Rate limiting observable [duplicate] - reactive-programming

I would like to set up an Rx subscription that can respond to an event right away, and then ignore subsequent events that happen within a specified "cooldown" period.
The out of the box Throttle/Buffer methods respond only once the timeout has elapsed, which is not quite what I need.
Here is some code that sets up the scenario, and uses a Throttle (which isn't the solution I want):
class Program
{
static Stopwatch sw = new Stopwatch();
static void Main(string[] args)
{
var subject = new Subject<int>();
var timeout = TimeSpan.FromMilliseconds(500);
subject
.Throttle(timeout)
.Subscribe(DoStuff);
var factory = new TaskFactory();
sw.Start();
factory.StartNew(() =>
{
Console.WriteLine("Batch 1 (no delay)");
subject.OnNext(1);
});
factory.StartNewDelayed(1000, () =>
{
Console.WriteLine("Batch 2 (1s delay)");
subject.OnNext(2);
});
factory.StartNewDelayed(1300, () =>
{
Console.WriteLine("Batch 3 (1.3s delay)");
subject.OnNext(3);
});
factory.StartNewDelayed(1600, () =>
{
Console.WriteLine("Batch 4 (1.6s delay)");
subject.OnNext(4);
});
Console.ReadKey();
sw.Stop();
}
private static void DoStuff(int i)
{
Console.WriteLine("Handling {0} at {1}ms", i, sw.ElapsedMilliseconds);
}
}
The output of running this right now is:
Batch 1 (no delay)
Handling 1 at 508ms
Batch 2 (1s delay)
Batch 3 (1.3s delay)
Batch 4 (1.6s delay)
Handling 4 at 2114ms
Note that batch 2 isn't handled (which is fine!) because we wait for 500ms to elapse between requests due to the nature of throttle. Batch 3 is also not handled, (which is less alright because it happened more than 500ms from batch 2) due to its proximity to Batch 4.
What I'm looking for is something more like this:
Batch 1 (no delay)
Handling 1 at ~0ms
Batch 2 (1s delay)
Handling 2 at ~1000s
Batch 3 (1.3s delay)
Batch 4 (1.6s delay)
Handling 4 at ~1600s
Note that batch 3 wouldn't be handled in this scenario (which is fine!) because it occurs within 500ms of Batch 2.
EDIT:
Here is the implementation for the "StartNewDelayed" extension method that I use:
/// <summary>Creates a Task that will complete after the specified delay.</summary>
/// <param name="factory">The TaskFactory.</param>
/// <param name="millisecondsDelay">The delay after which the Task should transition to RanToCompletion.</param>
/// <returns>A Task that will be completed after the specified duration.</returns>
public static Task StartNewDelayed(
this TaskFactory factory, int millisecondsDelay)
{
return StartNewDelayed(factory, millisecondsDelay, CancellationToken.None);
}
/// <summary>Creates a Task that will complete after the specified delay.</summary>
/// <param name="factory">The TaskFactory.</param>
/// <param name="millisecondsDelay">The delay after which the Task should transition to RanToCompletion.</param>
/// <param name="cancellationToken">The cancellation token that can be used to cancel the timed task.</param>
/// <returns>A Task that will be completed after the specified duration and that's cancelable with the specified token.</returns>
public static Task StartNewDelayed(this TaskFactory factory, int millisecondsDelay, CancellationToken cancellationToken)
{
// Validate arguments
if (factory == null) throw new ArgumentNullException("factory");
if (millisecondsDelay < 0) throw new ArgumentOutOfRangeException("millisecondsDelay");
// Create the timed task
var tcs = new TaskCompletionSource<object>(factory.CreationOptions);
var ctr = default(CancellationTokenRegistration);
// Create the timer but don't start it yet. If we start it now,
// it might fire before ctr has been set to the right registration.
var timer = new Timer(self =>
{
// Clean up both the cancellation token and the timer, and try to transition to completed
ctr.Dispose();
((Timer)self).Dispose();
tcs.TrySetResult(null);
});
// Register with the cancellation token.
if (cancellationToken.CanBeCanceled)
{
// When cancellation occurs, cancel the timer and try to transition to cancelled.
// There could be a race, but it's benign.
ctr = cancellationToken.Register(() =>
{
timer.Dispose();
tcs.TrySetCanceled();
});
}
if (millisecondsDelay > 0)
{
// Start the timer and hand back the task...
timer.Change(millisecondsDelay, Timeout.Infinite);
}
else
{
// Just complete the task, and keep execution on the current thread.
ctr.Dispose();
tcs.TrySetResult(null);
timer.Dispose();
}
return tcs.Task;
}

Here's my approach. It's similar to others that have gone before, but it doesn't suffer the over-zealous window production problem.
The desired function works a lot like Observable.Throttle but emits qualifying events as soon as they arrive rather than delaying for the duration of the throttle or sample period. For a given duration after a qualifying event, subsequent events are suppressed.
Given as a testable extension method:
public static class ObservableExtensions
{
public static IObservable<T> SampleFirst<T>(
this IObservable<T> source,
TimeSpan sampleDuration,
IScheduler scheduler = null)
{
scheduler = scheduler ?? Scheduler.Default;
return source.Publish(ps =>
ps.Window(() => ps.Delay(sampleDuration,scheduler))
.SelectMany(x => x.Take(1)));
}
}
The idea is to use the overload of Window that creates non-overlapping windows using a windowClosingSelector that uses the source time-shifted back by the sampleDuration. Each window will therefore: (a) be closed by the first element in it and (b) remain open until a new element is permitted. We then simply select the first element from each window.
Rx 1.x Version
The Publish extension method used above is not available in Rx 1.x. Here is an alternative:
public static class ObservableExtensions
{
public static IObservable<T> SampleFirst<T>(
this IObservable<T> source,
TimeSpan sampleDuration,
IScheduler scheduler = null)
{
scheduler = scheduler ?? Scheduler.Default;
var sourcePub = source.Publish().RefCount();
return sourcePub.Window(() => sourcePub.Delay(sampleDuration,scheduler))
.SelectMany(x => x.Take(1));
}
}

The solution I found after a lot of trial and error was to replace the throttled subscription with the following:
subject
.Window(() => { return Observable.Interval(timeout); })
.SelectMany(x => x.Take(1))
.Subscribe(i => DoStuff(i));
Edited to incorporate Paul's clean-up.

Awesome solution Andrew! We can take this a step further though and clean up the inner Subscribe:
subject
.Window(() => { return Observable.Interval(timeout); })
.SelectMany(x => x.Take(1))
.Subscribe(DoStuff);

The initial answer I posted has a flaw: namely that the Window method, when used with an Observable.Interval to denote the end of the window, sets up an infinite series of 500ms windows. What I really need is a window that starts when the first result is pumped into the subject, and ends after the 500ms.
My sample data masked this problem because the data broke down nicely into the windows that were already going to be created. (i.e. 0-500ms, 501-1000ms, 1001-1500ms, etc.)
Consider instead this timing:
factory.StartNewDelayed(300,() =>
{
Console.WriteLine("Batch 1 (300ms delay)");
subject.OnNext(1);
});
factory.StartNewDelayed(700, () =>
{
Console.WriteLine("Batch 2 (700ms delay)");
subject.OnNext(2);
});
factory.StartNewDelayed(1300, () =>
{
Console.WriteLine("Batch 3 (1.3s delay)");
subject.OnNext(3);
});
factory.StartNewDelayed(1600, () =>
{
Console.WriteLine("Batch 4 (1.6s delay)");
subject.OnNext(4);
});
What I get is:
Batch 1 (300ms delay)
Handling 1 at 356ms
Batch 2 (700ms delay)
Handling 2 at 750ms
Batch 3 (1.3s delay)
Handling 3 at 1346ms
Batch 4 (1.6s delay)
Handling 4 at 1644ms
This is because the windows begin at 0ms, 500ms, 1000ms, and 1500ms and so each Subject.OnNext fits nicely into its own window.
What I want is:
Batch 1 (300ms delay)
Handling 1 at ~300ms
Batch 2 (700ms delay)
Batch 3 (1.3s delay)
Handling 3 at ~1300ms
Batch 4 (1.6s delay)
After a lot of struggling and an hour banging on it with a co-worker, we arrived at a better solution using pure Rx and a single local variable:
bool isCoolingDown = false;
subject
.Where(_ => !isCoolingDown)
.Subscribe(
i =>
{
DoStuff(i);
isCoolingDown = true;
Observable
.Interval(cooldownInterval)
.Take(1)
.Subscribe(_ => isCoolingDown = false);
});
Our assumption is that calls to the subscription method are synchronized. If they are not, then a simple lock could be introduced.

Use .Scan() !
This is what I use for Throttling when I need the first hit (after a certain period) immediately, but delay (and group/ignore) any subsequent hits.
Basically works like Throttle, but fires immediately if the previous onNext was >= interval ago, otherwise, schedule it at exactly interval from the previous hit. And of course, if within the 'cooling down' period multiple hits come, the additional ones are ignored, just like Throttle does.
The difference with your use case is that if you get an event at 0 ms and 100 ms, they will both be handled (at 0ms and 500ms), which might be what you actually want (otherwise, the accumulator is easy to adapt to ignore ANY hit closer than interval to the previous one).
public static IObservable<T> QuickThrottle<T>(this IObservable<T> src, TimeSpan interval, IScheduler scheduler)
{
return src
.Scan(new ValueAndDueTime<T>(), (prev, id) => AccumulateForQuickThrottle(prev, id, interval, scheduler))
.Where(vd => !vd.Ignore)
.SelectMany(sc => Observable.Timer(sc.DueTime, scheduler).Select(_ => sc.Value));
}
private static ValueAndDueTime<T> AccumulateForQuickThrottle<T>(ValueAndDueTime<T> prev, T value, TimeSpan interval, IScheduler s)
{
var now = s.Now;
// Ignore this completely if there is already a future item scheduled
// but do keep the dueTime for accumulation!
if (prev.DueTime > now) return new ValueAndDueTime<T> { DueTime = prev.DueTime, Ignore = true };
// Schedule this item at at least interval from the previous
var min = prev.DueTime + interval;
var nextTime = (now < min) ? min : now;
return new ValueAndDueTime<T> { DueTime = nextTime, Value = value };
}
private class ValueAndDueTime<T>
{
public DateTimeOffset DueTime;
public T Value;
public bool Ignore;
}

I got another one for your. This one doesn't use Repeat() nor Interval() so it might be what you are after:
subject
.Window(() => Observable.Timer(TimeSpan.FromMilliseconds(500)))
.SelectMany(x => x.Take(1));

Well the most obvious thing will be to use Repeat() here. However, as far as I know Repeat() might introduce problems so that notifications disappear in between the moment when the stream stops and we subscribe again. In practice this has never been a problem for me.
subject
.Take(1)
.Concat(Observable.Empty<long>().Delay(TimeSpan.FromMilliseconds(500)))
.Repeat();
Remember to replace with the actual type of your source.
UPDATE:
Updated query to use Concat instead of Merge

I have stumbled upon this question while trying to re-implement my own solution to the same or similar problem using .Window
Take a look, it seems to be the same as this one and solved quite elegantly:
https://stackoverflow.com/a/3224723/58463

It's an old post, but no answer could really fill my needs, so I'm giving my own solution :
public static IObservable<T> ThrottleOrImmediate<T>(this IObservable<T> source, TimeSpan delay, IScheduler scheduler)
{
return Observable.Create<T>((obs, token) =>
{
// Next item cannot be send before that time
DateTime nextItemTime = default;
return Task.FromResult(source.Subscribe(async item =>
{
var currentTime = DateTime.Now;
// If we already reach the next item time
if (currentTime - nextItemTime >= TimeSpan.Zero)
{
// Following item will be send only after the set delay
nextItemTime = currentTime + delay;
// send current item with scheduler
scheduler.Schedule(() => obs.OnNext(item));
}
// There is still time before we can send an item
else
{
// we schedule the time for the following item
nextItemTime = currentTime + delay;
try
{
await Task.Delay(delay, token);
}
catch (TaskCanceledException)
{
return;
}
// If next item schedule was change by another item then we stop here
if (nextItemTime > currentTime + delay)
return;
else
{
// Set next possible time for an item and send item with scheduler
nextItemTime = currentTime + delay;
scheduler.Schedule(() => obs.OnNext(item));
}
}
}));
});
}
First item is immediately sent, then following items are throttled. Then if a following item is sent after the delayed time, it's immediately sent too.

Related

Vertx delayed batch process

How can I process a list of delayed jobs in Vertx (actually
hundreds of HTTP GET requests, to limited API that bans fast requesting hosts)? now, I am using this code and it gets blocked because Vertx starts all requests at once. It is desirable to process each request with a 5-second delay between each request.
public void getInstrumnetDailyInfo(Instrument instrument,
Handler<AsyncResult<OptionInstrument>> handler) {
webClient
.get("/Loader")
.addQueryParam("i", instrument.getId())
.timeout(30000)
.send(
ar -> {
if (ar.succeeded()) {
String html = ar.result().bodyAsString();
Integer thatData = processHTML(html);
instrument.setThatData(thatData);
handler.handle(Future.succeededFuture(instrument));
} else {
// error
handler.handle(Future.failedFuture("error " +ar.cause()));
}
});
}
public void start(){
List<Instrument> instruments = loadInstrumentsList();
instruments.forEach(
instrument -> {
webClient.getInstrumnetDailyInfo(instrument,
async -> {
if(async.succeeded()){
instrumentMap.put(instrument.getId(), instrument);
}else {
log.warn("getInstrumnetDailyInfo: ", async.cause());
}
});
});
}
You can consider using a timer to fire events (rather than all at startup).
There are two variants in Vertx,
.setTimer() that fires a specific event after a delay
vertx.setTimer(interval, new Handler<T>() {});
and
2. .setPeriodic() that fires every time a specified period of time has passed.
vertx.setPeriodic(interval, new Handler<Long>() {});
setPeriodic seems to be what you are looking for.
You can get more info from the documentation
For more sophisticated Vertx scheduling use-cases, you can have a look at Chime or other schedulers or this module
You could use any out of the box rate limiter function and adapt it for async use.
An example with the RateLimiter from Guava:
// Make permits available at a rate of one every 5 seconds
private RateLimiter limiter = RateLimiter.create(1 / 5.0);
// A vert.x future that completes when it obtains a throttle permit
public Future<Double> throttle() {
return vertx.executeBlocking(p -> p.complete(limiter.acquire()), true);
}
Then...
throttle()
.compose(d -> {
System.out.printf("Waited %.2f before running job\n", d);
return runJob(); // runJob returns a Future result
});

How to limit API calls per second with angular2

I have an API limit of 10 calls per second (however thousands per day), however, when I run this function (Called each Style ID of object, > 10 per second):
getStyleByID(styleID: number): void {
this._EdmundsAPIService.getStyleByID(styleID).subscribe(
style => {this.style.push(style); },
error => this.errorMessage = <any>error);
}
from this function (only 1 call, used onInit):
getStylesWithoutYear(): void {
this._EdmundsAPIService.getStylesWithoutYear(this.makeNiceName, this.modelNiceName, this.modelCategory)
.subscribe(
styles => { this.styles = styles;
this.styles.years.forEach(year =>
year.styles.forEach(style =>
this.getStyleByID(style.id)));
console.log(this.styles); },
error => this.errorMessage = <any>error);
}
It makes > 10 calls a second. How can I throttle or slow down these calls in order to prevent from getting a 403 error?
I have a pretty neat solution where you combine two observables with the .zip() operator:
An observable emitting the requests.
Another observable emitting a value every .1 second.
You end up with one observable emitting requests every .1 second (= 10 requests per second).
Here's the code (JSBin):
// Stream of style ids you need to request (this will be throttled).
const styleIdsObs = new Rx.Subject<number>();
// Getting a style means pushing a new styleId to the stream of style ids.
const getStyleByID = (id) => styleIdsObs.next(id);
// This second observable will act as the "throttler".
// It emits one value every .1 second, so 10 values per second.
const intervalObs = Rx.Observable.interval(100);
Rx.Observable
// Combine the 2 observables. The obs now emits a styleId every .1s.
.zip(styleIdsObs, intervalObs, (styleId, i) => styleId)
// Get the style, i.e. run the request.
.mergeMap(styleId => this._EdmundsAPIService.getStyleByID(styleId))
// Use the style.
.subscribe(style => {
console.log(style);
this.style.push(style);
});
// Launch of bunch of requests at once, they'll be throttled automatically.
for (let i=0; i<20; i++) {
getStyleByID(i);
}
Hopefully you'll be able to translate my code to your own use case. Let me know if you have any questions.
UPDATE: Thanks to Adam, there's also a JSBin showing how to throttle the requests if they don't come in consistently (see convo in the comments). It uses the concatMap() operator instead of the zip() operator.
You could use a timed Observable that triggers every n milliseconds. I didn't adapt your code but this one shows how it would work:
someMethod() {
// flatten your styles into an array:
let stylesArray = ["style1", "style2", "style3"];
// create a scheduled Observable that triggers each second
let source = Observable.timer(1000,1000);
// use a counter to track when all styles are processed
let counter = 0;
let subscription = source.subscribe( x => {
if (counter < stylesArray.length) {
// call your API here
counter++;
} else {
subscription.complete();
}
});
}
Find here a plunk that shows it in action
While I didn't test this code, I would do try something along these lines.
Basically I create a variable that keeps track of when the next request is allowed to be made. If that time has not passed, and a new request comes in, it will use setTimeout to allow that function to run at the appropriate time interval. If the delayUntil value is in the past, then the request can run immediately, and also push back the timer by 100 ms from the current time.
delayUntil = Date.now();
getStylesWithoutYear(): void {
this.delayRequest(() => {
this._EdmundsAPIService.getStylesWithoutYear(this.makeNiceName, this.modelNiceName, this.modelCategory)
.subscribe(
styles => { this.styles = styles;
this.styles.years.forEach(year =>
year.styles.forEach(style =>
this.getStyleByID(style.id)));
console.log(this.styles); },
error => this.errorMessage = <any>error);
};
}
delayRequest(delayedFunction) {
if (this.delayUntil > Date.now()) {
setTimeout(delayedFunction, this.delayUntil - Date.now());
this.delayUntil += 100;
} else {
delayedFunction();
this.delayUntil = Date.now() + 100;
}
}

Rxjava User-Retry observable with .cache operator?

i've an observable that I create with the following code.
Observable.create(new Observable.OnSubscribe<ReturnType>() {
#Override
public void call(Subscriber<? super ReturnType> subscriber) {
try {
if (!subscriber.isUnsubscribed()) {
subscriber.onNext(performRequest());
}
subscriber.onCompleted();
} catch (Exception e) {
subscriber.onError(e);
}
}
});
performRequest() will perform a long running task as you might expect.
Now, since i might be launching the same Observable twice or more in a very short amount of time, I decided to write such transformer:
protected Observable.Transformer<ReturnType, ReturnType> attachToRunningTaskIfAvailable() {
return origObservable -> {
synchronized (mapOfRunningTasks) {
// If not in maps
if ( ! mapOfRunningTasks.containsKey(getCacheKey()) ) {
Timber.d("Cache miss for %s", getCacheKey());
mapOfRunningTasks.put(
getCacheKey(),
origObservable
.doOnTerminate(() -> {
Timber.d("Removed from tasks %s", getCacheKey());
synchronized (mapOfRunningTasks) {
mapOfRunningTasks.remove(getCacheKey());
}
})
.cache()
);
} else {
Timber.d("Cache Hit for %s", getCacheKey());
}
return mapOfRunningTasks.get(getCacheKey());
}
};
}
Which basically puts the original .cache observable in a HashMap<String, Observable>.
This basically disallows multiple requests with the same getCacheKey() (Example login) to call performRequest() in parallel. Instead, if a second login request arrives while another is in progress, the second request observable gets "discarded" and the already-running will be used instead. => All the calls to onNext are going to be cached and sent to both subscribers actually hitting my backend only once.
Now, suppouse this code:
// Observable loginTask
public void doLogin(Observable<UserInfo> loginTask) {
loginTask.subscribe(
(userInfo) -> {},
(throwable) -> {
if (userWantsToRetry()) {
doLogin(loinTask);
}
}
);
}
Where loginTask was composed with the previous transformer. Well, when an error occurs (might be connectivity) and the userWantsToRetry() then i'll basically re-call the method with the same observable. Unfortunately that has been cached and I'll receive the same error without hitting performRequest() again since the sequence gets replayed.
Is there a way I could have both the "same requests grouping" behavior that the transformer provides me AND the retry button?
Your question has a lot going on and it's hard to put it into direct terms. I can make a couple recommendations though. Firstly your Observable.create can be simplified by using an Observable.defer(Func0<Observable<T>>). This will run the func every time a new subscriber is subscribed and catch and channel any exceptions to the subscriber's onError.
Observable.defer(() -> {
return Observable.just(performRequest());
});
Next, you can use observable.repeatWhen(Func1<Observable<Void>, Observable<?>>) to decide when you want to retry. Repeat operators will re-subscribe to the observable after an onComplete event. This particular overload will send an event to a subject when an onComplete event is received. The function you provide will receive this subject. Your function should call something like takeWhile(predicate) and onComplete when you do not want to retry again.
Observable.just(1,2,3).flatMap((Integer num) -> {
final AtomicInteger tryCount = new AtomicInteger(0);
return Observable.just(num)
.repeatWhen((Observable<? extends Void> notifications) ->
notifications.takeWhile((x) -> num == 2 && tryCount.incrementAndGet() != 3));
})
.subscribe(System.out::println);
Output:
1
2
2
2
3
The above example shows that retries are aloud when the event is not 2 and up to a max of 22 retries. If you switch to a repeatWhen then the flatMap would contain your decision as to use a cached observable or the realWork observable. Hope this helps!

Throttle observable based on whether handler is still busy [duplicate]

I want to run periodic tasks in with a restriction that at most only one execution of a method is running at any given time.
I was experimenting with Rx, but I am not sure how to impose at most once concurrency restriction.
var timer = Observable.Interval(TimeSpan.FromMilliseconds(100));
timer.Subscribe(tick => DoSomething());
Additionally, if a task is still running, I want the subsequent schedule to elapse. i.e I don't want the tasks to queue up and cause problems.
I have 2 such tasks to execute periodically. The tasks being executed is currently synchronous. But, I could make them async if there is a necessity.
You are on the right track, you can use Select + Concat to flatten out the observable and limit the number of inflight requests (Note: if your task takes longer than the interval time, then they will start to stack up since they can't execute fast enough):
var source = Observable.Interval(TimeSpan.FromMilliseconds(100))
//I assume you are doing async work since you want to limit concurrency
.Select(_ => Observable.FromAsync(() => DoSomethingAsync()))
//This is equivalent to calling Merge(1)
.Concat();
source.Subscribe(/*Handle the result of each operation*/);
You should have tested your code as is because this is exactly what Rx imposes already.
Try this as a test:
void Main()
{
var timer = Observable.Interval(TimeSpan.FromMilliseconds(100));
using (timer.Do(x => Console.WriteLine("!")).Subscribe(tick => DoSomething()))
{
Console.ReadLine();
}
}
private void DoSomething()
{
Console.Write("<");
Console.Write(DateTime.Now.ToString("HH:mm:ss.fff"));
Thread.Sleep(1000);
Console.WriteLine(">");
}
When you run this you'll get this kind of output:
!
<16:54:57.111>
!
<16:54:58.112>
!
<16:54:59.113>
!
<16:55:00.113>
!
<16:55:01.114>
!
<16:55:02.115>
!
<16:55:03.116>
!
<16:55:04.117>
!
<16:55:05.118>
!
<16:55:06.119
It is already ensuring that there's no overlap.
Below are two implementations of a PeriodicSequentialExecution method, that creates an observable by executing an asynchronous method in a periodic fashion, enforcing a no-overlapping-execution policy. The interval between subsequent executions can be extended to prevent overlapping, in which case the period is time-shifted accordingly.
The first implementation is purely functional, while the second implementation is mostly imperative. Both implementations are functionally identical. The first one can be supplied with a custom IScheduler. The second one may be slightly more efficient.
The functional implementation:
/// <summary>
/// Creates an observable sequence containing the results of an asynchronous
/// action that is invoked periodically and sequentially (without overlapping).
/// </summary>
public static IObservable<T> PeriodicSequentialExecution<T>(
Func<CancellationToken, Task<T>> action,
TimeSpan dueTime, TimeSpan period,
CancellationToken cancellationToken = default,
IScheduler scheduler = null)
{
// Arguments validation omitted
scheduler ??= DefaultScheduler.Instance;
return Delay(dueTime) // Initial delay
.Concat(Observable.Using(() => CancellationTokenSource.CreateLinkedTokenSource(
cancellationToken), linkedCTS =>
// Execution loop
Observable.Publish( // Start a hot delay timer before each operation
Delay(period), hotTimer => Observable
.StartAsync(() => action(linkedCTS.Token)) // Start the operation
.Concat(hotTimer) // Await the delay timer
)
.Repeat()
.Finally(() => linkedCTS.Cancel()) // Unsubscription: cancel the operation
));
IObservable<T> Delay(TimeSpan delay)
=> Observable
.Timer(delay, scheduler)
.IgnoreElements()
.Select(_ => default(T))
.TakeUntil(Observable.Create<Unit>(o => cancellationToken.Register(() =>
o.OnError(new OperationCanceledException(cancellationToken)))));
}
The imperative implementation:
public static IObservable<T> PeriodicSequentialExecution2<T>(
Func<CancellationToken, Task<T>> action,
TimeSpan dueTime, TimeSpan period,
CancellationToken cancellationToken = default)
{
// Arguments validation omitted
return Observable.Create<T>(async (observer, ct) =>
{
using (var linkedCTS = CancellationTokenSource.CreateLinkedTokenSource(
ct, cancellationToken))
{
try
{
await Task.Delay(dueTime, linkedCTS.Token);
while (true)
{
var delayTask = Task.Delay(period, linkedCTS.Token);
var result = await action(linkedCTS.Token);
observer.OnNext(result);
await delayTask;
}
}
catch (Exception ex) { observer.OnError(ex); }
}
});
}
The cancellationToken parameter can be used for the graceful termination of the resulting observable sequence. This means that the sequence waits for the currently running operation to complete before terminating. If you prefer it to terminate instantaneously, potentially leaving work running unobserved in a fire-and-forget fashion, you can simply dispose the subscription to the observable sequence as always. Canceling the cancellationToken results to the observable sequence completing in a faulted state (OperationCanceledException).
Here is a factory function that does exactly what you are asking for.
public static IObservable<Unit> Periodic(TimeSpan timeSpan)
{
return Observable.Return(Unit.Default).Concat(Observable.Return(Unit.Default).Delay(timeSpan).Repeat());
}
Here is an example usage
Periodic(TimeSpan.FromSeconds(1))
.Subscribe(x =>
{
Console.WriteLine(DateTime.Now.ToString("mm:ss:fff"));
Thread.Sleep(500);
});
If you run this, each console print will be roughly 1.5 seconds apart.
Note, If you don't want the first tick to run immediately, you could instead use this factory, which won't send the first Unit until after the timespan.
public static IObservable<Unit> DelayedPeriodic(TimeSpan timeSpan)
{
return Observable.Return(Unit.Default).Delay(timeSpan).Repeat();
}

What is the best way to "rate limit" consuming of an Observable?

I have a bunch of events coming in and I have to execute ALL of them without a loss, but I want to make sure that they are buffered and consumed at the appropriate time slots. Anyone have a solution?
I can't find any operators in Rx that can do that without the loss of the events (Throttle - looses events). I've also considered Buffered, Delay, etc... Can't find a good solution.
I've tried to put a timer in the middle, but somehow it doesn't work at all:
GetInitSequence()
.IntervalThrottle(TimeSpan.FromSeconds(5))
.Subscribe(
item =>
{
Console.WriteLine(DateTime.Now);
// Process item
}
);
public static IObservable<T> IntervalThrottle<T>(this IObservable<T> source, TimeSpan dueTime)
{
return Observable.Create<T>(o =>
{
return source.Subscribe(x =>
{
new Timer(state =>
o.OnNext((T)state), x, dueTime, TimeSpan.FromMilliseconds(-1));
}, o.OnError, o.OnCompleted);
});
}
The question is not 100% clear so I'm making some presumptions.
Observable.Delay is not what you want because that will create a delay from when each event arrives, rather than creating even time intervals for processing.
Observable.Buffer is not what you want because that will cause all events in each given interval to be passed to you, rather than one at a time.
So I believe you're looking for a solution that creates some sort of metronome that ticks away, and gives you an event per tick. This can be naively constructed using Observable.Interval for the metronome and Zip for connecting it to your source:
var source = GetInitSequence();
var trigger = Observable.Interval(TimeSpan.FromSeconds(5));
var triggeredSource = source.Zip(trigger, (s,_) => s);
triggeredSource.Subscribe(item => Console.WriteLine(DateTime.Now));
This will trigger every 5 seconds (in the example above), and give you the original items in sequence.
The only problem with this solution is that if you don't have any more source elements for (say) 10 seconds, when the source elements arrive they will be immediately sent out since some of the 'trigger' events are sitting there waiting for them. Marble diagram for that scenario:
source: -a-b-c----------------------d-e-f-g
trigger: ----o----o----o----o----o----o----o
result: ----a----b----c-------------d-e-f-g
This is a very reasonable issue. There are two questions here already that tackle it:
Rx IObservable buffering to smooth out bursts of events
A way to push buffered events in even intervals
The solution provided is a main Drain extension method and secondary Buffered extension. I've modified these to be far simpler (no need for Drain, just use Concat). Usage is:
var bufferedSource = source.StepInterval(TimeSpan.FromSeconds(5));
The extension method StepInterval:
public static IObservable<T> StepInterval<T>(this IObservable<T> source, TimeSpan minDelay)
{
return source.Select(x =>
Observable.Empty<T>()
.Delay(minDelay)
.StartWith(x)
).Concat();
}
I know this could just be too simple, but would this work?
var intervaled = source.Do(x => { Thread.Sleep(100); });
Basically this just puts a minimum delay between values. Too simplistic?
Along the lines of Enigmativity's answer, if all you want to do is just Delay all of the values by a TimeSpan, I cant see why Delay is not the operator you want
GetInitSequence()
.Delay(TimeSpan.FromSeconds(5)) //ideally pass an IScheduler here
.Subscribe(
item =>
{
Console.WriteLine(DateTime.Now);
// Process item
}
);
How about Observable.Buffer? This should return all the events in the 1s window as a single event.
var xs = Observable.Interval(TimeSpan.FromMilliseconds(100));
var bufferdStream = xs.Buffer(TimeSpan.FromSeconds(5));
bufferdStream.Subscribe(item => { Console.WriteLine("Number of events in window: {0}", item.Count); });
It might be what you're asking isnt that clear. What is your code supposed to do? It looks like you're just delaying by creating a timer for each event. It also breaks the semantics of the observable as the next and complete could occur before the next.
Note this is also only as accurate at the timer used. Typically the timers are accurate to at most 16ms.
Edit:
your example becomes, and item contains all the events in the window:
GetInitSequence()
.Buffer(TimeSpan.FromSeconds(5))
.Subscribe(
item =>
{
Console.WriteLine(DateTime.Now);
// Process item
}
);