I have a data source service, which takes an observer as a parameter.
void subscribe(Consumer onEventConsumer);
I want to use flux as a response stream for RSocket.
How can I do this?
As I see it now, it should be something like
Flux<T> controllerMethod(RequestMessage mgs) {
var flux = Flux.empty();
dataSource.subscribe(event -> flux.push(event));
return flux;
}
But I have big doubts that it's a proper solution, and I'm new in the reactive approach, I don't know what methods I should use here?
As Simon already pointed out, this is what you use Flux.create for.
Take a look at the Getting Started Guide on projectreactor.io.
In short, you register a custom listener inside the lambda of the create method:
Flux<String> bridge = Flux.create(sink -> {
myEventProcessor.register(
new MyEventListener<String>() {
public void onDataChunk(List<String> chunk) {
for(String s : chunk) {
sink.next(s);
}
}
public void processComplete() {
sink.complete();
}
});
});
What you want to do is to pass the incoming elements on to a FluxSink, which will then publish those elements on the Flux.
this is a typical use case of Flux.create. you register an obsereer from inside the create lambda, which will pass the data it receives down to the provided FluxSink
(Disclaimer: There are a ton of questions which arise from people asking about data being null/incorrect when using asynchronous operations through requests such as facebook,firebase, etc. My intention for this question was to provide a simple answer for that problem to everyone starting out with asynchronous operations in android)
I'm trying to get data from one of my operations, when I debug it using breakpoints or logs, the values are there, but when I run it they are always null, how can I solve this ?
Firebase
firebaseFirestore.collection("some collection").get()
.addOnSuccessListener(new OnSuccessListener<QuerySnapshot>() {
#Override
public void onSuccess(QuerySnapshot documentSnapshots) {
//I want to return these values I receive here...
});
//...and use the returned value here.
Facebook
GraphRequest request = GraphRequest.newGraphPathRequest(
accessToken,
"some path",
new GraphRequest.Callback() {
#Override
public void onCompleted(GraphResponse response) {
//I want to return these values I receive here...
}
});
request.executeAsync();
//...and use the returned value here.
Kotlin coroutine
var result: SomeResultType? = null
someScope.launch {
result = someSuspendFunctionToRetrieveSomething()
//I want to return the value I received here...
}
Log.d("result", result.toString()) //...but it is still null here.
Etc.
What is a Synchronous/Asynchronous operation ?
Well, Synchronous waits until the task has completed. Your code executes "top-down" in this situation.
Asynchronous completes a task in the background and can notify you when it is complete.
If you want to return the values from an async operation through a method/function, you can define your own callbacks in your method/function to use these values as they are returned from these operations.
Here's how for Java
Start off by defining an interface :
interface Callback {
void myResponseCallback(YourReturnType result);//whatever your return type is: string, integer, etc.
}
next, change your method signature to be like this :
public void foo(final Callback callback) { // make your method, which was previously returning something, return void, and add in the new callback interface.
next up, wherever you previously wanted to use those values, add this line :
callback.myResponseCallback(yourResponseObject);
as an example :
#Override
public void onSuccess(QuerySnapshot documentSnapshots) {
// create your object you want to return here
String bar = document.get("something").toString();
callback.myResponseCallback(bar);
})
now, where you were previously calling your method called foo:
foo(new Callback() {
#Override
public void myResponseCallback(YourReturnType result) {
//here, this result parameter that comes through is your api call result to use, so use this result right here to do any operation you previously wanted to do.
}
});
}
How do you do this for Kotlin ?
(as a basic example where you only care for a single result)
start off by changing your method signature to something like this:
fun foo(callback:(YourReturnType) -> Unit) {
.....
then, inside your asynchronous operation's result :
firestore.collection("something")
.document("document").get()
.addOnSuccessListener {
val bar = it.get("something").toString()
callback(bar)
}
then, where you would have previously called your method called foo, you now do this :
foo() { result->
// here, this result parameter that comes through is
// whatever you passed to the callback in the code aboce,
// so use this result right here to do any operation
// you previously wanted to do.
}
// Be aware that code outside the callback here will run
// BEFORE the code above, and cannot rely on any data that may
// be set inside the callback.
if your foo method previously took in parameters :
fun foo(value:SomeType, callback:(YourType) -> Unit)
you simply change it to :
foo(yourValueHere) { result ->
// here, this result parameter that comes through is
// whatever you passed to the callback in the code aboce,
// so use this result right here to do any operation
// you previously wanted to do.
}
these solutions show how you can create a method/function to return values from async operations you've performed through the use of callbacks.
However, it is important to understand that, should you not be interested in creating a method/function for these:
#Override
public void onSuccess(SomeApiObjectType someApiResult) {
// here, this `onSuccess` callback provided by the api
// already has the data you're looking for (in this example,
// that data would be `someApiResult`).
// you can simply add all your relevant code which would
// be using this result inside this block here, this will
// include any manipulation of data, populating adapters, etc.
// this is the only place where you will have access to the
// data returned by the api call, assuming your api follows
// this pattern
})
There's a particular pattern of this nature I've seen repeatedly, and I think an explanation of what's happening would help. The pattern is a function/method that calls an API, assigning the result to a variable in the callback, and returns that variable.
The following function/method always returns null, even if the result from the API is not null.
Kotlin
fun foo(): String? {
var myReturnValue: String? = null
someApi.addOnSuccessListener { result ->
myReturnValue = result.value
}.execute()
return myReturnValue
}
Kotlin coroutine
fun foo(): String? {
var myReturnValue: String? = null
lifecycleScope.launch {
myReturnValue = someApiSuspendFunction()
}
return myReturnValue
}
Java 8
private String fooValue = null;
private String foo() {
someApi.addOnSuccessListener(result -> fooValue = result.getValue())
.execute();
return fooValue;
}
Java 7
private String fooValue = null;
private String foo() {
someApi.addOnSuccessListener(new OnSuccessListener<String>() {
public void onSuccess(Result<String> result) {
fooValue = result.getValue();
}
}).execute();
return fooValue;
}
The reason is that when you pass a callback or listener to an API function, that callback code will only be run some time in the future, when the API is done with its work. By passing the callback to the API function, you are queuing up work, but the current function (foo() in this case) returns immediately before that work begins and before that callback code is run.
Or in the case of the coroutine example above, the launched coroutine is very unlikely to complete before the function that started it.
Your function that calls the API cannot return the result that is returned in the callback (unless it's a Kotlin coroutine suspend function). The solution, explained in the other answer, is to make your own function take a callback parameter and not return anything.
Alternatively, if you're working with coroutines, you can make your function suspend instead of launching a separate coroutine. When you have suspend functions, somewhere in your code you must launch a coroutine and handle the results within the coroutine. Typically, you would launch a coroutine in a lifecycle function like onCreate(), or in a UI callback like in an OnClickListener.
Other answer explains how to consume APIs based on callbacks by exposing a similar callbacks-based API in the outer function. However, recently Kotlin coroutines become more and more popular, especially on Android and while using them, callbacks are generally discouraged for such purposes. Kotlin approach is to use suspend functions instead. Therefore, if our application uses coroutines already, I suggest not propagating callbacks APIs from 3rd party libraries to the rest of our code, but converting them to suspend functions.
Converting callbacks to suspend
Let's assume we have this callback API:
interface Service {
fun getData(callback: Callback<String>)
}
interface Callback<in T> {
fun onSuccess(value: T)
fun onFailure(throwable: Throwable)
}
We can convert it to suspend function using suspendCoroutine():
private val service: Service
suspend fun getData(): String {
return suspendCoroutine { cont ->
service.getData(object : Callback<String> {
override fun onSuccess(value: String) {
cont.resume(value)
}
override fun onFailure(throwable: Throwable) {
cont.resumeWithException(throwable)
}
})
}
}
This way getData() can return the data directly and synchronously, so other suspend functions can use it very easily:
suspend fun otherFunction() {
val data = getData()
println(data)
}
Note that we don't have to use withContext(Dispatchers.IO) { ... } here. We can even invoke getData() from the main thread as long as we are inside the coroutine context (e.g. inside Dispatchers.Main) - main thread won't be blocked.
Cancellations
If the callback service supports cancelling of background tasks then it is best to cancel when the calling coroutine is itself cancelled. Let's add a cancelling feature to our callback API:
interface Service {
fun getData(callback: Callback<String>): Task
}
interface Task {
fun cancel();
}
Now, Service.getData() returns Task that we can use to cancel the operation. We can consume it almost the same as previously, but with small changes:
suspend fun getData(): String {
return suspendCancellableCoroutine { cont ->
val task = service.getData(object : Callback<String> {
...
})
cont.invokeOnCancellation {
task.cancel()
}
}
}
We only need to switch from suspendCoroutine() to suspendCancellableCoroutine() and add invokeOnCancellation() block.
Example using Retrofit
interface GitHubService {
#GET("users/{user}/repos")
fun listRepos(#Path("user") user: String): Call<List<Repo>>
}
suspend fun listRepos(user: String): List<Repo> {
val retrofit = Retrofit.Builder()
.baseUrl("https://api.github.com/")
.build()
val service = retrofit.create<GitHubService>()
return suspendCancellableCoroutine { cont ->
val call = service.listRepos(user)
call.enqueue(object : Callback<List<Repo>> {
override fun onResponse(call: Call<List<Repo>>, response: Response<List<Repo>>) {
if (response.isSuccessful) {
cont.resume(response.body()!!)
} else {
// just an example
cont.resumeWithException(Exception("Received error response: ${response.message()}"))
}
}
override fun onFailure(call: Call<List<Repo>>, t: Throwable) {
cont.resumeWithException(t)
}
})
cont.invokeOnCancellation {
call.cancel()
}
}
}
Native support
Before we start converting callbacks to suspend functions, it is worth checking whether the library that we use does support suspend functions already: natively or with some extension. Many popular libraries like Retrofit or Firebase support coroutines and suspend functions. Usually, they either provide/handle suspend functions directly or they provide suspendable waiting on top of their asynchronous task/call/etc. object. Such waiting is very often named await().
For example, Retrofit supports suspend functions directly since 2.6.0:
interface GitHubService {
#GET("users/{user}/repos")
suspend fun listRepos(#Path("user") user: String): List<Repo>
}
Note that we not only added suspend, but also we no longer return Call, but the result directly. Now, we can use it without all this enqueue() boilerplate:
val repos = service.listRepos(user)
TL;DR The code you pass to these APIs (e.g. in the onSuccessListener) is a callback, and it runs asynchronously (not in the order it is written in your file). It runs at some point later in the future to "call back" into your code. Without using a coroutine to suspend the program, you cannot "return" data retrieved in a callback from a function.
What is a callback?
A callback is a piece of code you pass to some third party library that it will run later when some event happens (e.g. when it gets data from a server). It is important to remember that the callback is not run in the order you wrote it - it may be run much later in the future, could run multiple times, or may never run at all. The example callback below will run Point A, start the server fetching process, run Point C, exit the function, then some time in the distant future may run Point B when the data is retrieved. The printout at Point C will always be empty.
fun getResult() {
// Point A
var r = ""
doc.get().addOnSuccessListener { result ->
// The code inside the {} here is the "callback"
// Point B - handle result
r = result // don't do this!
}
// Point C - r="" still here, point B hasn't run yet
println(r)
}
How do I get the data from the callback then?
Make your own interface/callback
Making your own custom interface/callback can sometimes make things cleaner looking but it doesn't really help with the core question of how to use the data outside the callback - it just moves the aysnc call to another location. It can help if the primary API call is somewhere else (e.g. in another class).
// you made your own callback to use in the
// async API
fun getResultImpl(callback: (String)->Unit) {
doc.get().addOnSuccessListener { result ->
callback(result)
}
}
// but if you use it like this, you still have
// the EXACT same problem as before - the printout
// will always be empty
fun getResult() {
var r = ""
getResultImpl { result ->
// this part is STILL an async callback,
// and runs later in the future
r = result
}
println(r) // always empty here
}
// you still have to do things INSIDE the callback,
// you could move getResultImpl to another class now,
// but still have the same potential pitfalls as before
fun getResult() {
getResultImpl { result ->
println(result)
}
}
Some examples of how to properly use a custom callback: example 1, example 2, example 3
Make the callback a suspend function
Another option is to turn the async method into a suspend function using coroutines so it can wait for the callback to complete. This lets you write linear-looking functions again.
suspend fun getResult() {
val result = suspendCoroutine { cont ->
doc.get().addOnSuccessListener { result ->
cont.resume(result)
}
}
// the first line will suspend the coroutine and wait
// until the async method returns a result. If the
// callback could be called multiple times this may not
// be the best pattern to use
println(result)
}
Re-arrange your program into smaller functions
Instead of writing monolithic linear functions, break the work up into several functions and call them from within the callbacks. You should not try to modify local variables within the callback and return or use them after the callback (e.g. Point C). You have to move away from the idea of returning data from a function when it comes from an async API - without a coroutine this generally isn't possible.
For example, you could handle the async data in a separate method (a "processing method") and do as little as possible in the callback itself other than call the processing method with the received result. This helps avoid a lot of the common errors with async APIs where you attempt to modify local variables declared outside the callback scope or try to return things modified from within the callback. When you call getResult it starts the process of getting the data. When that process is complete (some time in the future) the callback calls showResult to show it.
fun getResult() {
doc.get().addOnSuccessListener { result ->
showResult(result)
}
// don't try to show or return the result here!
}
fun showResult(result: String) {
println(result)
}
Example
As a concrete example here is a minimal ViewModel showing how one could include an async API into a program flow to fetch data, process it, and display it in an Activity or Fragment. This is written in Kotlin but is equally applicable to Java.
class MainViewModel : ViewModel() {
private val textLiveData = MutableLiveData<String>()
val text: LiveData<String>
get() = textLiveData
fun fetchData() {
// Use a coroutine here to make a dummy async call,
// this is where you could call Firestore or other API
// Note that this method does not _return_ the requested data!
viewModelScope.launch {
delay(3000)
// pretend this is a slow network call, this part
// won't run until 3000 ms later
val t = Calendar.getInstance().time
processData(t.toString())
}
// anything out here will run immediately, it will not
// wait for the "slow" code above to run first
}
private fun processData(d: String) {
// Once you get the data you may want to modify it before displaying it.
val p = "The time is $d"
textLiveData.postValue(p)
}
}
A real API call in fetchData() might look something more like this
fun fetchData() {
firestoreDB.collection("data")
.document("mydoc")
.get()
.addOnCompleteListener { task ->
if (task.isSuccessful) {
val data = task.result.data
processData(data["time"])
}
else {
textLiveData.postValue("ERROR")
}
}
}
The Activity or Fragment that goes along with this doesn't need to know anything about these calls, it just passes actions in by calling methods on the ViewModel and observes the LiveData to update its views when new data is available. It cannot assume that the data is available immediately after a call to fetchData(), but with this pattern it doesn't need to.
The view layer can also do things like show and hide a progress bar while the data is being loaded so the user knows it's working in the background.
class MainActivity : AppCompatActivity() {
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
val binding = ActivityMainBinding.inflate(layoutInflater)
setContentView(binding.root)
val model: MainViewModel by viewModels()
// Observe the LiveData and when it changes, update the
// state of the Views
model.text.observe(this) { processedData ->
binding.text.text = processedData
binding.progress.visibility = View.GONE
}
// When the user clicks the button, pass that action to the
// ViewModel by calling "fetchData()"
binding.getText.setOnClickListener {
binding.progress.visibility = View.VISIBLE
model.fetchData()
}
binding.progress.visibility = View.GONE
}
}
The ViewModel is not strictly necessary for this type of async workflow - here is an example of how to do the same thing in the activity
class MainActivity : AppCompatActivity() {
private lateinit var binding: ActivityMainBinding
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
binding = ActivityMainBinding.inflate(layoutInflater)
setContentView(binding.root)
// When the user clicks the button, trigger the async
// data call
binding.getText.setOnClickListener {
binding.progress.visibility = View.VISIBLE
fetchData()
}
binding.progress.visibility = View.GONE
}
private fun fetchData() {
lifecycleScope.launch {
delay(3000)
val t = Calendar.getInstance().time
processData(t.toString())
}
}
private fun processData(d: String) {
binding.progress.visibility = View.GONE
val p = "The time is $d"
binding.text.text = p
}
}
(and, for completeness, the activity XML)
<?xml version="1.0" encoding="utf-8"?>
<androidx.constraintlayout.widget.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context=".MainActivity">
<TextView
android:id="#+id/text"
android:layout_margin="16dp"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintRight_toRightOf="parent"
app:layout_constraintTop_toTopOf="parent"/>
<Button
android:id="#+id/get_text"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_margin="16dp"
android:text="Get Text"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintRight_toRightOf="parent"
app:layout_constraintTop_toBottomOf="#+id/text"
/>
<ProgressBar
android:id="#+id/progress"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:padding="48dp"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintRight_toRightOf="parent"
app:layout_constraintTop_toBottomOf="#+id/get_text"
/>
</androidx.constraintlayout.widget.ConstraintLayout>
I am getting a Flowable from one method called getAlldata()
and this method will get the data from the server and then modify the data that been returned base on the data that had been stored in the DB.
So the process of this method goes like this:
getdata from the server
doOnNext for each item get the id
get the local data by id.
modify the current item
The problem is:
the result will be return before actully the modification of the data in doOnNext() since getting the local data from the DB is another observable.
Question
how can I delay stream until the other observable that is on doOnNext() completes?
The codes
private Flowable<List<MyModule>> getAlldata() {
return remoteDataSource
.getData().flatMap(data -> Flowable.fromIterable(data))
.doOnNext(new Consumer<MyModule>() {
#Override
public void accept(MyModule singleItem) throws Exception {
localDataSource.getData(singleItem.getId())
.firstElement().toFlowable()
.subscribe(new Consumer<Optional<MyModule>>() {
#Override
public void accept(Optional<MyModule> itemOptional) throws Exception {
if (itemOptional.isPresent()) {
// modify the item
}
}
});
}
})
.distinct()
.sorted(ProductsRepository.this::sortItems)
.toList().toFlowable();
}
Use flatmap operator instead of doOnNext() which get the singleItem as a parameter and throw an observable of the type localdatabase. so now you can map the response instead of making your Observable wait.
Observable<ModuleData> obs = remoteDataSource
.getData().flatMapIterable(data ->data)
.flatMap(singleItem->localDataSource.getData(singleItem.getId()))
.distinct()
.sorted(ProductsRepository.this::sortItems)
.toList().toFlowable();
I have a scenario in which I've to bridge the nonreactive code with Reactive Code.
Consider the following scenario.
I have a list of 3 URLs in an ArrayList. I want to call each URL in the order they are inside the ArrayList. I can call only 1 URL at a time. If the first URL returns a successful Response, I want to call onComplete() and don't wanna execute the remaining URL. However, if the response is an error, I want to execute the next URL in the list. I don't want RxJava to call flatMap for the next URL unless I get an error response for the previous URL. Due to my primitive understanding of RxJava, I couldn't figure out a way to achieve this.
What I planned to do something like this:
Observable.fromIteratable(urlList)
.subscribeOn(Schedulars.io())
.flatMap(new Func(String url, String data) {
SomeNetworkLibrary.getData(url)
.OnResponse(new NewResponse() {
public void onSuccess(String dataFromInternet) {return dataFromInternet;}
public void onError(String errorMessage) {return errorMessage;)
})
// wait until we have response from the network call above and then return
// I don't know what will be the cleanest and efficient way of waiting here.
});
TLDR;
I don't want flatMap() to be called before the results from the previous flatMap() have been returned.
How can I do that?
You can turn the network api call into an Observable and then use take(1) after the flattening:
Observable.fromIteratable(urlList)
.subscribeOn(Schedulars.io())
.concatMapDelayError((String url, String data) -> {
return Observable.create(emitter -> {
SomeNetworkLibrary.getData(url)
.OnResponse(new NewResponse() {
public void onSuccess(String dataFromInternet) {
emitter.onNext(dataFromInternet);
// don't call emitter.onComplete() so that
// concatMapDelayError doesn't switch to the next source
}
public void onError(String errorMessage) {
emitter.onError(errorMessage);
}
);
});
// wait until we have response from the network call above and then return
// I don't know what will be the cleanest and efficient way of waiting here.
})
.take(1);
I am attempting to write a Reactive Stream based on the following information:
We have a stream of Entity Events where each Event contains the ID of its Entity and a Type of either INTENT or COMMIT. It is assumed that a COMMIT with a given ID will always be preceded by one-or-more INTENTs with the same ID. When an INTENT is received, it should be grouped by its ID and a "buffer" for that group should be opened. The buffer should be "closed" when a COMMIT for the same group is received or a configured timeout has lapsed. The resulting buffers should be emitted.
Note that it is possible to receive multiple INTENTs before receiving a closing COMMIT. (Edit:) The bufferDuration should guarantee that any "opened" buffer is emitted after bufferDuration time has lapsed since the INTENT that opened the buffer was received, with or without a COMMIT.
My latest attempt at this is the following:
public EntityEventBufferFactory {
private final Duration bufferDuration;
public EntityEventBufferFactory(Duration bufferDuration) {
this.bufferDuration = bufferDuration;
}
public Flux<List<EntityEvent>> createGroupBufferFlux(Flux<EntityEvent> eventFlux) {
return eventFlux.groupBy(EntityEvent::getId)
.map(groupedFlux -> createGroupBuffer(groupedFlux))
.flatMap(Function.identity());
}
protected Flux<List<EntityEvent>> createGroupBuffer(Flux<EntityEvent> groupFlux) {
return groupFlux.publish().buffer(groupFlux.filter(this::shouldOpenBufferOnEvent), createGroupBufferCloseSelector(groupFlux));
}
protected Function<EntityEvent, Publisher<EntityEvent>> createGroupBufferCloseSelector(Flux<EntityEvent> groupFlux) {
return event -> Flux.firstEmitting(Flux.just(event).delay(bufferDuration), groupFlux.filter(this::shouldCloseBufferOnEvent).publish());
}
protected boolean shouldOpenBufferOnEvent(EntityEvent entityEvent) {
return entityEvent.getEventType() == EventType.INTENT;
}
protected boolean shouldCloseBufferOnEvent(EntityEvent entityEvent) {
return entityEvent.getEventType() == EventType.COMMIT;
}
}
And here is the test I am attempting to get passing:
#Test
public void entityEventsCanBeBuffered() throws Exception {
FluxProcessor<EntityEvent, EntityEvent> eventQueue = UnicastProcessor.create();
Duration bufferDuration = Duration.ofMillis(250);
Flux<List<EntityEvent>> bufferFlux = new EntityEventBufferFactory(bufferDuration).createGroupBufferFlux(eventQueue);
bufferFactory.setBufferDuration(bufferDuration);
List<List<EntityEvent>> buffers = new ArrayList<>();
bufferFlux.subscribe(buffers::add);
EntityEvent intent = new EntityEvent();
intent.setId("SOME_ID");
intent.setEventType(EventType.INTENT);
EntityEvent commit = new EntityEvent();
commit.setId(intent.getId());
commit.setEventType(EventType.COMMIT);
eventQueue.onNext(intent);
eventQueue.onNext(commit);
eventQueue.onNext(intent);
eventQueue.onNext(commit);
Thread.sleep(500);
assertEquals(2, buffers.size());
assertFalse(buffers.get(0).isEmpty());
assertFalse(buffers.get(1).isEmpty());
}
With this test, I get two emitted buffers, but they are both empty. You'll note that after digging around, I had to add .publish() at certain points to not get an Exception from Reactor saying This processor allows only a single Subscriber. The answer to this question, RxJava: "java.lang.IllegalStateException: Only one subscriber allowed!", is what led me to that approach.
I'm currently using Reactor, but I think this translates 1-to-1 with RxJava using Observable and methods of the same names.
Any thoughts?
I think that is the definitive use case of Rx groupBy. From the documentation:
Groups the items emitted by a Publisher according to a specified criterion, and emits these grouped items as GroupedFlowables. The emitted GroupedPublisher allows only a single Subscriber during its lifetime and if this Subscriber cancels before the source terminates, the next emission by the source having the same key will trigger a new GroupedPublisher emission.
In your case, this criterion is the ID, and on each GroupedPublisher emitted you takeUntil the type is COMMIT:
source
.groupBy(EntityEvent::getId)
.flatMap(group ->
group
.takeUntil(Flowable.timer(10,TimeUnit.SECONDS))
.takeUntil(this::shouldCloseBufferOnEvent)
.toList())
Edit: added time condition.
Thank you to Tassos Bassoukos for the input. The following Reactor code works for me:
public EntityEventBufferFactory {
private final Duration bufferDuration;
public EntityEventBufferFactory(Duration bufferDuration) {
this.bufferDuration = bufferDuration;
}
#Override
public Flux<List<EntityEvent>> create(Flux<EntityEvent> eventFlux) {
return eventFlux.groupBy(EntityEvent::getId)
.map(this::createGroupBuffer)
.flatMap(Function.identity());
}
protected Mono<List<EntityEvent>> createGroupBuffer(Flux<EntityEvent> groupFlux) {
return groupFlux.take(bufferDuration)
.takeUntil(this::shouldCloseBufferOnEvent)
.collectList();
}
protected boolean shouldCloseBufferOnEvent(EntityEvent EntityEvent) {
return EntityEvent.getEventType() == EventType.COMMIT;
}
}