Observable的分类
Observable 有 Cold 和 Hot 之分。
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 subscriber1 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println("subscriber1: "+aLong);
}
};
Consumer subscriber2 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber2: "+aLong);
}
};
Observable observable = Observable.create(new ObservableOnSubscribe() {
@Override
public void subscribe(@NonNull ObservableEmitter 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 subscriber1 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println("subscriber1: "+aLong);
}
};
Consumer subscriber2 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber2: "+aLong);
}
};
Consumer subscriber3 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber3: "+aLong);
}
};
ConnectableObservable observable = Observable.create(new ObservableOnSubscribe() {
@Override
public void subscribe(@NonNull ObservableEmitter 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 subscriber1 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println("subscriber1: "+aLong);
}
};
Consumer subscriber2 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber2: "+aLong);
}
};
Consumer subscriber3 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber3: "+aLong);
}
};
Observable observable = Observable.create(new ObservableOnSubscribe() {
@Override
public void subscribe(@NonNull ObservableEmitter e) throws Exception {
Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation())
.take(Integer.MAX_VALUE)
.subscribe(e::onNext);
}
}).observeOn(Schedulers.newThread());
PublishSubject 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.
* All methods except the onSubscribe, onNext, onError and onComplete are thread-safe.
* Use {@link #toSerialized()} to make these methods thread-safe as well.
*
* @param the item value type
*/
public abstract class Subject extends Observable implements Observer {
/**
* Returns true if the subject has any Observers.
* 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.
*
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.
*
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.
*
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.
*
The method is thread-safe.
* @return the wrapped and serialized subject
*/
@NonNull
public final Subject toSerialized() {
if (this instanceof SerializedSubject) {
return this;
}
return new SerializedSubject(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 subscriber1 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println("subscriber1: "+aLong);
}
};
Consumer subscriber2 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber2: "+aLong);
}
};
ConnectableObservable connectableObservable = Observable.create(new ObservableOnSubscribe() {
@Override
public void subscribe(@NonNull ObservableEmitter e) throws Exception {
Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation())
.take(Integer.MAX_VALUE)
.subscribe(e::onNext);
}
}).observeOn(Schedulers.newThread()).publish();
connectableObservable.connect();
Observable 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 subscriber1 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println("subscriber1: "+aLong);
}
};
Consumer subscriber2 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber2: "+aLong);
}
};
Consumer subscriber3 = new Consumer() {
@Override
public void accept(@NonNull Long aLong) throws Exception {
System.out.println(" subscriber3: "+aLong);
}
};
ConnectableObservable connectableObservable = Observable.create(new ObservableOnSubscribe() {
@Override
public void subscribe(@NonNull ObservableEmitter e) throws Exception {
Observable.interval(10, TimeUnit.MILLISECONDS,Schedulers.computation())
.take(Integer.MAX_VALUE)
.subscribe(e::onNext);
}
}).observeOn(Schedulers.newThread()).publish();
connectableObservable.connect();
Observable 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}.
*
* This is an alias for {@link #publish()}.{@link ConnectableObservable#refCount()}.
*
* 
*
* - Scheduler:
* - {@code share} does not operate by default on a particular {@link Scheduler}.
*
*
* @return an {@code ObservableSource} that upon connection causes the source {@code ObservableSource} to emit items
* to its {@link Observer}s
* @see ReactiveX operators documentation: RefCount
*/
@CheckReturnValue
@SchedulerSupport(SchedulerSupport.NONE)
public final Observable 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。