 RxSingleScheduler，优先级为5 不阻塞 的 RxThreadFactory 对象。

(2.0)然后设置当前的 threadFactory 为此 RxThreadFactory 对象。

(3.0)然后通过SchedulerPoolFactory.create(threadFactory)创建了一个执行者。 (3.1)即通过 Executors.newScheduledThreadPool(1, factory)创建了一个核心线程数为 1 的 ScheduledExecutorService(调度线程池)。 (3.2)并将ScheduledExecutorService 放进 SchedulerPoolFactory的 key 为 ScheduledThreadPoolExecutor的 Map 集合 POOLS中。

// Upcast to the Map interface here to avoid 8.x compatibility issues.
// See http://stackoverflow.com/a/32955708/61158
//这个用map接口是为了解决java8的一个bug，具体可以点击上面的链接查看
static final Map<ScheduledThreadPoolExecutor, Object> POOLS =
        new ConcurrentHashMap<ScheduledThreadPoolExecutor, Object>();

public static ScheduledExecutorService create(ThreadFactory factory) {
    final ScheduledExecutorService exec = Executors.newScheduledThreadPool(1, factory);//3.1
    tryPutIntoPool(PURGE_ENABLED, exec);
    return exec;
}

static void tryPutIntoPool(boolean purgeEnabled, ScheduledExecutorService exec) {
    if (purgeEnabled && exec instanceof ScheduledThreadPoolExecutor) {
        ScheduledThreadPoolExecutor e = (ScheduledThreadPoolExecutor) exec;
        POOLS.put(e, exec);//3.2
    }
}

(4.0)然后将 AtomicReference<ScheduledExecutorService> 对象 executor 的 value 设置为上面创建的 ScheduledExecutorService。

我们之前在 Rxjava之timer和interval操作符源码解析介绍过 timer操作符在订阅的时候会执行ObservableTimer的 subscribeActual 方法，

public void subscribeActual(Observer<? super Long> observer) {
    TimerObserver ios = new TimerObserver(observer);
    observer.onSubscribe(ios);
    Disposable d = scheduler.scheduleDirect(ios, delay, unit);
    ios.setResource(d);
}

其中的 scheduler.scheduleDirect(ios, delay, unit)中会通过createWorker()创建一个 Worker。

public Disposable scheduleDirect(@NonNull Runnable run, long delay, @NonNull TimeUnit unit) {
    final Worker w = createWorker(); //
    final Runnable decoratedRun = RxJavaPlugins.onSchedule(run);
    DisposeTask task = new DisposeTask(decoratedRun, w);
    w.schedule(task, delay, unit);
    return task;
}

我们来看看 SingleScheduler的 createWorker()：

public Worker createWorker() {
    return new ScheduledWorker(executor.get()); 
}

static final class ScheduledWorker extends Scheduler.Worker {
    final ScheduledExecutorService executor;
    final CompositeDisposable tasks;
    ScheduledWorker(ScheduledExecutorService executor) {
        this.executor = executor;
        this.tasks = new CompositeDisposable();
    }
    ...
}

通过executor.get()获取 AtomicReference 的value值，通过上面的SingleScheduler 源码(4.0)的介绍，即获取到的是核心线程数为1的 ScheduledExecutorService。
然后将其赋值给 ScheduledWorker的 executor。

然后我们看看w.schedule(task, delay, unit)：

public Disposable schedule(@NonNull Runnable run, long delay, @NonNull TimeUnit unit) {
    if (disposed) {
        return EmptyDisposable.INSTANCE;
    }
    Runnable decoratedRun = RxJavaPlugins.onSchedule(run);
    ScheduledRunnable sr = new ScheduledRunnable(decoratedRun, tasks);
    tasks.add(sr);
    try {
        Future<?> f;
        if (delay <= 0L) {
            f = executor.submit((Callable<Object>)sr);
        } else {
            f = executor.schedule((Callable<Object>)sr, delay, unit);
        }
        sr.setFuture(f);
    } catch (RejectedExecutionException ex) {
        dispose();
        RxJavaPlugins.onError(ex);
        return EmptyDisposable.INSTANCE;
    }
    return sr;
}

首先校验 disposed 的状态，true就直接返回EmptyDisposable.INSTANCE。Rxjava之timer和interval操作符源码解析中介绍的interval操作符里schedulePeriodicallyDirect中会校验这个返回值。

然后构建了也给ScheduledRunnable对象(继承自AtomicReferenceArray)。将传递进来的Runnable对象赋值给actual。将 tasks赋值给AtomicReferenceArray的长度为3的array的第一个索引位置。

public ScheduledRunnable(Runnable actual, DisposableContainer parent) {
    super(3);
    this.actual = actual;
    this.lazySet(0, parent);
}

tasks.add(sr)即把ScheduledRunnable添加到OpenHashSet<Disposable>的resources集合中，在调用dispose()的时候去清空这个集合。

public void dispose() {
    if (!disposed) {
        disposed = true;
        tasks.dispose();
    }
}

然后把这个任务丢给线程池去执行：以timer操作符为例，线程池执行任务即为执行 ObservableTimer中TimerObserver 的 run 方法。

//ObservableTimer
public void subscribeActual(Observer<? super Long> observer) {
    TimerObserver ios = new TimerObserver(observer);
    observer.onSubscribe(ios);
    Disposable d = scheduler.scheduleDirect(ios, delay, unit);
    ios.setResource(d);
}
//ScheduledRunnable
public void run() {
    lazySet(THREAD_INDEX, Thread.currentThread());//1.0
    try {
        try {
            actual.run();
        } catch (Throwable e) {
            // Exceptions.throwIfFatal(e); nowhere to go
            RxJavaPlugins.onError(e);
        }
    } finally {
        lazySet(THREAD_INDEX, null);//1.1
        Object o = get(PARENT_INDEX);//2.0
        if (o != PARENT_DISPOSED && compareAndSet(PARENT_INDEX, o, DONE) && o != null) {
            ((DisposableContainer)o).delete(this);//2.1
        }
        for (;;) {
            o = get(FUTURE_INDEX);//3.0
            if (o == SYNC_DISPOSED || o == ASYNC_DISPOSED || compareAndSet(FUTURE_INDEX, o, DONE)) {
                break;
            }
        }
    }
}

(1.0)保存当前执行任务的线程，(1.1)置空当前执行任务的线程。
(2.0) 获取上面设置的CompositeDisposable对象。(2.2) 去删除OpenHashSet<Disposable> resources中执行完成的任务。
(3.0)直到任务执行完成或者被取消才结束。

返回的 Future对象，被赋值给 ScheduledRunnable中 array的第二个位置。

static final int PARENT_INDEX = 0;
static final int FUTURE_INDEX = 1;
static final int THREAD_INDEX = 2;
public void setFuture(Future<?> f) {
    for (;;) {
        Object o = get(FUTURE_INDEX);
        if (o == DONE) {
            return;
        }
        if (o == SYNC_DISPOSED) {
            f.cancel(false);
            return;
        }
        if (o == ASYNC_DISPOSED) {
            f.cancel(true);
            return;
        }
        if (compareAndSet(FUTURE_INDEX, o, f)) {
            return;
        }
    }
}

NewThreadScheduler 源码介绍

和SingleScheduler类似NewThreadScheduler也是构建了一个核心线程数为1的ScheduledExecutorService。区别就是 NewThreadScheduler 每次调用 Schedulers.newThread() 都是重新创建了一个新的线程池, 不需要去记录之前运行的任务，每个任务之前不会有什么关联，所以使用得时候要注意。以下代码是 NewThreadWorker的 scheduleDirect方法：

public Disposable scheduleDirect(final Runnable run, long delayTime, TimeUnit unit) {
    ScheduledDirectTask task = new ScheduledDirectTask(RxJavaPlugins.onSchedule(run));
    try {
        Future<?> f;
        if (delayTime <= 0L) {
            f = executor.submit(task);
        } else {
            f = executor.schedule(task, delayTime, unit);
        }
        task.setFuture(f);
        return task;
    } catch (RejectedExecutionException ex) {
        RxJavaPlugins.onError(ex);
        return EmptyDisposable.INSTANCE;
    }
}

ScheduledDirectTask：执行任务的返回值为 null。

public final class ScheduledDirectTask extends AbstractDirectTask implements Callable<Void> {
    private static final long serialVersionUID = 1811839108042568751L;
    public ScheduledDirectTask(Runnable runnable) {
        super(runnable);
    }
    @Override
    public Void call() throws Exception {
        runner = Thread.currentThread();
        try {
            runnable.run();
        } finally {
            lazySet(FINISHED);
            runner = null;
        }
        return null;
    }
}

ComputationScheduler 源码介绍

ComputationScheduler 在Rxjava之timer和interval操作符源码解析中已经介绍过，就不再赘述了。

IoScheduler 源码介绍

首先我们看看构造函数做了些什么：

private static final TimeUnit KEEP_ALIVE_UNIT = TimeUnit.SECONDS;
static {
    KEEP_ALIVE_TIME = Long.getLong(KEY_KEEP_ALIVE_TIME, KEEP_ALIVE_TIME_DEFAULT);
    SHUTDOWN_THREAD_WORKER = new ThreadWorker(new RxThreadFactory("RxCachedThreadSchedulerShutdown"));
    SHUTDOWN_THREAD_WORKER.dispose();
    int priority = Math.max(Thread.MIN_PRIORITY, Math.min(Thread.MAX_PRIORITY,
        Integer.getInteger(KEY_IO_PRIORITY, Thread.NORM_PRIORITY)));
    WORKER_THREAD_FACTORY = new RxThreadFactory(WORKER_THREAD_NAME_PREFIX, priority);
    EVICTOR_THREAD_FACTORY = new RxThreadFactory(EVICTOR_THREAD_NAME_PREFIX, priority);
    NONE = new CachedWorkerPool(0, null, WORKER_THREAD_FACTORY);//1.0
    NONE.shutdown();
}

static final class CachedWorkerPool implements Runnable {
    private final long keepAliveTime;
    private final ConcurrentLinkedQueue<ThreadWorker> expiringWorkerQueue;
    final CompositeDisposable allWorkers;
    private final ScheduledExecutorService evictorService;
    private final Future<?> evictorTask;
    private final ThreadFactory threadFactory;

    CachedWorkerPool(long keepAliveTime, TimeUnit unit, ThreadFactory threadFactory) {
        this.keepAliveTime = unit != null ? unit.toNanos(keepAliveTime) : 0L;
        this.expiringWorkerQueue = new ConcurrentLinkedQueue<ThreadWorker>();
        this.allWorkers = new CompositeDisposable();
        this.threadFactory = threadFactory;

        ScheduledExecutorService evictor = null;
        Future<?> task = null;
        if (unit != null) {
            evictor = Executors.newScheduledThreadPool(1, EVICTOR_THREAD_FACTORY);
            task = evictor.scheduleWithFixedDelay(this, this.keepAliveTime, this.keepAliveTime, TimeUnit.NANOSECONDS);
        }
        evictorService = evictor;
        evictorTask = task;
    }
    ...
    void shutdown() {
        allWorkers.dispose();
        if (evictorTask != null) {
            evictorTask.cancel(true);
        }
        if (evictorService != null) {
            evictorService.shutdownNow();
        }
    }
}

public IoScheduler() {
    this(WORKER_THREAD_FACTORY);
}

public IoScheduler(ThreadFactory threadFactory) {
    this.threadFactory = threadFactory;
    this.pool = new AtomicReference<CachedWorkerPool>(NONE);
    start();
}

@Override
public void start() {
    CachedWorkerPool update = new CachedWorkerPool(KEEP_ALIVE_TIME, KEEP_ALIVE_UNIT, threadFactory);
    if (!pool.compareAndSet(NONE, update)) {
        update.shutdown();
    }
}

(1.0)首先构造了一个CachedWorkerPool。
(2.0)将构造的CachedWorkerPool设置为AtomicReference的value的值。
(3.0)构造了一个CachedWorkerPool(60, TimeUnit.SECONDS, new RxThreadFactory(WORKER_THREAD_NAME_PREFIX, priority))，(3.1)即创建了evictorService为核心线程数为1的ScheduledExecutorService的CachedWorkerPool对象。
(4.0)更新AtomicReference的value的值为(3.0)构造的CachedWorkerPool，!pool.compareAndSet(NONE, update)不成立。

接下来我们看看createWorker()：

public Worker createWorker() {
    return new EventLoopWorker(pool.get());//1.0
}

static final class EventLoopWorker extends Scheduler.Worker {
    private final CompositeDisposable tasks;
    private final CachedWorkerPool pool;
    private final ThreadWorker threadWorker;

    final AtomicBoolean once = new AtomicBoolean();

    EventLoopWorker(CachedWorkerPool pool) {
        this.pool = pool;
        this.tasks = new CompositeDisposable();
        this.threadWorker = pool.get();//2.0
    }
    ....
}

(1.0) pool.get()返回的即是 evictorService为核心线程数为1的ScheduledExecutorService的CachedWorkerPool对象。

(2.0) 调用CachedWorkerPool对象的get()获取ThreadWorker。 (2.1) expiringWorkerQueue初始化为空，所以不成立。 (2.2) 所以get()返回的是一个new ThreadWorker(new RxThreadFactory("RxCachedThreadScheduler", 5))。

ThreadWorker get() {
    if (allWorkers.isDisposed()) {
        return SHUTDOWN_THREAD_WORKER;
    }
    while (!expiringWorkerQueue.isEmpty()) { //2.1
        ThreadWorker threadWorker = expiringWorkerQueue.poll();
        if (threadWorker != null) {
            return threadWorker;
        }
    }
    // No cached worker found, so create a new one.
    ThreadWorker w = new ThreadWorker(threadFactory);//2.2
    allWorkers.add(w);
    return w;
}

接下来我们看看EventLoopWorker的schedule()：

 public Disposable schedule(@NonNull Runnable action, long delayTime, @NonNull TimeUnit unit) {
     if (tasks.isDisposed()) {
         // don't schedule, we are unsubscribed
         return EmptyDisposable.INSTANCE;
     }
     return threadWorker.scheduleActual(action, delayTime, unit, tasks);
 }

在createWorker()中我们知到threadWorker即为 new ThreadWorker(new RxThreadFactory("RxCachedThreadScheduler", 5))。

接下来我们看看ThreadWorker继承自NewThreadWorker的scheduleActual(...)：

public ScheduledRunnable scheduleActual(final Runnable run, long delayTime, @NonNull TimeUnit unit, @Nullable DisposableContainer parent) {
    Runnable decoratedRun = RxJavaPlugins.onSchedule(run);
    ScheduledRunnable sr = new ScheduledRunnable(decoratedRun, parent);
    if (parent != null) {
        if (!parent.add(sr)) {
            return sr;
        }
    }
    Future<?> f;
    try {
        if (delayTime <= 0) {
            f = executor.submit((Callable<Object>)sr);
        } else {
            f = executor.schedule((Callable<Object>)sr, delayTime, unit);
        }
        sr.setFuture(f);
    } catch (RejectedExecutionException ex) {
        if (parent != null) {
            parent.remove(sr);
        }
        RxJavaPlugins.onError(ex);
    }
    return sr;
}

可以看到基本和 SingleScheduler类似，就不再赘述了。

小结

Schedulers.single() 实际返回的是 SingleScheduler。 Schedulers.io() 实际返回的是 IoScheduler。 Schedulers.computation() 实际返回的是 ComputationScheduler。 Schedulers.newThread() 实际返回的是 NewThreadScheduler。

createWorker() 返回的值分别为： Schedulers.single() ： ScheduledWorker。 Schedulers.io() ：ThreadWorker。 Schedulers.computation() ：PoolWorker。 Schedulers.newThread() ：NewThreadWorker。

SingleScheduler、Schedulers.io()、NewThreadScheduler 、Schedulers.computation() 最终都是通过 Executors.newScheduledThreadPool(1, factory);构建的核心线程数为1的线程池。

区别就是 Schedulers.newThread() 每次都是创建新的线程池，而其他的都是服用之前已经创建得线程池!!! 所以要慎重选择。

以上

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原始发表：2019-06-01，如有侵权请联系 cloudcommunity@tencent.com 删除

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