RxJava – Reactive Extensions for the JVM – a library for composing asynchronous and event-based programs using observable sequences for the Java VM.
setDisposable. The behavior then is provided by the Emitter. I don't see any case for misleading naming, just misunderstanding. The main use case for setCancellable is to release resources created within the emitter callback which are scoped for the duration of the emission. If you have external resources that are shared, you'll need other means to release them considering how a solution would interact with it.
The governing rule here is 1.6:
"If a Publisher signals either onError or onComplete on a Subscriber, that Subscriber’s Subscription MUST be considered cancelled.
The intent of this rule is to make sure that a Subscription is treated the same no matter if it was cancelled, the Publisher signalled onError or onComplete."
People coming from different backgrounds tend to get confused by different naming. There is often discussion how to name components so that it doesn't imply too much but doesn't go under the radar either. setCancellable follows the typical bean-setter naming indicating you set some object on this emitter.
I want to create a PublishSubject, but how can I, upon declaration, specify actions that should be done when an observer subscribes, or when the subject gets disposed?
BehaviorSubject<T> valueSubject = (BehaviorSubject<T>) BehaviorSubject.create(new ObservableOnSubscribe<T>() {
@Override
public void subscribe(ObservableEmitter<T> emitter) throws Exception {
// do something here
}
});
io.reactivex.internal.operators.observable.ObservableCreate cannot be cast to io.reactivex.subjects.BehaviorSubject
create method. create(ObservableOnSubscribe) is defined on Observable which creates an Observable, a cold source and will have nothing to do with the subject type. Many operators in RxJava are named after the behavior they do in an everyday language, such as "actions done when an observer subscribes" -> doOnSubscribe, when the subscription gets disposed: doOnDispose. Subjects themselves are not disposed.Based on the misunderstanding your question implies, I wanted to encourage you to familiarize yourself with the concepts and components of RxJava first, so the answer, which invokes more concepts and components, can be understood better. For this, I suggest reading Learning RxJava.
@RequestMapping(method = RequestMethod.POST, value = "/pushData", produces = MediaType.APPLICATION_JSON_UTF8_VALUE)
public Single<String> pushData(@RequestBody String json) How I can slowdown a pressure on the logic inside this method? Is it a right way of thinking or I should slow it down the level of Undertow/Jetty/Netty by applying some strategy on it.
Single implies a single result so backpressure is not really at play there. If you want to reduce the call frequency to pushData itself, there are ways for it, such as using concatMap or flatMap with concurrency limit, spanning out the source events over time, etc. You could also research Retrofit use cases similar to your problem.
public Single<String> pushJsonDataAsync(String json) {
return Single.create(source -> {
try {
PushCrawlerDataRequest.Builder request = PushCrawlerDataRequest.newBuilder();
JsonFormat.parser().merge(json, request);
PushCrawlerDataResponse.Builder builder = pushData(request.build());
source.onSuccess(JsonFormat.printer().print(builder));
} catch (Exception ex) {
source.onError(ex);
}
});
}
hello,
I have a Flowable that gets inbound data with events. These events are not in order. These messages are expected to reach subscribers in order(ascending order of event ID).
This is a infinite stream, sometime may be large enough to be stored in memory.
How can I achieve this using rxJava or without rx?
I'm processing a live video stream and would like to improve performance using
Flowable, BackpressureStrategy.DROP and the sample operator to limit the number of frames per second. I have implemented the same functionality using Observable and also limiting the number of frames with the sample operator. The second variant has a superior performance with respect to the first, however, I am concerned that in a computer with less processing power may have Backpressure issues.
How to properly perform action after the subscription? doOnSubscribe doesn't fit the needs
Example
PublishProcessor<Integer> processor = PublishProcessor.create();
processor
.doOnSubscribe(subscription -> processor.onNext(1))
.subscribe(System.out::println);
processor.onNext(2);prints
2As a workaround i use this approach
processor
.mergeWith(Completable.fromAction(() -> processor.onNext(1)).toFlowable())
.subscribe(System.out::println);This prints
1
2as expected
@akarnokd I have 2 event bus like processors. One is for requests second is for results. There may be multiple request handlers which will post a results to the result processor. This may be either synchronously or asynchronously. I want to make a request and wait for the result in the same flowable
Simplified case
PublishProcessor<Integer> requestBus = PublishProcessor.create();
PublishProcessor<Pair<Integer, Integer>> resultBus = PublishProcessor.create();
requestBus.filter(value -> value == 1)
.map(value -> Pair.create(value, 10))
.subscribe(resultBus);
Integer request = 1;
Flowable<Integer> resultFlowable = resultBus
.filter(requestResultPair -> requestResultPair.first == request)
.doOnSubscribe(__ -> requestBus.onNext(request));
BehaviorSubject flatMapped in instead of the constant and subscribe the BehaviorSubject to the shared observable in publish.