Assume that I have some subscriber implementation:
// SafeSubscriber extension doesn't matter here - the problem exists for simple Subscriber implementations too
class ParticularSubscriber<T> extends SafeSubscriber<T> {
private Subscriber<T> actual;
public ParticularSubscriber() {
super(Subscribers.create(System.out::println));
}
}
Then, I need to create an observer that performs some extra configurations depending on the subscriber passed. Naive approach first:
Observable<String> o = Observable.<String>create(subscriber -> {
if(subscriber instanceof ParticularSubscriber) {
// do some extra logic here.
}
});
It is successfully works if we directly subscribe to the Observable o:
o.subscribe(new ParticularSubscriber<>());
But things changed if we apply some operations on it:
o.map(str -> str + 1)
.filter(str -> str != "")
.subscribe(new ParticularSubscriber<>());
In the latter case, some wrapper is passed to OnSubscribe. Deeply inside this wrapper there is my initial ParticularSubscriber, but I have no ability to get to it.
Is there any way to access initially passed subscriber in the observer's callbacks?
Related
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);
});
}
I have a remote call(retrofit) - which I converted into an Observable. Let's call it Observable Y.
Now, I also have a certain code that looks for geo location with GPS and NETWORK providers. I have a Timer there, that basically limits the time that the geo search can be performed for. Let's call it Task X. I want to convert it into an Observable X.
Then, I want to have a subcription, that will perform Observable X(that is, find location), once it will return a Location, I will "analyze" in a certain way, and then I will either pass that Location into the Observable Y(the retrofit call), or simply quit(if that "raw" location will be enough in my case)
At ALL time, I want to be able to interrupt all that "process". From what I gather, I can achieve that by simply unsubscribing the subscription, right?
and then next time just subscribe this subscription once again in the future.
Questions:
1. Can all of that be implemented via RxJava/RxAndroid ?
2. Does it even make sense implementing it with Rx ? or is there a more efficient way?
3. How is it done with Rx?
(More specifically : (a) How do I convert task Y into an Observable Y?
(b) How do I perform them in sequence with only one subscription?)
1- It can be implemented via RxJava
2- This is your best option so far
3-
3-a Observable.fromCallable() does the trick
3-b flatmap operator is used to chain observable calls
you can proceed like this:
private Location searchForLocation() {
// of course you will return not null location
return null;
}
// your task X
//mock your location fetching
private Observable<Location> getLocationObservableX() {
return Observable.fromCallable(() -> searchForLocation());
}
//your task Y
//replace CustomData with simple String
//just to mock your asynchronous retrofit call
private Observable<List<String>> getRetrofitCallObservableY(String param){
return Observable.just(new ArrayList<String>());
}
//subscribe
private void initialize() {
getLocationObservableX()
.filter(location -> {
//place your if else here
//condition
//don't continue tu retrofit
boolean condition = false;
if (condition) {
//process
//quit and pass that Location in Broadcas
//you shall return false if you don't want to continue
return false;
}
return true;
})
//filter operation does not continue here if you return false
.flatMap(location -> getRetrofitCallObservableY("param"))
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe(response -> {
//do what you want with response
});
}
The application i'm writing performs an initial API call with Retrofit which returns a URL. That response is then .flatMap'd into another API call depending on the text contained in the URL. However, the two secondary API calls are defined to return different response models.
To make things clearer, here is some code:
APIService service = retrofit.create(APIService.class);
service.getURL() // returns response model containing a URL.
.flatMap(new Function<GetURLResponse, ObservableSource<?>>() {
#Override
public ObservableSource<?> apply(GetURLResponse getURLResponse) throws Exception {
// Determine whether the returned url is for "first.com".
if (getURLResponse.url.contains("first.com")) {
return service.first(getURLResponse.url);
}
// Otherwise, the URL is not for "first.com", so use our other service method.
return service.second(getURLResponse.url);
}
})
Here are the interface definitions for service.first() and service.second():
#GET
Observable<retrofit2.Response<ResponseBody>> first(#Url String url);
#GET
Observable<SecondModel> second(#Url String url);
How can I better handle these two different possible types (retrofit2.Response<ResponseBody> and SecondModel) for the rest of the stream? Eg. If the initial URL contains first.com then the service.first() API call should fire, and operators down the stream should received a retrofit2.Response<ResponseBody>. Conversely, if the initial URL does not contain first.com, the service.second() API call should fire and operators down the stream should receive a SecondModel.
The easiest way would be to have both your model classes implement an interface and return that interface, alternatively the models could both extend an abstract class to achieve the same effect. You would then do an instanceOf check to see which model it is and continue with your preferred transformations.
That having said you mentioning downstream operators, makes me think that this would cause an annoying amount of checks. So what I would do is split the stream using the publish operator, and then apply your further transformations to each sub-stream. Finally you should merge the two streams back together and return a single model encompassing both models.
Below a code example to get you started.
Observable<Integer> fooObservableSecondaryRequest(String foo) {
return Observable.just(1);
}
Observable<Integer> booObservableSecondaryRequest(String boo) {
return Observable.just(2);
}
Observable<String> stringObservable = Observable.just("foo", "boo");
stringObservable.publish(shared -> Observable.merge(
shared.filter(a -> a.equals("foo"))
.flatMap(fooString -> fooObservableSecondaryRequest(fooString))
.map(num -> num * 2),
shared.filter(a -> a.equals("boo"))
.flatMap(booString -> booObservableSecondaryRequest(booString))
.map(num -> num * 10)
)).subscribe(result -> System.out.println(result)); // will print 2 and 20
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
I'm having a hard time understanding some component in RxJava and how they work.
I have these code based on how to implement Repository Pattern with RxJava:
private Observable<String> getData(boolean refresh) {
Observable<String> a = Observable.concat(getCache(), getNetwork());
if(!refresh) {
a.first(s -> s.equals("cache"));
}
return a;
}
private Observable<String> getCache() {
return Observable.just("cache");
}
private Observable<String> getNetwork() {
return Observable.just("network");
}
And I called the function:
getData(false).subscribe(s -> Log.d("Not Refresh", s));
getData(true).subscribe(s -> Log.d("Refresh", s));
// Both of them print this:
// cache
// network
Which doesn't right because I applied first() function when refresh = true.
Then, I thought maybe first() operator didn't reflect to the original object; so I re-assign it back.
if(!refresh) {
a = a.first(s -> s.equals("cache"));
}
Then it worked like I wanted to and print these lines:
// Not Refresh cache
// Refresh cache
// Refresh network
I moved on and learn on another thing, RxBus. My code:
private ReplaySubject<Object> subject = ReplaySubject.create();
private <T> Observable<T> subscribe(Class<T> desiredClass) {
return subject
.filter(item -> item.getClass().equals(desiredClass)) // Note this line
.map(item -> (T) item);
}
private <T> void post(T item) {
subject.onNext(item); // This one too
}
Called the functions with these:
sub(String.class).subscribe(s -> Log.d("Sub String", s));
sub(Integer.class).subscribe(s -> Log.d("Sub Integer", s + ""));
post("String A");
post(5);
// Result:
// Sub String A
// Sub Integer 5
When I call sub(), it applied filter() and map() operators and return it. In my understanding the original subject is not changed, then why does invoking subject.onNext() also invoke the modified object returned in the sub()?
Does it have anything to do with Subject? Or my understanding of RxJava is completely wrong here?
You miss one thing: Subject is both an Observable and Observer.
Subject will act like an Observable when you call Observable's methods (e.g., filter, map), and it will return a new Observable without changing the original one.
However, Subject will act like an Observer when you call Observer's methods (e.g., onNext, onCompleted, onError), and you will see side effects of these methods.