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RxJava repeat with delay only part of the flow

I have an Rx flow which performs two actions in sequence whenever a certain event happens:
send an SMS to a given set of numbers - which returns Single<Holster>
save the event on a local DB - which returns Completable
here is my code
private void saveBluetoothAlarm(#NonNull Alarm alarm, int type) {
disposable.add( dbManager.getHolsterDAO().getCurrentHolster()
.map(holsters -> holsters.get(0))
.observeOn(AndroidSchedulers.mainThread())
.flatMap(holster -> sendSmsToAll(holster, alarm.type))
.observeOn(Schedulers.io())
.flatMapCompletable(holster -> {
switch (alarm.type) {
case StatisticsEventType.EXTRACTION:
if (something)
return Completable.complete();
else
return Completable.fromAction(() -> dbManager.getAlarmDAO().insert(alarm))
.andThen(saveAlarmOnServer(holster.getId(), alarm));
case StatisticsEventType.MOVEMENT:
if (somethingMore)
return Completable.complete();
else
return Completable.fromAction(() -> dbManager.getAlarmDAO().insert(alarm))
.andThen(saveAlarmOnServer(holster.getId(), alarm));
}
return Completable.complete();
})
.subscribe(() -> {}, Timber::e)
);
}
everything works, now I need the first action sendSmsToAll(holster, alarm.type) to be repeated a defined amount of times, each delayed by a defined amount of seconds, these settings are defined in my Holster object.
I tried editing to the flatMap() like the following, making sendSmsToAll() return Holster:
.flatMapObservable(holster -> Observable.just(sendSmsToAll(holster, alarm.type))
.repeat(holster.sms_settings.repetitions_count)
.delaySubscription(holster.sms_settings.interval, TimeUnit.SECONDS)
)
but the SMS is sent only once, I even tried a lot of other "combinations" (mostly because I am a noob with RxJava) but nothing works.

Have you tried something like that:
.flatMapObservable(holster -> Observable.zip(Observable.defer(() -> sendSmsToAll(holster, alarm.type)),
Flowable.timer(holster.sms_settings.interval, SECONDS),
(x, y) -> x)
.repeat(holster.sms_settings.repetitions_count))
?

Java RX, why this line is called twice and these 2 line never called

I am new to Java Rx, I don't know if that is a valid question or not.
I have function
public Single<PayResponse> pay(PayRequest apiRequest) {
return client.initiatePayment(apiRequest)
.doOnSuccess(initiatePaymentResponse -> {
System.out.println("first");
client.confirmPayment(initiatePaymentResponse.getPaymentId())
.doOnSuccess(confirmPaymentResponse -> {System.out.println("second");doConfirmationLogic(confirmPaymentResponse ))}
.doOnError(ex -> {System.out.println("thirs");ex.printStackTrace();logError(ex);});
})
.doOnError(ex -> {ex.printStackTrace();logError(ex);});
}
after executing this method i can find first was printed twice but neither second nor third was printed
It is odd behaviour for me, because i expect to find first and second or third.
Any idea ?

In order to start receiving the emitted value(s) from an observable (like a Single<T>), you must subscribe() to it first.
You are probably only subscribing to the Single returned by pay twice somewhere else, and that's why you see first printed two times. In the code you show, I can see that are not subscribing to any of the observable there, so nothing will happen afterwards.
If you want to chain observables, the most common choice would be to use the flatMap operator (there are other options as well).
In your case, it would look similar to this:
public Single<PayResponse> pay(PayRequest apiRequest) {
return client.initiatePayment(apiRequest)
.flatMap(initiatePaymentResponse -> {
System.out.println("first");
return client.confirmPayment(initiatePaymentResponse.getPaymentId();
})
.flatMap(confirmPaymentResponse -> {
System.out.println("second");
return doConfirmationLogic(confirmPaymentResponse);
})
.doOnSuccess(confirmationLogicResponse -> System.out.println("third"))
.doOnError(ex -> {
ex.printStackTrace();
logError(ex);
});
}
Then, you subscribe to the single returned by pay somewhere else like this:
...
pay(apiRequest)
.subscribe(onSuccesValue -> {
// The whole chain was successful and this is the value returned
// by the last observable in the chain (doConfirmationLogic in your case)
}, onError {
// There was an error at some point during the chain
}
...
I am supposing that all the methods initiatePayment, confirmPayment, doConfirmationLogic return Singles and that doConfirmationLogic ends up returning a Single<PayResponse>. If that's not the case, you will need to make some small changes, but you get the general idea of how chaining observables work.

Using reactor's Flux.buffer to batch work only works for single item

I'm trying to use Flux.buffer() to batch up loads from a database.
The use case is that loading records from a DB may be 'bursty', and I'd like to introduce a small buffer to group together loads where possible.
My conceptual approach has been to use some form of processor, publish to it's sink, let that buffer, and then subscribe & filter for the result I want.
I've tried multiple different approaches (different types of processors, creating the filtered Mono in different ways).
Below is where I've gotten so far - largely by stumbling.
Currently, this returns a single result, but subsequent calls are dropped (though I'm unsure of where).
class BatchLoadingRepository {
// I've tried all manner of different processors here. I'm unsure if
// TopicProcessor is the correct one to use.
private val bufferPublisher = TopicProcessor.create<String>()
private val resultsStream = bufferPublisher
.bufferTimeout(50, Duration.ofMillis(50))
// I'm unsure if concatMapIterable is the correct operator here,
// but it seems to work.
// I'm really trying to turn the List<MyEntity>
// into a stream of MyEntity, published on the Flux<>
.concatMapIterable { requestedIds ->
// this is a Spring Data repository. It returns List<MyEntity>
repository.findAllById(requestedIds)
}
// Multiple callers will invoke this method, and then subscribe to receive
// their entity back.
fun findByIdAsync(id: String): Mono<MyEntity> {
// Is there a potential race condition here, caused by a result
// on the resultsStream, before I've subscribed?
return Mono.create<MyEntity> { sink ->
bufferPublisher.sink().next(id)
resultsStream.filter { it.id == id }
.subscribe { next ->
sink.success(next)
}
}
}
}

Hi i was testing your code and i think the best way is to use EmitterProcessor shared. I did a test with emitterProcessor and it seems to work.
Flux<String> fluxi;
EmitterProcessor emitterProcessor;
#Override
public void run(String... args) throws Exception {
emitterProcessor = EmitterProcessor.create();
fluxi = emitterProcessor.share().bufferTimeout(500, Duration.ofMillis(500))
.concatMapIterable(o -> o);
Flux.range(0,1000)
.flatMap(integer -> findByIdAsync(integer.toString()))
.map(s -> {
System.out.println(s);
return s;
}).subscribe();
}
private Mono<String> findByIdAsync(String id) {
return Mono.create(monoSink -> {
fluxi.filter(s -> s == id).subscribe(value -> monoSink.success(value));
emitterProcessor.onNext(id);
});
}

Java Reactor - conditional stream execution

I was wondering how to create "logical stream" using Reactor.
Lets assume that I want to implement following scenario:
As input I have object to save in database. As output I would like to get Mono representing execution message.
Option 1: if object to save has all fields filled then I perform additionall operations, save it to database and finally return "Success" message
Option 2: if object to save has at least one field not filled I return "Error"
I have created such code:
Mono<String> message = Mono.just(new User("Bob the Reactor master")) // user with name = can be saved
.flatMap(user -> {
if(user.getName() != null && user.getName().length() > 1){
// Perform additional operations e.g. user.setCreatedDate(new Date())
// Save to repository e.g. repository.save(user)
return Mono.just("Success!");
}
else{
return Mono.just("Error!");
}
})
.doOnNext(System.out::println); // print stream result
message.subscribe();
Is this code 100% reactive (has all its benefits)? If no then what it will look like?

The answer depends on your commented repository.
Repository is non-blocking and returns Mono or Flux
You should subscribe it then return Success Mono. In your if statement:
return repository.save(user).then(Mono.just("Success!"));
Repository is blocking
You should make your repository call non-blocking moving its execution to separate thread. Reactor way is to wrap it with Mono and subscribe on elastic scheduler or your custom scheduler.
Mono<String> message = Mono.just(new User("Bob the Reactor master"))
.filter(user -> user.getName() != null && user.getName().length() > 1)
.map(user -> user) // Perform additional operations e.g. user.setCreatedDate(new Date())
.flatMap(user -> Mono.fromRunnable(() -> repository.save(user))
.subscribeOn(Schedulers.elastic())
.then(Mono.just("Success!")))
.switchIfEmpty(Mono.just("Error!"));

RxJava Combine Sequence Of Requests

The Problem
I have two Apis. Api 1 gives me a List of Items and Api 2 gives me more detailed Information for each of the items I got from Api 1. The way I solved it so far results in bad Performance.
The Question
Efficent and fast solution to this Problem with the help of Retrofit and RxJava.
My Approach
At the Moment my Solution Looks like this:
Step 1: Retrofit executes Single<ArrayList<Information>> from Api 1.
Step 2: I iterate through this Items and make a request for each to Api 2.
Step 3: Retrofit Returns Sequentially executes Single<ExtendedInformation> for
each item
Step 4: After all calls form Api 2 completely executed I create a new Object for all Items combining the Information and Extended Information.
My Code
public void addExtendedInformations(final Information[] informations) {
final ArrayList<InformationDetail> informationDetailArrayList = new ArrayList<>();
final JSONRequestRatingHelper.RatingRequestListener ratingRequestListener = new JSONRequestRatingHelper.RatingRequestListener() {
#Override
public void onDownloadFinished(Information baseInformation, ExtendedInformation extendedInformation) {
informationDetailArrayList.add(new InformationDetail(baseInformation, extendedInformation));
if (informationDetailArrayList.size() >= informations.length){
listener.onAllExtendedInformationLoadedAndCombined(informationDetailArrayList);
}
}
};
for (Information information : informations) {
getExtendedInformation(ratingRequestListener, information);
}
}
public void getRatingsByTitle(final JSONRequestRatingHelper.RatingRequestListener ratingRequestListener, final Information information) {
Single<ExtendedInformation> repos = service.findForTitle(information.title);
disposable.add(repos.subscribeOn(Schedulers.io()).observeOn(AndroidSchedulers.mainThread()).subscribeWith(new DisposableSingleObserver<ExtendedInformation>() {
#Override
public void onSuccess(ExtendedInformation extendedInformation) {
ratingRequestListener.onDownloadFinished(information, extendedInformation);
}
#Override
public void onError(Throwable e) {
ExtendedInformation extendedInformation = new ExtendedInformation();
ratingRequestListener.onDownloadFinished(extendedInformation, information);
}
}));
}
public interface RatingRequestListener {
void onDownloadFinished(Information information, ExtendedInformation extendedInformation);
}

tl;dr use concatMapEager or flatMap and execute sub-calls asynchronously or on a schedulers.
long story
I'm not an android developer, so my question will be limited to pure RxJava (version 1 and version 2).
If I get the picture right the needed flow is :
some query param
\--> Execute query on API_1 -> list of items
|-> Execute query for item 1 on API_2 -> extended info of item1
|-> Execute query for item 2 on API_2 -> extended info of item1
|-> Execute query for item 3 on API_2 -> extended info of item1
...
\-> Execute query for item n on API_2 -> extended info of item1
\----------------------------------------------------------------------/
|
\--> stream (or list) of extended item info for the query param
Assuming Retrofit generated the clients for
interface Api1 {
#GET("/api1") Observable<List<Item>> items(#Query("param") String param);
}
interface Api2 {
#GET("/api2/{item_id}") Observable<ItemExtended> extendedInfo(#Path("item_id") String item_id);
}
If the order of the item is not important, then it is possible to use flatMap only:
api1.items(queryParam)
.flatMap(itemList -> Observable.fromIterable(itemList)))
.flatMap(item -> api2.extendedInfo(item.id()))
.subscribe(...)
But only if the retrofit builder is configured with
Either with the async adapter (calls will be queued in the okhttp internal executor). I personally think this is not a good idea, because you don't have control over this executor.
.addCallAdapterFactory(RxJava2CallAdapterFactory.createAsync()
Or with the scheduler based adapter (calls will be scheduled on the RxJava scheduler). It would my preferred option, because you explicitly choose which scheduler is used, it will be most likely the IO scheduler, but you are free to try a different one.
.addCallAdapterFactory(RxJava2CallAdapterFactory.createWithScheduler(Schedulers.io()))
The reason is that flatMap will subscribe to each observable created by api2.extendedInfo(...) and merge them in the resulting observable. So results will appear in the order they are received.
If the retrofit client is not set to be async or set to run on a scheduler, it is possible to set one :
api1.items(queryParam)
.flatMap(itemList -> Observable.fromIterable(itemList)))
.flatMap(item -> api2.extendedInfo(item.id()).subscribeOn(Schedulers.io()))
.subscribe(...)
This structure is almost identical to the previous one execpts it indicates locally on which scheduler each api2.extendedInfo is supposed to run.
It is possible to tune the maxConcurrency parameter of flatMap to control how many request you want to perform at the same time. Although I'd be cautious on this one, you don't want run all queries at the same time. Usually the default maxConcurrency is good enough (128).
Now if order of the original query matter. concatMap is usually the operator that does the same thing as flatMap in order but sequentially, which turns out to be slow if the code need to wait for all sub-queries to be performed. The solution though is one step further with concatMapEager, this one will subscribe to observable in order, and buffer the results as needed.
Assuming retrofit clients are async or ran on a specific scheduler :
api1.items(queryParam)
.flatMap(itemList -> Observable.fromIterable(itemList)))
.concatMapEager(item -> api2.extendedInfo(item.id()))
.subscribe(...)
Or if the scheduler has to be set locally :
api1.items(queryParam)
.flatMap(itemList -> Observable.fromIterable(itemList)))
.concatMapEager(item -> api2.extendedInfo(item.id()).subscribeOn(Schedulers.io()))
.subscribe(...)
It is also possible to tune the concurrency in this operator.
Additionally if the Api is returning Flowable, it is possible to use .parallel that is still in beta at this time in RxJava 2.1.7. But then results are not in order and I don't know a way (yet?) to order them without sorting after.
api.items(queryParam) // Flowable<Item>
.parallel(10)
.runOn(Schedulers.io())
.map(item -> api2.extendedInfo(item.id()))
.sequential(); // Flowable<ItemExtended>

the flatMap operator is designed to cater to these types of workflows.
i'll outline the broad strokes with a simple five step example. hopefully you can easily reconstruct the same principles in your code:
#Test fun flatMapExample() {
// (1) constructing a fake stream that emits a list of values
Observable.just(listOf(1, 2, 3, 4, 5))
// (2) convert our List emission into a stream of its constituent values
.flatMap { numbers -> Observable.fromIterable(numbers) }
// (3) subsequently convert each individual value emission into an Observable of some
// newly calculated type
.flatMap { number ->
when(number) {
1 -> Observable.just("A1")
2 -> Observable.just("B2")
3 -> Observable.just("C3")
4 -> Observable.just("D4")
5 -> Observable.just("E5")
else -> throw RuntimeException("Unexpected value for number [$number]")
}
}
// (4) collect all the final emissions into a list
.toList()
.subscribeBy(
onSuccess = {
// (5) handle all the combined results (in list form) here
println("## onNext($it)")
},
onError = { error ->
println("## onError(${error.message})")
}
)
}
(incidentally, if the order of the emissions matter, look at using concatMap instead).
i hope that helps.

Check below it's working.
Say you have multiple network calls you need to make–cals to get Github user information and Github user events for example.
And you want to wait for each to return before updating the UI. RxJava can help you here.
Let’s first define our Retrofit object to access Github’s API, then setup two observables for the two network requests call.
Retrofit repo = new Retrofit.Builder()
.baseUrl("https://api.github.com")
.addConverterFactory(GsonConverterFactory.create())
.addCallAdapterFactory(RxJavaCallAdapterFactory.create())
.build();
Observable<JsonObject> userObservable = repo
.create(GitHubUser.class)
.getUser(loginName)
.subscribeOn(Schedulers.newThread())
.observeOn(AndroidSchedulers.mainThread());
Observable<JsonArray> eventsObservable = repo
.create(GitHubEvents.class)
.listEvents(loginName)
.subscribeOn(Schedulers.newThread())
.observeOn(AndroidSchedulers.mainThread());
Used Interface for it like below:
public interface GitHubUser {
#GET("users/{user}")
Observable<JsonObject> getUser(#Path("user") String user);
}
public interface GitHubEvents {
#GET("users/{user}/events")
Observable<JsonArray> listEvents(#Path("user") String user);
}
After we use RxJava’s zip method to combine our two Observables and wait for them to complete before creating a new Observable.
Observable<UserAndEvents> combined = Observable.zip(userObservable, eventsObservable, new Func2<JsonObject, JsonArray, UserAndEvents>() {
#Override
public UserAndEvents call(JsonObject jsonObject, JsonArray jsonElements) {
return new UserAndEvents(jsonObject, jsonElements);
}
});
Finally let’s call the subscribe method on our new combined Observable:
combined.subscribe(new Subscriber<UserAndEvents>() {
...
#Override
public void onNext(UserAndEvents o) {
// You can access the results of the
// two observabes via the POJO now
}
});
No more waiting in threads etc for network calls to finish. RxJava has done all that for you in zip().
hope my answer helps you.

I solved a similar problem with RxJava2. Execution of requests for Api 2 in parallel slightly speeds up the work.
private InformationRepository informationRepository;
//init....
public Single<List<FullInformation>> getFullInformation() {
return informationRepository.getInformationList()
.subscribeOn(Schedulers.io())//I usually write subscribeOn() in the repository, here - for clarity
.flatMapObservable(Observable::fromIterable)
.flatMapSingle(this::getFullInformation)
.collect(ArrayList::new, List::add);
}
private Single<FullInformation> getFullInformation(Information information) {
return informationRepository.getExtendedInformation(information)
.map(extendedInformation -> new FullInformation(information, extendedInformation))
.subscribeOn(Schedulers.io());//execute requests in parallel
}
InformationRepository - just interface. Its implementation is not interesting for us.
public interface InformationRepository {
Single<List<Information>> getInformationList();
Single<ExtendedInformation> getExtendedInformation(Information information);
}
FullInformation - container for result.
public class FullInformation {
private Information information;
private ExtendedInformation extendedInformation;
public FullInformation(Information information, ExtendedInformation extendedInformation) {
this.information = information;
this.extendedInformation = extendedInformation;
}
}

Try using Observable.zip() operator. It will wait until both Api calls are finished before continuing the stream. Then you can insert some logic by calling flatMap() afterwards.
http://reactivex.io/documentation/operators/zip.html