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When should one use RxJava Observable and when simple Callback on Android?

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When should I use RxJava?

RxJava provides a standard workflow that is used to manage all data and events across the application like Create an Observable> Give the Observable some data to emit> Create an Observer> Subscribe the Observer to the Observable. RxJava is becoming more and more popular particularly for Android developers.

Why do we use RxJava in Android?

RxJava is a Java library that enables Functional Reactive Programming in Android development. It raises the level of abstraction around threading in order to simplify the implementation of complex concurrent behavior.

What is difference between Observable and observer in Android?

An observable object can have one or more observers. An observer may be any object that implements interface Observer . After an observable instance changes, an application calling the Observable 's notifyObservers method causes all of its observers to be notified of the change by a call to their update method.

What is difference between RxJava and LiveData?

The RxJava's approach to choose a thread during the subscription, not in time of the sending is much more appropriate. Actually the only advantage of LiveData over RxJava we have noticed is they automatically subscribe and unsubscribe on Activity life cycle events (or over android components implementing life cycle).


For simple networking stuff, the advantages of RxJava over Callback is very limited. The simple getUserPhoto example:

RxJava:

api.getUserPhoto(photoId)
    .observeOn(AndroidSchedulers.mainThread())
    .subscribe(new Action1<Photo>() {
            @Override
            public void call(Photo photo) {
               // do some stuff with your photo 
            }
     });

Callback:

api.getUserPhoto(photoId, new Callback<Photo>() {
    @Override
    public void onSuccess(Photo photo, Response response) {
    }
});

The RxJava variant is not much better than the Callback variant. For now, let's ignore the error handling. Let's take a list of photos:

RxJava:

api.getUserPhotos(userId)
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.flatMap(new Func1<List<Photo>, Observable<Photo>>() {
    @Override
    public Observable<Photo> call(List<Photo> photos) {
         return Observable.from(photos);
    }
})
.filter(new Func1<Photo, Boolean>() {
    @Override
    public Boolean call(Photo photo) {
         return photo.isPNG();
    }
})
.subscribe(
    new Action1<Photo>() {
    @Override
        public void call(Photo photo) {
            list.add(photo)
        }
    });

Callback:

api.getUserPhotos(userId, new Callback<List<Photo>>() {
    @Override
    public void onSuccess(List<Photo> photos, Response response) {
        List<Photo> filteredPhotos = new ArrayList<Photo>();
        for(Photo photo: photos) {
            if(photo.isPNG()) {
                filteredList.add(photo);
            }
        }
    }
});

Now, the RxJava variant still isn't smaller, although with Lambdas it would be getter closer to the Callback variant. Furthermore, if you have access to the JSON feed, it would be kind of weird to retrieve all photos when you're only displaying the PNGs. Just adjust the feed to it only displays PNGs.

First conclusion

It doesn't make your codebase smaller when you're loading a simple JSON that you prepared to be in the right format.

Now, let's make things a bit more interesting. Let's say you not only want to retrieve the userPhoto, but you have an Instagram-clone, and you want to retrieve 2 JSONs: 1. getUserDetails() 2. getUserPhotos()

You want to load these two JSONs in parallel, and when both are loaded, the page should be displayed. The callback variant will become a bit more difficult: you have to create 2 callbacks, store the data in the activity, and if all the data is loaded, display the page:

Callback:

api.getUserDetails(userId, new Callback<UserDetails>() {
    @Override
    public void onSuccess(UserDetails details, Response response) {
        this.details = details;
        if(this.photos != null) {
            displayPage();
        }
    }
});

api.getUserPhotos(userId, new Callback<List<Photo>>() {
    @Override
    public void onSuccess(List<Photo> photos, Response response) {
        this.photos = photos;
        if(this.details != null) {
            displayPage();
        }
    }
});

RxJava:

private class Combined {
    UserDetails details;
    List<Photo> photos;
}


Observable.zip(api.getUserDetails(userId), api.getUserPhotos(userId), new Func2<UserDetails, List<Photo>, Combined>() {
            @Override
            public Combined call(UserDetails details, List<Photo> photos) {
                Combined r = new Combined();
                r.details = details;
                r.photos = photos;
                return r;
            }
        }).subscribe(new Action1<Combined>() {
            @Override
            public void call(Combined combined) {
            }
        });

We are getting somewhere! The code of RxJava is now as big as the callback option. The RxJava code is more robust; Think of what would happen if we needed a third JSON to be loaded (like the latest Videos)? The RxJava would only need a tiny adjustment, while the Callback variant needs to be adjusted in multiple places (on each callback we need to check if all data is retrieved).

Another example; we want to create an autocomplete field, which loads data using Retrofit. We don't want to do a webcall every time an EditText has a TextChangedEvent. When typing fast, only the last element should trigger the call. On RxJava we can use the debounce operator:

inputObservable.debounce(1, TimeUnit.SECONDS).subscribe(new Action1<String>() {
            @Override
            public void call(String s) {
                // use Retrofit to create autocompletedata
            }
        });

I won't create the Callback variant but you will understand this is much more work.

Conclusion: RxJava is exceptionally good when data is sent as a stream. The Retrofit Observable pushes all elements on the stream at the same time. This isn't particularly useful in itself compared to Callback. But when there are multiple elements pushed on the stream and different times, and you need to do timing-related stuff, RxJava makes the code a lot more maintainable.


The Observable stuff is already done in Retrofit, so the code could be this:

api.getUserPhoto(photoId)
    .observeOn(AndroidSchedulers.mainThread())
    .subscribe(new Action1<Photo>() {
         @Override
            public void call(Photo photo) {
                //save photo?
            }
     });

In the case of getUserPhoto() the advantages for RxJava aren't great. But let's take another example when you'll get all the photos for a user, but only when the image is PNG, and you don't have access to the JSON to do the filtering on the serverside.

api.getUserPhotos(userId)
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.flatMap(new Func1<List<Photo>, Observable<Photo>>() {
    @Override
    public Observable<Photo> call(List<Photo> photos) {
         return Observable.from(photos);
    }
})
.filter(new Func1<Photo, Boolean>() {
    @Override
    public Boolean call(Photo photo) {
         return photo.isPNG();
    }
})
.subscribe(
    new Action1<Photo>() {
    @Override
        public void call(Photo photo) {
            // on main thread; callback for each photo, add them to a list or something.
            list.add(photo)
        }
    }, 
    new Action1<Throwable>() {
    @Override
        public void call(Throwable throwable) {
            // on main thread; something went wrong
            System.out.println("Error! " + throwable);
        }
    }, 
    new Action0() {
        @Override
        public void call() {
            // on main thread; all photo's loaded, time to show the list or something.
        }
    });

Now the JSON returns a list of Photo's. We'll flatMap them to individual items. By doing so, we'll be able to use the filter method to ignore photos which are not PNG. After that, we'll subscribe, and get a callback for each individual photo, an errorHandler, and a callback when all rows have been completed.

TLDR Point here being; the callback only returns you a callback for succes and failure; the RxJava Observable allows you to do map, reduce, filter and many more stuff.


With rxjava you can do more things with less code.

Let´s assume that you want to implement instant search in your app. With callbacks you have worried about unsubscribing the previous request and subscribe to the new one, handle orientation change yourself... I think it´s a lot of code and too verbose.

With rxjava is very simple.

public class PhotoModel{
  BehaviorSubject<Observable<Photo>> subject = BehaviorSubject.create(...);

  public void setUserId(String id){
   subject.onNext(Api.getUserPhoto(photoId));
  }

  public Observable<Photo> subscribeToPhoto(){
    return Observable.switchOnNext(subject);
  }
}

if you want to implement instant search you only have to listen for TextChangeListener and call to photoModel.setUserId(EditText.getText());

In onCreate method of Fragment or activity you subscribe to the Observable that returns photoModel.subscribeToPhoto(), it returns an Observable that always emit the items emited by the latest Observable(request).

AndroidObservable.bindFragment(this, photoModel.subscribeToPhoto())
                 .subscribe(new Action1<Photo>(Photo photo){
      //Here you always receive the response of the latest query to the server.
                  });

Also, if PhotoModel is a Singleton, for instance, you don't need to worry about orientation changes, because BehaviorSubject emits the last server response, regardless of when you subscribe.

With this lines of code we have implemented an instant search and handle orientation changes. Do you think that you can implement this with callbacks with less code? I doubt it.


We usually go with the following logic:

  1. If it's a simple one-response call, then Callback or Future is better.
  2. If it's a call with multiple responses (stream), or when there are complex interaction between different calls (see @Niels' answer), then Observables are better.

By the samples and conclusions in other answers, I think there is no big difference for simple one or two-steps tasks. However, Callback is simple and straightforward. RxJava is more complicated and too big for simple task. There is the third solution by: AbacusUtil. Let me implement above use cases with all three solutions: Callback, RxJava, CompletableFuture(AbacusUtil) with Retrolambda:

Fetch photo from network and save/display on device:

// By Callback
api.getUserPhoto(userId, new Callback<Photo>() {
    @Override
    public void onResponse(Call<Photo> call, Response<Photo> response) {
        save(response.body()); // or update view on UI thread.
    }

    @Override
    public void onFailure(Call<Photo> call, Throwable t) {
        // show error message on UI or do something else.
    }
});

// By RxJava
api.getUserPhoto2(userId) //
        .observeOn(AndroidSchedulers.mainThread())
        .subscribe(photo -> {
            save(photo); // or update view on UI thread.
        }, error -> {
            // show error message on UI or do something else.
        });

// By Thread pool executor and CompletableFuture.
TPExecutor.execute(() -> api.getUserPhoto(userId))
        .thenRunOnUI((photo, error) -> {
            if (error != null) {
                // show error message on UI or do something else.
            } else {
                save(photo); // or update view on UI thread.
            }
        });

Load user details and photo in parallel

// By Callback
// ignored because it's little complicated

// By RxJava
Observable.zip(api.getUserDetails2(userId), api.getUserPhoto2(userId), (details, photo) -> Pair.of(details, photo))
        .subscribe(p -> {
            // Do your task.
        });

// By Thread pool executor and CompletableFuture.
TPExecutor.execute(() -> api.getUserDetails(userId))
          .runOnUIAfterBoth(TPExecutor.execute(() -> api.getUserPhoto(userId)), p -> {
    // Do your task
});