Observable的分类
Observable 有 Cold 和 Hot 之分。
hot&cold observable.jpg
Hot Observable 无论有没有 Subscriber 订阅，事件始终都会发生。当 Hot Observable 有多个订阅者时，Hot Observable 与订阅者们的关系是一对多的关系，可以与多个订阅者共享信息。
然而，Cold Observable 只有 Subscriber 订阅时，才开始执行发射数据流的代码。并且 Cold Observable 和 Subscriber 只能是一对一的关系，当有多个不同的订阅者时，消息是重新完整发送的。也就是说对 Cold Observable 而言，有多个Subscriber的时候，他们各自的事件是独立的。
如果上面的解释有点枯燥的话，那么下面会更加形象地说明 Cold 和 Hot 的区别：
Think of a hot Observable as a radio station. All of the listeners that are listening to it at this moment listen to the same song.
A cold Observable is a music CD. Many people can buy it and listen to it independently.
by Nickolay Tsvetinov
Cold Observable
Observable 的 just、creat、range、fromXXX 等操作符都能生成Cold Observable。
Consumer<Long> subscriber1 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println("subscriber1: "+aLong); } }; Consumer<Long> subscriber2 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber2: "+aLong); } }; Observable<Long> observable = Observable.create(new ObservableOnSubscribe<Long>() { @Override public void subscribe(@NonNull ObservableEmitter<Long> e) throws Exception { Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation()) .take(Integer.MAX_VALUE) .subscribe(e::onNext); } }).observeOn(Schedulers.newThread()); observable.subscribe(subscriber1); observable.subscribe(subscriber2); try { Thread.sleep(100L); } catch (InterruptedException e) { e.printStackTrace(); }
执行结果：
subscriber1: 0 subscriber2: 0 subscriber1: 1 subscriber2: 1 subscriber1: 2 subscriber2: 2 subscriber2: 3 subscriber1: 3 subscriber1: 4 subscriber2: 4 subscriber2: 5 subscriber1: 5 subscriber1: 6 subscriber2: 6 subscriber1: 7 subscriber2: 7 subscriber1: 8 subscriber2: 8 subscriber1: 9 subscriber2: 9
可以看出，subscriber1 和 subscriber2 的结果并不一定是相同的，二者是完全独立的。
尽管 Cold Observable 很好，但是对于某些事件不确定何时发生以及不确定 Observable 发射的元素数量，那还得使用 Hot Observable。比如：UI交互的事件、网络环境的变化、地理位置的变化、服务器推送消息的到达等等。
Cold Observable 如何转换成 Hot Observable？
1. 使用publish，生成 ConnectableObservable
使用 publish 操作符，可以让 Cold Observable 转换成 Hot Observable。它将原先的 Observable 转换成 ConnectableObservable。
来看看刚才的例子：
Consumer<Long> subscriber1 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println("subscriber1: "+aLong); } }; Consumer<Long> subscriber2 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber2: "+aLong); } }; Consumer<Long> subscriber3 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber3: "+aLong); } }; ConnectableObservable<Long> observable = Observable.create(new ObservableOnSubscribe<Long>() { @Override public void subscribe(@NonNull ObservableEmitter<Long> e) throws Exception { Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation()) .take(Integer.MAX_VALUE) .subscribe(e::onNext); } }).observeOn(Schedulers.newThread()).publish(); observable.connect(); observable.subscribe(subscriber1); observable.subscribe(subscriber2); try { Thread.sleep(20L); } catch (InterruptedException e) { e.printStackTrace(); } observable.subscribe(subscriber3); try { Thread.sleep(100L); } catch (InterruptedException e) { e.printStackTrace(); }
注意，生成的 ConnectableObservable 需要调用connect()才能真正执行。
执行结果：
subscriber1: 0 subscriber2: 0 subscriber1: 1 subscriber2: 1 subscriber1: 2 subscriber2: 2 subscriber3: 2 subscriber1: 3 subscriber2: 3 subscriber3: 3 subscriber1: 4 subscriber2: 4 subscriber3: 4 subscriber1: 5 subscriber2: 5 subscriber3: 5 subscriber1: 6 subscriber2: 6 subscriber3: 6 subscriber1: 7 subscriber2: 7 subscriber3: 7 subscriber1: 8 subscriber2: 8 subscriber3: 8 subscriber1: 9 subscriber2: 9 subscriber3: 9 subscriber1: 10 subscriber2: 10 subscriber3: 10 subscriber1: 11 subscriber2: 11 subscriber3: 11
可以看到，多个订阅的 Subscriber 共享同一事件。
在这里，ConnectableObservable 是线程安全的。
2. 使用Subject/Processor
Subject 和 Processor 的作用是相同的。Processor 是 RxJava2.x 新增的类，继承自 Flowable 支持背压控制。而 Subject 则不支持背压控制。
Consumer<Long> subscriber1 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println("subscriber1: "+aLong); } }; Consumer<Long> subscriber2 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber2: "+aLong); } }; Consumer<Long> subscriber3 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber3: "+aLong); } }; Observable<Long> observable = Observable.create(new ObservableOnSubscribe<Long>() { @Override public void subscribe(@NonNull ObservableEmitter<Long> e) throws Exception { Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation()) .take(Integer.MAX_VALUE) .subscribe(e::onNext); } }).observeOn(Schedulers.newThread()); PublishSubject<Long> subject = PublishSubject.create(); observable.subscribe(subject); subject.subscribe(subscriber1); subject.subscribe(subscriber2); try { Thread.sleep(20L); } catch (InterruptedException e) { e.printStackTrace(); } subject.subscribe(subscriber3); try { Thread.sleep(100L); } catch (InterruptedException e) { e.printStackTrace(); }
执行结果跟上面使用 publish 操作符是一样的。
Subject 既是 Observable 又是 Observer(Subscriber)。这一点可以从 Subject 的源码上看到。
import io.reactivex.*; import io.reactivex.annotations.*; /** * Represents an Observer and an Observable at the same time, allowing * multicasting events from a single source to multiple child Subscribers. * <p>All methods except the onSubscribe, onNext, onError and onComplete are thread-safe. * Use {@link #toSerialized()} to make these methods thread-safe as well. * * @param <T> the item value type */ public abstract class Subject<T> extends Observable<T> implements Observer<T> { /** * Returns true if the subject has any Observers. * <p>The method is thread-safe. * @return true if the subject has any Observers */ public abstract boolean hasObservers(); /** * Returns true if the subject has reached a terminal state through an error event. * <p>The method is thread-safe. * @return true if the subject has reached a terminal state through an error event * @see #getThrowable() * &see {@link #hasComplete()} */ public abstract boolean hasThrowable(); /** * Returns true if the subject has reached a terminal state through a complete event. * <p>The method is thread-safe. * @return true if the subject has reached a terminal state through a complete event * @see #hasThrowable() */ public abstract boolean hasComplete(); /** * Returns the error that caused the Subject to terminate or null if the Subject * hasn't terminated yet. * <p>The method is thread-safe. * @return the error that caused the Subject to terminate or null if the Subject * hasn't terminated yet */ @Nullable public abstract Throwable getThrowable(); /** * Wraps this Subject and serializes the calls to the onSubscribe, onNext, onError and * onComplete methods, making them thread-safe. * <p>The method is thread-safe. * @return the wrapped and serialized subject */ @NonNull public final Subject<T> toSerialized() { if (this instanceof SerializedSubject) { return this; } return new SerializedSubject<T>(this); } }
当 Subject 作为 Subscriber 时，它可以订阅目标 Cold Observable 使对方开始发送事件。同时它又作为Observable 转发或者发送新的事件，让 Cold Observable 借助 Subject 转换为 Hot Observable。
注意，Subject 并不是线程安全的，如果想要其线程安全需要调用toSerialized()方法。(在RxJava1.x的时代还可以用 SerializedSubject 代替 Subject，但是在RxJava2.x以后SerializedSubject不再是一个public class）
然而，很多基于 EventBus 改造的 RxBus 并没有这么做，包括我以前也写过这样的 RxBus :( 。这样的做法是非常危险的，因为会遇到并发的情况。
Hot Observable 如何转换成 Cold Observable？
1. ConnectableObservable的refCount操作符
reactivex官网的解释是
make a Connectable Observable behave like an ordinary Observable
RefCount.png
RefCount操作符把从一个可连接的 Observable 连接和断开的过程自动化了。它操作一个可连接的Observable，返回一个普通的Observable。当第一个订阅者订阅这个Observable时，RefCount连接到下层的可连接Observable。RefCount跟踪有多少个观察者订阅它，直到最后一个观察者完成才断开与下层可连接Observable的连接。
如果所有的订阅者都取消订阅了，则数据流停止。如果重新订阅则重新开始数据流。
Consumer<Long> subscriber1 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println("subscriber1: "+aLong); } }; Consumer<Long> subscriber2 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber2: "+aLong); } }; ConnectableObservable<Long> connectableObservable = Observable.create(new ObservableOnSubscribe<Long>() { @Override public void subscribe(@NonNull ObservableEmitter<Long> e) throws Exception { Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation()) .take(Integer.MAX_VALUE) .subscribe(e::onNext); } }).observeOn(Schedulers.newThread()).publish(); connectableObservable.connect(); Observable<Long> observable = connectableObservable.refCount(); Disposable disposable1 = observable.subscribe(subscriber1); Disposable disposable2 = observable.subscribe(subscriber2); try { Thread.sleep(20L); } catch (InterruptedException e) { e.printStackTrace(); } disposable1.dispose(); disposable2.dispose(); System.out.println("重新开始数据流"); disposable1 = observable.subscribe(subscriber1); disposable2 = observable.subscribe(subscriber2); try { Thread.sleep(20L); } catch (InterruptedException e) { e.printStackTrace(); }
执行结果：
subscriber1: 0 subscriber2: 0 subscriber1: 1 subscriber2: 1 重新开始数据流 subscriber1: 0 subscriber2: 0 subscriber1: 1 subscriber2: 1
如果不是所有的订阅者都取消了订阅，只取消了部分。部分的订阅者重新开始订阅，则不会从头开始数据流。
Consumer<Long> subscriber1 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println("subscriber1: "+aLong); } }; Consumer<Long> subscriber2 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber2: "+aLong); } }; Consumer<Long> subscriber3 = new Consumer<Long>() { @Override public void accept(@NonNull Long aLong) throws Exception { System.out.println(" subscriber3: "+aLong); } }; ConnectableObservable<Long> connectableObservable = Observable.create(new ObservableOnSubscribe<Long>() { @Override public void subscribe(@NonNull ObservableEmitter<Long> e) throws Exception { Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation()) .take(Integer.MAX_VALUE) .subscribe(e::onNext); } }).observeOn(Schedulers.newThread()).publish(); connectableObservable.connect(); Observable<Long> observable = connectableObservable.refCount(); Disposable disposable1 = observable.subscribe(subscriber1); Disposable disposable2 = observable.subscribe(subscriber2); observable.subscribe(subscriber3); try { Thread.sleep(20L); } catch (InterruptedException e) { e.printStackTrace(); } disposable1.dispose(); disposable2.dispose(); System.out.println("subscriber1、subscriber2 重新订阅"); disposable1 = observable.subscribe(subscriber1); disposable2 = observable.subscribe(subscriber2); try { Thread.sleep(20L); } catch (InterruptedException e) { e.printStackTrace(); }
执行结果：
subscriber1: 0 subscriber2: 0 subscriber3: 0 subscriber1: 1 subscriber2: 1 subscriber3: 1 subscriber1、subscriber2 重新订阅 subscriber3: 2 subscriber1: 2 subscriber2: 2 subscriber3: 3 subscriber1: 3 subscriber2: 3 subscriber3: 4 subscriber1: 4 subscriber2: 4
在这里，subscriber1和subscriber2先取消了订阅，subscriber3并没有取消订阅。之后，subscriber1和subscriber2又重新订阅。最终subscriber1、subscriber2、subscriber3的值保持一致。
2. Observable的share操作符
share操作符封装了publish().refCount()调用，可以看其源码。
/** * Returns a new {@link ObservableSource} that multicasts (shares) the original {@link ObservableSource}. As long as * there is at least one {@link Observer} this {@link ObservableSource} will be subscribed and emitting data. * When all subscribers have disposed it will dispose the source {@link ObservableSource}. * <p> * This is an alias for {@link #publish()}.{@link ConnectableObservable#refCount()}. * <p> *  * <dl> * <dt><b>Scheduler:</b></dt> * <dd>{@code share} does not operate by default on a particular {@link Scheduler}.</dd> * </dl> * * @return an {@code ObservableSource} that upon connection causes the source {@code ObservableSource} to emit items * to its {@link Observer}s * @see <a href="http://reactivex.io/documentation/operators/refcount.html">ReactiveX operators documentation: RefCount</a> */ @CheckReturnValue @SchedulerSupport(SchedulerSupport.NONE) public final Observable<T> share() { return publish().refCount(); }
总结
理解了 Hot Observable 和 Cold Observable 的区别才能够写出更好Rx代码。同理，也能理解Hot & Cold Flowable。再者，在其他语言的Rx版本中包括 RxSwift、RxJS 等也存在 Hot Observable 和 Cold Observable 这样的概念。
