I have been working with Rx Java 2 for awhile but recently came across a situation that has stumped me. I have a semi-complex chain of operations and wish to pass a "state object" down the chain.
There are 4 operations during which I wish to repeat operations 2 and 3 (serialy, not together) until certain conditions are true. I know i can solve this by chaining each operation using andThen(), but this limits my ability to pass a state object down the chain without reaching outside of the chain.
The reason I need to have a state object is because I need to save an initial value during the first operation and compare it to a value recieved during operation 4 to determine if the overall procedure was successful.
Any clues as to what RxJava2 operators can help me achieve the proper repeat conditions for operation 2 and 3? I would prefer to not nest observables if possible.
You can keep your state as some AtomicReference<State> and use repeatUntil operator.
AtomicReference<State> state = new AtomicReference<>();
Completable operation = Completable.create() // do something and modify state
.repeatUntil(() -> state.get() == SATISFYING_CONDITION);
You can easily chain these Completables with andThen
Related
Currently struggling with this one, and so far no combination of SharedFlow and StateFlow have worked.
I have a flow that might have already started with a value, or not.
Using that flow I want to collect any new values that are emitted after I start collecting.
At this moment all my attempts have always failed, no matter what I try it always gets the current value as soon as I start collecting.
An example of what I am trying to achieve:
Given a Flow (could be any type, Int is just for simplification)
with the following timeline: value 4 is emitted | value 2 is emitted | value 10 is emitted
I want to be able to do the following:
If I start collecting after value 4 has already been emitted, I want to only receive anything after that, in this case it would collect 2 and 10 once emitted
If I start collecting after value 2 then it would only receive the 10
If I start collecting before 4 then it would receive 4, 2 and 10
Tried SharedFlow and Stateflow, tried with replay = 0 and WhileSubscribed, no combination I could find would do what I am looking for.
The only workaround so far that I found was to locally register the time I start my .collect{ } and compare with the start time of the item I receive in the collect. In this case I have the object I am using has a specific origin time, but this workaround will not work for everything like the example above with Integers.
EDIT: Adding implementation example as requested for SharedFlow
This is tied to a Room database call that returns a Flow<MyObject>
MyFragment.kt
lifecycleScope.launch(Dispatchers.IO) {
viewModel.getMyObjectFlow.shareIn(
viewModel.viewModelScope, // also tried with fragment lifecyclescope
SharingStarted.WhileSubscribed(), // also tried with the other 2 options
replay = 0,
).collect{
...
}
}
You have a misconception of how flows work. They always emit only after you start collecting. They emit on-demand. Let's get this example:
val flow1 = flow {
println("Emitting 1")
emit(1)
delay(10.seconds)
println("Emitting 2")
emit(2)
}
delay(5.seconds)
println("Start collecting")
flow1.collect {
println("Collected: $it")
}
The output is:
Start collecting
Emitting 1
Collected: 1
not:
Emitting 1
Start collecting
Collected: 1
This is because flow starts emitting only after you start collecting it. Otherwise, it would have nowhere to emit.
Of course, there are flows which emit from some kind of a cache, queue or a buffer. For example shared flows do this. In that case it looks like you collect after emitting. But this is not really the case. Technically speaking, it works like this:
val buffer = listOf(1 , 2, 3)
val flow1 = flow {
buffer.forEach {
println("Emitting $it")
emit(it)
}
}
It still emits after you start collecting, but it just emits from the cache. Of course, the item was added to the cache before you started collecting, but this is entirely abstracted from you. You can't know why a flow emitted an item. From the collector perspective it always emitted just now, not in the past. Similarly, you can't know if a webserver read the data from the DB or a cache - this is abstracted from you.
Summing up: it is not possible to collect only new items from just any flow in an universal way. Flows in general don't understand the concept of "new items". They just emit, but you don't know why they do this. Maybe they somehow generate items on-the-fly, maybe they passively observe external events or maybe they re-transmit some items that they collected from another flow. You don't know that.
While developing your solution, you need to understand what was the source of items and develop your code accordingly. For example, if the source is a regular cold flow, then it never starts doing anything before you start collecting. If the source is a state flow, you can just drop the first item. If it is a shared flow or a flow with some replay buffer, then the situation is more complicated.
One possible approach would be to start collecting earlier than we need, initially ignore all collected items and at some point in time start processing them. But this is still far from perfect and it may not work as we expect.
It doesn't make sense to use shareIn at the use site like that. You're creating a shared Flow that cannot be shared because you don't store the reference for other classes to access and use.
Anyway, the problem is that you are creating the SharedFlow at the use site, so your shared flow only begins collecting from upstream when the fragment calls this code. If the upstream flow is cold, then you will be getting the first value emitted by the cold flow.
The SharedFlow should be created in the ViewModel and put in a property so each Fragment can collect from the same instance. You'll want to use SharingStarted.Eagerly to prevent the cold upstream flow from restarting from the beginning when there are new subscribers after a break.
I'm trying to implement redux state update pattern using RXJava
val subject=PublishSubject.create()
val subject1=PublishSubject.create()
// multiple threads posting
// on subject and subject1 here. Concurrently
subject.mergeWith(subject1)
.scan(
getInitState(),
{state, event ->
// state update here
}
)
.subscribe({state ->
// use state here
})
As you can see, I'm using scan operator to maintain the state.
How can I be sure that the state updates happen sequentially even when multiple threads are producing events?
Is there some mechanism in scan operator which makes the events stand in some queue while waiting for current state update function to finish?
What I have done:
I have successfully implemented this pattern in Android environment. It's really easy because if you always do the state update in
AndroidSchedulers.mainThread()
And make state object immutable you are guaranteed to have atomic and sequential state update. But what happens if you don't have dedicated scheduler for state updates? What if you are not on Android?
What I have researched:
I have read the source code for scan operator and there is no
waiting "queue" involved. Just simple state update and emission
I have also read SerializedSubject source code. There indeed is a waiting queue which serializes emissions. But what happens if I have two subjects? Serializing both of them doesn't mean that they don't interfere with each other.
To force execution on a single thread, you can explicitly create a single thread scheduler to replace AndroidSchedulers.mainThread():
val singleThreadScheduler = Schedulers.single()
Even if the events are emitted on other threads, you can ensure you process them only on your single thread using observeOn:
subject.mergeWith(subject1)
.observeOn(singleThreadScheduler)
.scan(
getInitState(),
{state, event ->
// state update here
}
)
.subscribe({state ->
// use state here
})
The difference between observeOn and subscribeOn can be pretty confusing, and logging the thread id can be useful to check everything is running on the thread you expect.
http://reactivex.io/documentation/scheduler.html
Let's say I have a flowable, that some view is subscribed to and it's listening to the changes. I would like to add a custom method based on only the first emit of the flowable, but also keeping the other methods that listen to the changes. What is the best way to approach it?
The naive approach I have is to duplicate the flowable and convert it to Single or Completable to get the results, but it seems redundant.
Thank you.
Use .take(1). BTW also make sure that flowable is shared (otherwise some observers will miss events).
I think you can use share operator for that. Share operator makes a Connectable Observable. And then Connectable Observable publishes items each subscribes.
val o = Flowable.fromArray(1, 2, 3, 4, 5)
.map {
println("heavy operation")
it + it
}
.share() // publish the changes
.subscribeOn(Schedulers.computation()) // for testing. change what you want
o.take(1).subscribe { println("Special work: $it") } // take one
o.subscribe { println("Normal work: $it") }
Result
heavy operation
Special work: 2
Normal work: 2
heavy operation
Normal work: 4
heavy operation
Normal work: 6
heavy operation
Normal work: 8
heavy operation
Normal work: 10
I am trying to transform Observable using concatMap, since the order is important for my case.
#Test
fun load_data() {
val sub = TestSubscriber<Long>()
var s = BehaviorSubject.create<Long>()
s.concatMap {
Observable.timer(it, TimeUnit.MILLISECONDS)
}
.take(4)
.subscribe(sub)
s.onNext(5)
s.onNext(6)
s.onNext(7)
s.onNext(8) //rx.exceptions.MissingBackpressureException
sub.awaitTerminalEvent(500, TimeUnit.MILLISECONDS)
sub.assertNoErrors()
}
I have changed real data loading to Observable.timer() in order to simplify example and make it easier to reproduce.
I am using in the app BehaviorSubject to link UI actions with rx
From documentation, especially from marble diagram I expect that it will store items in queue and transform them one-by-one.
However it seems like concatMap has queue with size set only to 2 items. Adding more items cause MissingBackpressureException
So I have following questions:
Why concatMap has queue size 2 instead of RxRingBuffer.SIZE as
other operators has?
Should I as a rule add any of onBackpressure* operators before
calling concatMap to prevent from MissingBackpressureException
exception?
Before I answer the questions, please consider switching to RxJava 2 where this is be not a problem with an Observable.
Why concatMap has queue size 2 instead of RxRingBuffer.SIZE as other operators has?
The operator runs one Observable at a time and there was no reason to prefetch more than 1 in advance.
Should I as a rule add any of onBackpressure* operators before calling concatMap to prevent from MissingBackpressureException exception?
Yes.
I'm trying to get my head around the golden rule (if any) about:
When to use BehaviorSubject ?
and
When to use PublishSubject ?
The difference between them is very clear
There are many kinds of subjects. For this specific requirement, a PublishSubject works well because we wish to continue the sequence from where it left off. So assuming events 1,2,3 were emitted in (B), after (A) connects back we only want to see 4, 5, 6. If we used a ReplaySubject we would see [1, 2, 3], 4, 5, 6; or if we used a BehaviorSubject we would see 3, 4, 5, 6 etc.
(source : How to think about Subjects in RxJava (Part 1))
I have seen that Subject's are used in two contexts (at least), UI context and listener context.
UI context (MVVM as example)
For example here a BehaviorSubject is used, and it's clear why they use Subject and not Observable but I have changed the BehaviorSubject to PublishSubject but the app behavior still the same.
Listener context
Why they make project field a BehaviorSubject and not PublishSubject ?
The main difference between PublishSubject and BehaviorSubject is that the latter one remembers the last emitted item. Because of that BehaviorSubject is really useful when you want to emit states.
Why they make project field a BehaviorSubject and not PublishSubject ?
Probably because they want to be able to retrieve the last emitted project with this method:
#Override public #NonNull Observable<Project> project() {
return this.project;
}
PublishSubject: Starts empty and only emits new elements to subscribers.
There is a possibility that one or more items may be lost between the time the Subject is created and the observer subscribes to it because PublishSubject starts emitting elements immediately upon creation.
BehaviorSubject: It needs an initial value and replays it or the latest element to new subscribers. As BehaviorSubject always emits the latest element, you can’t create one without giving a default initial value.
BehaviorSubject is helpful for depicting "values over time". For example, an event stream of birthdays is a Subject, but the stream of a person's age would be a BehaviorSubject.
Publish Subject: Here, if a student entered late into the classroom, he just wants to listen from that point of time when he entered the classroom. So, Publish will be the best for this use-case.
Behavior Subject: Here, if a student entered late into the classroom, he wants to listen the most recent things(not from the beginning) being taught by the professor so that he gets the idea of the context. So, here we will use Behavior.
The difference on BehaviourSubject and PublishSubject relies on how long they keep the data they captures, in instance the PublishSubject only keeps the data available at moment and keeps updating on every entry while BehaviourSubject keeps the last data inserted, so you may use for example to confirm password on a signup form and as an example for PublishSubject, performing a search and it has to update the data constantly in order to give accurate results and there's no too much necessity to compare data that are being inserted.
As reference i leave this two photos from http://reactivex.io/documentation/subject.html
PublishSubject
BehaviourSubject