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Mutiny - How to group items to send request by blocks

I'm using Mutiny extension (for Quarkus) and I don't know how to manage this problem.
I want to send many request in an async way so I've read about Mutiny extension. But the server closes the connection because it receives thousand of them.
So I need:
Send the request by blocks
After all request are sent, do things.
I've been using Uni object to combine all the responses as this:
Uni<Map<Integer, String>> uniAll = Uni.combine()
.all()
.unis(list)
.combinedWith(...);
And then:
uniAll.subscribe()
.with(...);
This code, send all the request in paralell so the server closes the connection.
I'm using group of Multi objects, but I don't know how to use it (in Mutiny docs I can't found any example).
This is the way I'm doing now:
//Launch 1000 request
for (int i=0;i<1000;i++) {
multi = client.getAbs("https://api.*********.io/jokes/random")
.as(BodyCodec.jsonObject())
.send()
.onItem().transformToMulti(
array -> Multi.createFrom()
.item(array.body().getString("value")))
.group()
.intoLists()
.of(100)
.subscribe()
.with(a->{
System.out.println("Value: "+a);
});
}
I think that the subscription doesn't execute until there are "100" groups of items, but I guess this is not the way because it doesn't work.
Does anybody know how to launch 1000 of async requests in blocks of 100?
Thanks in advance.
UPDATED 2021-04-19
I've tried with this approach:
List<Uni<String>> listOfUnis = new ArrayList<>();
for (int i=0;i<1000;i++) {
listOfUnis.add(client
.getAbs("https://api.*******.io/jokes/random")
.as(BodyCodec.jsonObject())
.send()
.onItem()
.transform(item -> item
.body()
.getString("value")));
}
Multi<Uni<String>> multiFormUnis = Multi.createFrom()
.iterable(listOfUnis);
List<String> listOfResponses = new ArrayList<>();
List<String> listOfValues = multiFormUnis.group()
.intoLists()
.of(100)
.onItem()
.transformToMultiAndConcatenate(listOfOneHundred ->
{
System.out.println("Size: "+listOfOneHundred.size());
for (int index=0;index<listOfOneHundred.size();index++) {
listOfResponses.add(listOfOneHundred.get(index)
.await()
.indefinitely());
}
return Multi.createFrom()
.iterable(listOfResponses);
})
.collectItems()
.asList()
.await()
.indefinitely();
for (String value : listOfValues) {
System.out.println(value);
}
When I put this line:
listOfResponses.add(listOfOneHundred.get(index)
.await()
.indefinitely());
The responses are printed one after each other, and when the first 100s group of items ends, it prints the next group. The problem? There are sequential requests and it takes so much time
I think I am close to the solution, but I need to know, how to send the parallel request only in group of 100s, because if I put:
subscribe().with()
All the request are sent in parallel (and not in group of 100s)

I think you create the multy wrong, it would be much easier to use this:
Multi<String> multiOfJokes = Multi.createFrom().emitter(multiEmitter -> {
for (int i=0;i<1000;i++) {
multiEmitter.emit(i);
}
multiEmitter.complete();
}).onItem().transformToUniAndMerge(index -> {
return Uni.createFrom().item("String" + index);
})
With this approach it should mace the call parallel.
Now is the question of how to make it to a list.
The grouping works fine
I run it with this code:
Random random = new Random();
Multi<Integer> multiOfInteger = Multi.createFrom().emitter(multiEmitter -> {
for (Integer i=0;i<1000;i++) {
multiEmitter.emit(i);
}
multiEmitter.complete();
});
Multi<String> multiOfJokes = multiOfInteger.onItem().transformToUniAndMerge(index -> {
if (index % 10 == 0 ) {
Duration delay = Duration.ofMillis(random.nextInt(100) + 1);
return Uni.createFrom().item("String " + index + " delayed").onItem()
.delayIt().by(delay);
}
return Uni.createFrom().item("String" + index);
}).onCompletion().invoke(() -> System.out.println("Completed"));
Multi<List<String>> multiListJokes = multiOfJokes
.group().intoLists().of(100)
.onCompletion().invoke(() -> System.out.println("Completed"))
.onItem().invoke(strings -> System.out.println(strings));
multiListJokes.collect().asList().await().indefinitely();
You will get a list of your string.
I don't know, how you intend to send the list to backend.
But you can either to it with:
call (executed asynchronously)
write own subscriber (implements Subscriber) the methods are straight forward.
As you need for your bulk request.
I hope you understand it better afterward.
PS: link to guide where I learned all of it:
https://smallrye.io/smallrye-mutiny/guides

So in short you want to batch parallel calls to the server, without hitting it with everything at once.
Could this work for you? It uses merge. In my example, it has a parallelism of 2.
Multi.createFrom().range(1, 10)
.onItem()
.transformToUni(integer -> {
return <<my long operation Uni>>
})
.merge(2) //this is the concurrency
.collect()
.asList();
I'm not sure if merge was added later this year, but this seems to do what you want. In my example, the "long operation producing Uni" is actually a call to the Microprofile Rest Client which produces a Uni, and returns a string. After the merge you can put another onItem to perform something with the response (it's a plain Multi after the merge), instead of collecting everything as list.

Java - sync call inside async thenCompose

Consider below code as I am not able to find better words to ask the question:
CompletionStage<Manager> callingAsyncFunction(int developerId) {
return getManagerIdByDeveloperId(developerId)
.thenCompose(id ->
getManagerById(id, mandatoryComputationToGetManager(id)))
}
mandatoryComputationToGetManager() returns a CompletionStage
Now the doubt which I have is :
I wanted to call mandatoryComputationToGetManager() and after its computation I want getManagerById(...) to be called.
I know there can be one way i.e. calling thenCompose() first to do mandatoryComputationToGetManager() and then do another thenCompose() on previous result for getManagerById(). But I wanted to figure out if there is a way without piping one thenCompose() o/p to another by which I can hold until mandatoryComputationToGetManager() result is ready.
As far as I understand, in the above code getManagerById() will get called even if the result is not yet ready from mandatoryComputationToGetManager(), which I want to wait for so that once mandatoryComputationToGetManager() give the result getManagerById() should get computed asynchronously.

Ideally, we should pipe one thenCompose o/p to another, but there is a way by which we can achieve what you are trying to do.
CompletionStage<String> callingAsyncFunction(int developerId) {
return getManagerIdByDeveloperId(developerId)
.thenCompose(id -> getManagerById(id, mandatoryComputationToGetManager()));
}
private CompletionStage<String> getManagerById(
Integer id, CompletionStage<String> stringCompletionStage) {
return stringCompletionStage.thenApply(__ -> "test");
}
private CompletionStage<String> mandatoryComputationToGetManager() {
return CompletableFuture.completedFuture("test");
}

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

RxJava sorted output from parallell computation

I have a list of tasks I want to perform in parallell, but I want to display the result of the tasks in the same order as the original list.
In other words, if I have task list [A,B,C], I do not wish to show B-result before I have shown A-result, but nor do I want to wait until A-task is finished before starting B-task.
Additionally, I want to show each result as soon as possible, in other words, if the tasks finish in the order B, then A, then C, I do not want to show anything when I receive B-result, then show A-result immediately followed by B-result when I receive A-result, then show C-result whenever I receive it.
This is of course not terribly tricky to do by making an Observable for each task, combining them with merge, and subscribing on a computation thread pool, then writing a Subscriber which holds a buffer for any results received out of order. However, the Rx rule of thumb tends to be "there's already an operator for that", so the question is "what is the proper RxJava way to solve this?" if indeed there is such a thing.

It seems you need concatEager for this task but it is somewhat possible to achieve it with pre 1.0.15 tools and no need for "creating" Observables. Here is an example for that:
Observable<Long> source1 = Observable.interval(100, 100, TimeUnit.MILLISECONDS).take(10);
Observable<Long> source2 = Observable.interval(100, 100, TimeUnit.MILLISECONDS).take(20);
Observable<Long> source3 = Observable.interval(100, 100, TimeUnit.MILLISECONDS).take(15);
Observable<Observable<Long>> sources = Observable.just(source1, source2, source3);
sources.map(v -> {
Observable<Long> c = v.cache();
c.subscribe(); // to cache all
return c;
})
.onBackpressureBuffer() // make sure all source started
.concatMap(v -> v)
.toBlocking()
.forEach(System.out::println);
The drawback is that it retains all values for the whole duration of the sequence. This can be fixed with a special kind of Subject: UnicastSubject but RxJava 1.x doesn't have one and may not get one "officially". You can, however, look at one of my blog posts and build if for yourself and have the following code:
//...
sources.map(v -> {
UnicastSubject<Long> subject = UnicastSubject.create();
v.subscribe(subject);
return subject;
})
//...

"There's not quite an operator for that". Although, in the 1.0.15-SNAPSHOT build there is an experimental concatEagar() operator those sounds like it does what you're looking for. Pull request for concatEager
repositories {
maven { url 'https://oss.jfrog.org/libs-snapshot' }
}
dependencies {
compile 'io.reactivex:rxjava:1.0.15-SNAPSHOT'
}
If you want to roll your own temporary solution until concatEager() gets the nod of approval. You could try something like this:
public Observable<Result> concatEager(final Observable<Result> taskA, final Observable<Result> taskB, final Observable<Result> taskC) {
return Observable
.create(subscriber -> {
final Observable<Result> taskACached = taskA.cache();
final Observable<Result> taskBCached = taskB.cache();
final Observable<Result> taskCCached = taskC.cache();
// Kick off all the tasks simultaneously.
subscriber.add(
Observable
.merge(taskACached, taskBCached, taskCCached)
.subscribe(
result -> { // Throw away result
},
throwable -> { // Ignore errors
}
)
);
// Put the results in order.
subscriber.add(
Observable
.concat(taskACached, taskBCached, taskCCached)
.subscribe(subscriber)
);
});
}
Note that the above code is totally untested. There are probably better ways to do this but this is what first came to mind...

Make two requests in worker verticle and merge response from two requests

I have vertx server application where I am getting single client requests and from the server, I need to make two blocking calls. For instance, one call to back-end system A and another call to back-end system B. I am looking to make two concurrent calls to both the systems. I need to wait for the responses from both the calls and then merge two data from both the calls and then send the response back to client. I am unable to figure out how to do this in worker verticle.
Could anyone recommend what would be the best approach in vertx?

This sounds like a good use case for Promises. Give the module vertx-promises a try.

create a CompositeFuture from your launched Futures and handle it normally.
public Future<JsonArray> getEntitiesByIndFields(String keyspace, String entidad, String field1, String field2) {
Promise<JsonArray> p = Promise.promise();
// launch in parallel
Future<JsonArray> f1 = getEntitiesByIndField1(keyspace, entidad, field1);
Future<JsonArray> f2 = getEntitiesByIndField2(keyspace, entidad, field2);
CompositeFuture.all(f1, f2).setHandler(done ->
{
if (done.failed()) {
p.fail(done.cause());
return;
}
List<JsonArray> ja = done.result().list();
JsonArray finalarray = ja.get(0);
ja.get(1).forEach(jo ->
{ // add one by one, don't duplicate ids
long id = ((JsonObject) jo).getLong("id");
if (!containsKey(finalarray, id)) {
finalarray.add(jo);
}
});
;
p.complete(finalarray); // send union of founds
});
return p.future();
}