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Spring Webflux Proper Way To Find and Save

I created the below method to find an Analysis object, update the results field on it and then lastly save the result in the database but not wait for a return.
public void updateAnalysisWithResults(String uuidString, String results) {
findByUUID(uuidString).subscribe(analysis -> {
analysis.setResults(results);
computeSCARepository.save(analysis).subscribe();
});
}
This feels poorly written to subscribe within a subscribe.
Is this a bad practice?
Is there a better way to write this?
UPDATE:
entry point
#PatchMapping("compute/{uuid}/results")
public Mono<Void> patchAnalysisWithResults(#PathVariable String uuid, #RequestBody String results) {
return computeSCAService.updateAnalysisWithResults(uuid,results);
}
public Mono<Void> updateAnalysisWithResults(String uuidString, String results) {
// findByUUID(uuidString).subscribe(analysis -> {
// analysis.setResults(results);
// computeSCARepository.save(analysis).subscribe();
// });
return findByUUID(uuidString)
.doOnNext(analysis -> analysis.setResults(results))
.doOnNext(computeSCARepository::save)
.then();
}

Why it is not working is because you have misunderstood what doOnNext does.
Lets start from the beginning.
A Flux or Mono are producers, they produce items. Your application produces things to the calling client, hence it should always return either a Mono or a Flux. If you don't want to return anything you should return a Mono<Void>.
When the client subscribes to your application what reactor will do is call all operators in the opposite direction until it finds a producer. This is what is called the assembly phase. If all your operators don't chain together you are what i call breaking the reactive chain.
When you break the chain, the things broken from the chain wont be executed.
If we look at your example but in a more exploded version:
#Test
void brokenChainTest() {
updateAnalysisWithResults("12345", "Foo").subscribe();
}
public Mono<Void> updateAnalysisWithResults(String uuidString, String results) {
return findByUUID(uuidString)
.doOnNext(analysis -> analysis.setValue(results))
.doOnNext(this::save)
.then();
}
private Mono<Data> save(Data data) {
return Mono.fromCallable(() -> {
System.out.println("Will not print");
return data;
});
}
private Mono<Data> findByUUID(String uuidString) {
return Mono.just(new Data());
}
private static class Data {
private String value;
public void setValue(String value) {
this.value = value;
}
}
in the above example save is a callable function that will return a producer. But if we run the above function you will notice that the print will never be executed.
This has to do with the usage of doOnNext. If we read the docs for it it says:
Add behavior triggered when the Mono emits a data successfully.
The Consumer is executed first, then the onNext signal is propagated downstream.
doOnNext takes a Consumer that returns void. And if we look at doOnNext we see that the function description looks as follows:
public final Mono<T> doOnNext(Consumer<? super T> onNext)`
THis means that it takes in a consumer that is a T or extends a T and it returns a Mono<T>. So to keep a long explanation short, you can see that it consumes something but also returns the same something.
What this means is that this usually used for what is called side effects basically for something that is done on the side that does not hinder the current flow. One of those things could for instance logging. Logging is one of those things that would consume for instance a string and log it, while we want to keep the string flowing down our program. Or maybe we we want to increment a number on the side. Or modify some state somewhere. You can read all about side effects here.
you can of think of it visually this way:
_____ side effect (for instance logging)
/
___/______ main reactive flow
That's why your first doOnNext setter works, because you are modifying a state on the side, you are setting the value on your class hence modifying the state of your class to have a value.
The second statement on the other hand, the save, does not get executed. You see that function is actually returning something we need to take care of.
This is what it looks like:
save
_____
/ \ < Broken return
___/ ____ no main reactive flow
all we have to do is actually change one single line:
// From
.doOnNext(this::save)
// To
.flatMap(this::save)
flatMap takes whatever is in the Mono, and then we can use that to execute something and then return a "new" something.
So our flow (with flatMap) now looks like this:
setValue() save()
______ _____
/ / \
__/____________/ \______ return to client
So with the use of flatMap we are now saving and returning whatever was returned from that function triggering the rest of the chain.
If you then choose to ignore whatever is returned from the flatMap its completely correct to do as you have done to call then which will
Return a Mono which only replays complete and error signals from this
The general rule is, in a fully reactive application, you should never block.
And you generally don't subscribe unless your application is the final consumer. Which means if your application started the request, then you are the consumerof something else so you subscribe. If a webpage starts off the request, then they are the final consumer and they are subscribing.
If you are subscribing in your application that is producing data its like you are running a bakery and eating your baked breads at the same time.
don't do that, its bad for business :D

Subscribe inside a subscribe is not a good practise. You can use flatMap operator to solve this problem.
public void updateAnalysisWithResults(String uuidString, String results) {
findByUUID(uuidString).flatMap(analysis -> {
analysis.setResults(results);
return computeSCARepository.save(analysis);
}).subscribe();
}

Is it safe to interact with StreamObserver asynchronously, i.e. with Java 8+ CompletableFutures?

I'm looking at the Simple RPC example from grpc.io's basic tutorial:
#Override
public void getFeature(Point request, StreamObserver<Feature> responseObserver) {
responseObserver.onNext(checkFeature(request));
responseObserver.onCompleted();
}
...
private Feature checkFeature(Point location) {
for (Feature feature : features) {
if (feature.getLocation().getLatitude() == location.getLatitude()
&& feature.getLocation().getLongitude() == location.getLongitude()) {
return feature;
}
}
// No feature was found, return an unnamed feature.
return Feature.newBuilder().setName("").setLocation(location).build();
}
Are there any caveats to interacting with the StreamObserver from other threads? For example, say checkFeature() asynchronously hits another service, returning a CompletableFuture:
#Override
public void getFeature(Point request, StreamObserver<Feature> responseObserver) {
checkFeature(request).
thenAccept(feature -> responseObserver.onNext(feature));
responseObserver.onCompleted();
}
Of course the above wouldn't work because the first thread would execute onCompleted() before the feature is returned. So let's fix that:
#Override
public void getFeature(Point request, StreamObserver<Feature> responseObserver) {
checkFeature(request).
thenAccept(feature -> {
responseObserver.onNext(feature);
responseObserver.onCompleted();
});
}
I think this should work, but I'm new to Java so I wonder what ramifications there are. For example,
Will Context.current() be consistent?
Will anything cause the StreamObserver to destruct or close prematurely besides onNext() for a unary calls and onError()?
Is there a better practice?
It would be great if someone could also step me through how they reasoned. I tried looking up actual implementations of StreamObserver but I wasn't sure what to look for.

Using thenAccept() to call onNext() and onCompleted() is fine, because the observer is not called concurrently from multiple threads.
The "broken" example that called onCompleted() separately was broken also because it could have called the observer from multiple threads without any form of synchronization. StreamObservers may not be called from multiple threads simultaneously.
Using thenAccept() isn't quite right though, as it doesn't handle the case where the future fails. So you need to receive the Throwable as well, which can be done with whenComplete():
#Override
public void getFeature(Point request, StreamObserver<Feature> responseObserver) {
checkFeature(request).
whenComplete((feature, t) -> {
if (t != null) {
responseObserver.onError(t);
} else {
responseObserver.onNext(feature);
responseObserver.onCompleted();
}
});
}
The Context could easily be "wrong" when processing that lambda. Typically we'd look for "architectural" solutions to make sure the context is propagated, like wrapping all application thread pools in Context.currentContextExecutor() when creating them, so individual call sites don't need to be concerned with propagation. I'm not familiar enough with CompletableFuture to provide strategy for it.

Will Context.current() be consistent?
Context.current() is using ThreadLocal. if you are accessing it on a different thread, it won't be consistent. You can propagate context between threads. You may find this post useful.
Will anything cause the StreamObserver to destruct or close prematurely besides onNext() for a unary calls and onError()?
Yes, Normal flow of StreamObserver ends with onError or onCompleted.
As StreamObserver javadoc states, "Since individual StreamObservers are not thread-safe, if multiple threads will be writing to a StreamObserver concurrently, the application must synchronize calls". If you are calling StreamObserver concurrently, you need to synchronize the calls. In other words, if you know for sure it won't be called concurrently even if you are using multiple threads, it should be fine.
If accessing the same StreamObserver on multiple threads, I would try to synchronize it unless the performance is critical since it is error prone. At least, it deserves a nice comment.

How can I run a concurrent queue of tasks using Rx?

I've found a lot of examples about it and doesn't know what's the 'right' implementation right there.
Basically I've got a object (let's call it NBAManager) and there's a method public Completable generateGame() for this object. The idea is that generateGame method gets called a lot of times and I want to generate games in a sequential way: I was thinking about concurrent queue. I came up with the following design: I'd create a singleton instance of NBAService: service for NBAManager and the body of generateGame() will look like this:
public Completable generateGame(RequestInfo info)
return service.generateGame(info);
So basically I'll pass up that Completable result. And inside of that NBAService object I'll have a queue (a concurrent one, because I want to have an opportunity to poll() and add(request) if there's a call of generateGame() while NBAManager was processing one of the earlier requests) of requests. I got stuck with this:
What's the right way to write such a job queue in Rx way? There're so many examples of it. Could you send me a link of a good implementation?
How do I handle the logic of queue execution? I believe we've to execute if there's one job only and if there're many then we just have to add it and that's it. How can I control it without runnable? I was thinking about using subjects.
Thanks!

There are multiple ways to implement this, you can choose how much RxJava should be invoked. The least involvement can use a single threaded ExecutorService as the "queue" and CompletableSubject for the delayed completion:
class NBAService {
static ExecutorService exec = Executors.newSingleThreadedExecutor();
public static Completable generateGame(RequestInfo info) {
CompletableSubject result = CompletableSubject.create();
exec.submit(() -> {
// do something with the RequestInfo instance
f(info).subscribe(result);
});
return result;
}
}
A more involved solution would be if you wanted to trigger the execution when the Completable is subscribed to. In this case, you can go with create() and subscribeOn():
class NBAService {
public static Completable generateGame(RequestInfo info) {
return Completable.create(emitter -> {
// do something with the RequestInfo instance
emitter.setDisposable(
f(info).subscribe(emitter::onComplete, emitter::onError)
);
})
.subscribeOn(Schedulers.single());
}
}

Concept of promises in Java

Is there a concept of using promises in java (just like ut is used in JavaScript) instead of using nested callbacks ?
If so, is there an example of how the callback is implemented in java and handlers are chained ?

Yep! Java 8 calls it CompletableFuture. It lets you implement stuff like this.
class MyCompletableFuture<T> extends CompletableFuture<T> {
static final Executor myExecutor = ...;
public MyCompletableFuture() { }
public <U> CompletableFuture<U> newIncompleteFuture() {
return new MyCompletableFuture<U>();
}
public Executor defaultExecutor() {
return myExecutor;
}
public void obtrudeValue(T value) {
throw new UnsupportedOperationException();
}
public void obtrudeException(Throwable ex) {
throw new UnsupportedOperationException();
}
}
The basic design is a semi-fluent API in which you can arrange:
(sequential or async)
(functions or actions)
triggered on completion of
i) ("then") ,or ii) ("andThen" and "orThen")
others. As in:
MyCompletableFuture<String> f = ...; g = ...
f.then((s -> aStringFunction(s)).thenAsync(s -> ...);
or
f.andThen(g, (s, t) -> combineStrings).or(CompletableFuture.async(()->...)....

UPDATE 7/20/17
I wanted to edit that there is also a Library called "ReactFX" which is supposed to be JavaFX as a reactive framework. There are many Reactive Java libraries from what I've seen, and since Play is based on the Reactive principal, I would assume that these Reactive libraries follow that same principal of non-blocking i/o, async calls from server to client and back while having communication be send by either end.
These libraries seem to be made for the client side of things, but there might be a Server reactive library as well, but I would assume that it would be wiser to use Play! with one of these client side reactive libraries.
You can take a look at https://www.playframework.com/
which implements this functionality here
https://www.playframework.com/documentation/2.2.0/api/java/play/libs/F.Promise.html
Additonal reading https://www.playframework.com/documentation/2.5.x/JavaAsync
Creating non-blocking actions
Because of the way Play works, action code must be as fast as possible, i.e., non-blocking. So what should we return from our action if we are not yet able to compute the result? We should return the promise of a result!
Java 8 provides a generic promise API called CompletionStage. A CompletionStage<Result> will eventually be redeemed with a value of type Result. By using a CompletionStage<Result> instead of a normal Result, we are able to return from our action quickly without blocking anything. Play will then serve the result as soon as the promise is redeemed.
The web client will be blocked while waiting for the response, but nothing will be blocked on the server, and server resources can be used to serve other clients.
How to create a CompletionStage
To create a CompletionStage<Result> we need another promise first: the promise that will give us the actual value we need to compute the result:
CompletionStage<Double> promiseOfPIValue = computePIAsynchronously();
CompletionStage<Result> promiseOfResult = promiseOfPIValue.thenApply(pi ->
ok("PI value computed: " + pi)
);
Play asynchronous API methods give you a CompletionStage. This is the case when you are calling an external web service using the play.libs.WS API, or if you are using Akka to schedule asynchronous tasks or to communicate with Actors using play.libs.Akka.
A simple way to execute a block of code asynchronously and to get a CompletionStage is to use the CompletableFuture.supplyAsync() helper:
CompletionStage<Integer> promiseOfInt = CompletableFuture.supplyAsync(() -> intensiveComputation());
Note: It’s important to understand which thread code runs on which promises. Here, the intensive computation will just be run on another thread.
You can’t magically turn synchronous IO into asynchronous by wrapping it in a CompletionStage. If you can’t change the application’s architecture to avoid blocking operations, at some point that operation will have to be executed, and that thread is going to block. So in addition to enclosing the operation in a CompletionStage, it’s necessary to configure it to run in a separate execution context that has been configured with enough threads to deal with the expected concurrency. See Understanding Play thread pools for more information.
It can also be helpful to use Actors for blocking operations. Actors provide a clean model for handling timeouts and failures, setting up blocking execution contexts, and managing any state that may be associated with the service. Also Actors provide patterns like ScatterGatherFirstCompletedRouter to address simultaneous cache and database requests and allow remote execution on a cluster of backend servers. But an Actor may be overkill depending on what you need.
Async results
We have been returning Result up until now. To send an asynchronous result our action needs to return a CompletionStage<Result>:
public CompletionStage<Result> index() {
return CompletableFuture.supplyAsync(() -> intensiveComputation())
.thenApply(i -> ok("Got result: " + i));
}
Actions are asynchronous by default
Play actions are asynchronous by default. For instance, in the controller code below, the returned Result is internally enclosed in a promise:
public Result index() {
return ok("Got request " + request() + "!");
}
Note: Whether the action code returns a Result or a CompletionStage<Result>, both kinds of returned object are handled internally in the same way. There is a single kind of Action, which is asynchronous, and not two kinds (a synchronous one and an asynchronous one). Returning a CompletionStage is a technique for writing non-blocking code.
Some info on CompletionStage
https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/CompletionStage.html
which is a subclass of the class mentioned in #Debosmit Ray's answer called CompletableFuture
This Youtube Video by LinkedIn dev Mr. Brikman explains a bit about Promises in
https://youtu.be/8z3h4Uv9YbE?t=15m46s
and
https://www.youtube.com/watch?v=4b1XLka0UIw
I believe the first video gives an example of a promise, the second video might also give some good info, I don't really recall which video had what content.
Either way the information here is very good, and worth looking into.
I personally do not use Play, but I have been looking at it for a long, long time, as it does a lot of really good stuff.

If you want to do Promise even before Java7, "java-promise" may be useful. (Of course it works with Java8)
You can easily control asynchronous operations like JavaScript's Promise.
https://github.com/riversun/java-promise
example
import org.riversun.promise.Promise;
public class Example {
public static void main(String[] args) {
Promise.resolve("foo")
.then(new Promise((action, data) -> {
new Thread(() -> {
String newData = data + "bar";
action.resolve(newData);
}).start();
}))
.then(new Promise((action, data) -> {
System.out.println(data);
action.resolve();
}))
.start();
System.out.println("Promise in Java");
}
}
result:
Promise in Java
foobar

Does DeferredResult have a race condition when returning a potentially already-set instance?

I'm using DeferredResult in my Spring MVC application to handle some server-side processing of a potentially long-running action. It might be very fast, or it could take a second or two.
But in either case, the incoming HTTP request causes an action to be pushed to a queue, which a separate thread (via an ExecutorService) is responsible for consuming. A callback is then called, notifying the pusher that the operation has completed.
I refactored some of this behavior into a utility method:
public static DeferredResult<String> toResponse(GameManager gameManager, final Player player, Action action) {
DeferredResult<String> deferredResult = new DeferredResult<>();
gameManager.execute(action, new Handler<Result>() {
#Override
public void handle(Result result) {
JSONObject obj;
try {
obj = gameManager.getGameJSON(player);
obj.put("success", result.getResult());
obj.put("message", result.getMessage());
deferredResult.setResult(obj.toString()); // POINT B
} catch (JSONException e) {
deferredResult.setErrorResult(e);
}
}
});
return deferredResult; // POINT A
}
But I'm wondering what happens if the execution of the action happens so quickly that the setResult() method is called (POINT B) on the DeferredResult before it has been returned (POINT A) to the calling method.
Will Spring see the returned DeferredResult already has a value and handle it, or does it only begin "watching" for the setter to be called after the instance has been provided?

I've not used Spring but would say that Class DeferredResult<> would be a pretty poor implementation of a Deferred if settlement timing made any difference to the downstream behaviour.
It seems safe to assume that the behaviour would be identical regardless of asynchronous process' timing - milliseconds, seconds or whatever, with the only proviso that a timeout didn't occur in which case the onTimeout handler would run (if set). Even if the Deferred was settled synchronously, in the same code block that created it, the caller function should act on the outcome as expected.
If this assumption is not valid then the Class DeferredResult<> is not fit for purpose and shouldn't be used.