Concept of vert.x concerning a webserver? - kotlin

I don't quite get how vert.x is applied for a webserver.
The concept I know for webserver is the thread-based one.
You start your webserver, which then is running.
Then for every client that connects, you get a socket, which is then passed to its own thread handler.
The thread handler then processes the tasks for this specific socket.
So it is clearly defined which thread is doing the work for which socket.
However for every socket you need a new thread, which is expensive in the long run for many sockets.
Then there is the event-based concept that vert.x supplies.
So far I have understood, it should work anyhow like this:
The Vertx instance deploys Verticles.
Verticles run in background threads, but not every Verticle has its own thread. As an example there could be 1000 verticles deployed in a Vertx instance, but the Vertx instance handles only 8 threads (nr of cores * 2).
Then there are the event loops. I'm not sure how they refer to verticles. I've read that every verticle has 2 event loops, but don't really know how that works.
As a webserver example:
class WebServer: AbstractVerticle() {
lateinit var server: HttpServer
override fun start() {
server = vertx.createHttpServer(HttpServerOptions().setPort(1234).setHost("localhost"))
var router = Router.router(vertx);
router.route("/test").handler { routingContext ->
var response = routingContext.response();
response.end("Hello from my first HttpServer")
}
server.requestHandler(router).listen()
}
}
This WebServer can be deployed multiple times in a Vertx instance. And as it seems, each WebServer instance gets its own thread. When I try to connect 100 Clients and reply with a simple response, it seems like each Client is handled synchronously. Because when I do a Thread.sleep statement in each server handler, then the every second one client gets a response. However it should be that all server handlers should start their 1 second sleep and then almost identically reply to all clients after this time.
This is the code to start 100 clients:
fun main(){
Vertx.vertx().deployVerticle(object : AbstractVerticle(){
override fun start() {
for(i in 0 .. 100)
MyWebClient(vertx)
}
})
}
class MyWebClient(val vertx: Vertx) {
init {
println("Client starting ...")
val webClient = WebClient.create(vertx, WebClientOptions().setDefaultPort(1234).setDefaultHost("localhost"))
webClient.get("/test").send { ar ->
if(ar.succeeded()){
val response: HttpResponse<Buffer> = ar.result()
println("Received response with status code ${response.statusCode()} + ${response.body()}")
} else {
println("Something went wrong " + ar.cause().message)
}
}
}
}
Does anybody know an explanation for this?

There are some major issues there.
When you do this:
class WebServer: AbstractVerticle() {
lateinit var server: HttpServer
override fun start() {
server = vertx.createHttpServer(HttpServerOptions().setPort(1234).setHost("localhost"))
...
}
}
Then something like this:
vertx.deployVerticle(WebServer::class.java.name, DeploymentOptions().setInstances(4)
You'll get 4 verticles, but only single one of them will actually listen on the port. So, you're not getting any more concurrency.
Second, when you use Thread.sleep in your Vert.x code, you're blocking the event loop thread.
Third, your test with client is incorrect. Creation of a WebClient is very expensive, so by creating those one after the other, you're actually issuing requests very slowly. If you really want to test your web application, use something like https://github.com/wg/wrk

The issue with your code is that by default Vert.x only uses a maximum of one thread per verticle (if there are more verticles than available threads, a single thread has to handle multiple verticles).
Therefore, if you perform 100 requests against a single instance of a single verticle, the requests are processed by a single thread.
To solve your issue, you should deploy multiple instances of your verticle, i.e.
vertx.deployVerticle(MainVerticle::class.java.name, DeploymentOptions().setInstances(4))
when doing that, always 4 responses will be received at nearly the same time, because 4 instances of the verticle are running and thus 4 threads are utilized.
In previous versions of Vert.x, you could also simply configure multi-threading for a verticle if you didn't want to set a specific amount of instances.
vertx.deployVerticle(MainVerticle::class.java.name, DeploymentOptions().setWorker(true).setMultiThreaded(true))
However, this feature has been deprecated and replaced with customer worker pools.
For more information concerning this topic, I encourage you to take a look at the Vert.x-core Kotlin documentation

Related

Hwo to convert Flux<Item> to List<Item> by blocking

Background
I have a legacy application where I need to return a List<Item>
There are many different Service classes each belonging to an ItemType.
Each service class calls a few different backend APIs and collects the responses to create a SubType of the Item.
So we can say, each service class implementation returns an Item
All backend API access code is using WebClient which returns Mono of some type, and I can zip all Mono within the service to create an Item
The user should be able to look up many different types of items in one call. This requires many backend calls
So for performance sake, I wanted to make this all asynchronous using reactor, so I introduced Spring Reactive code.
Problem
If my endpoint had to return Flux<Item> then this code work fine,
But this is some service code which is used by other legacy code caller.
So eventually I want to return the List<Item> but When I try to convert my Flux into the List I get an error
"message": "block()/blockFirst()/blockLast() are blocking,
which is not supported in thread reactor-http-nio-3",
Here is the service, which is calling a few other service classes.
Flux<Item> itemFlux = Flux.fromIterable(searchRequestByItemType.entrySet())
.flatMap(e ->
getService(e.getKey()).searchItems(e.getValue()))
.subscribeOn(Schedulers.boundedElastic());
Mono<List<Item>> listMono = itemFlux
.collectList()
.block(); //This line throws error
Here is what the above service is calling
default Flux<Item> searchItems(List<SingleItemSearchRequest> requests) {
return Flux.fromIterable(requests)
.flatMap(this::searchItem)
.subscribeOn(Schedulers.boundedElastic());
}
Here is what a single-item search is which is used by above
public Mono<Item> searchItem(SingleItemSearchRequest sisr) {
return Mono.zip(backendApi.getItemANameApi(sisr.getItemIdentifiers().getItemId()),
sisr.isAddXXXDetails()
?backendApi.getItemAXXXApi(sisr.getItemIdentifiers().getItemId())
:Mono.empty(),
sisr.isAddYYYDetails()
?backendApi.getItemAYYYApi(sisr.getItemIdentifiers().getItemId())
:Mono.empty())
.map(tuple3 -> Item.builder()
.name(tuple3.getT1())
.xxxDetails(tuple3.getT2())
.yyyDetails(tuple3.getT3())
.build()
);
}
Sample project to replicate the problem..
https://github.com/mps-learning/spring-reactive-example
I’m new to spring reactor, feel free to pinpoint ALL errors in the code.
UPDATE
As per Patrick Hooijer Bonus suggestion, updating the Mono.zip entries to always contain some default.
#Override
public Mono<Item> searchItem(SingleItemSearchRequest sisr) {
System.out.println("\t\tInside " + supportedItem() + " searchItem with thread " + Thread.currentThread().toString());
//TODO: how to make these XXX YYY calls conditionals In clear way?
return Mono.zip(getNameDetails(sisr).defaultIfEmpty("Default Name"),
getXXXDetails(sisr).defaultIfEmpty("Default XXX Details"),
getYYYDetails(sisr).defaultIfEmpty("Default YYY Details"))
.map(tuple3 -> Item.builder()
.name(tuple3.getT1())
.xxxDetails(tuple3.getT2())
.yyyDetails(tuple3.getT3())
.build()
);
}
private Mono<String> getNameDetails(SingleItemSearchRequest sisr) {
return mockBackendApi.getItemCNameApi(sisr.getItemIdentifiers().getItemId());
}
private Mono<String> getYYYDetails(SingleItemSearchRequest sisr) {
return sisr.isAddYYYDetails()
? mockBackendApi.getItemCYYYApi(sisr.getItemIdentifiers().getItemId())
: Mono.empty();
}
private Mono<String> getXXXDetails(SingleItemSearchRequest sisr) {
return sisr.isAddXXXDetails()
? mockBackendApi.getItemCXXXApi(sisr.getItemIdentifiers().getItemId())
: Mono.empty();
}
Edit: Below answer does not solve the issue, but it contains useful information about Thread switching. It does not work because .block() is no problem for non-blocking Schedulers if it's used to switch to synchronous code.
This is because the block operator inherited the reactor-http-nio-3 Thread from backendApi.getItemANameApi (or one of the other calls in Mono.zip), which is non-blocking.
Most operators continue working on the Thread on which the previous operator executed, this is because the Thread is linked to the emitted item. There are two groups of operators where the Thread of the output item differs from the input:
flatMap, concatMap, zip, etc: Operators that emit items from other Publishers will keep the Thread link they received from this inner Publisher, not from the input.
Time based operators like delayElements, interval, buffer(Duration), etc. will schedule their tasks on the provided Scheduler, or Schedulers.parallel() if none provided. The emitted items will then be linked to the Thread the task was scheduled on.
In your case, Mono.zip emits items from backendApi.getItemANameApi linked to reactor-http-nio-3, which gets propagated downstream, goes outside both the flatMap in searchItems and in itemFlux, until it reaches your block operator.
You can solve this by placing a .publishOn(Schedulers.boundedElastic()), either in searchItem, searchItems or itemFlux. This will cause the item to switch to a Thread in the provided Scheduler.
Bonus: Since you requested to pinpoint errors: Your Mono.zip will not work if sisr.isAddXXXDetails() is false, as Mono.zip discards any element it could not zip. Since you return a Mono.empty() in that case, no items can be zipped and it will return an empty Mono.
If we have only spring-boot-starter-webflux defined as application dependency, then springbok spin up a `Netty server.
One is not expected to block() in a reactive application using a non-blocking server.
However, once we add spring-boot-starter-web dependency then even with the presence of spring-boot-starter-webflux, springboot spinup a tomcat server. Which is a thread-per-request model and is expected to have blocking calls
So to solve my problem, all I had to do above is, to add spring-boot-starter-web dependency in pom.xml. After that applications is started in Tomcat
with timcat .collectList().block() works in Controller class to return the List<Item>.
Whereas with the Netty server I could return only Flux<Item> not List<Item>, which is expected.

How to create a listener for RBlockingQueue using redisson?

In one of my services I am adding to the queue:
RBlockingQueue<String> queue = redissonClient.getBlockingQueue("ABC");
queue.add(receivedTask.toString());
And in the 2nd service I am connecting to the same redis instance and want to read/pop from the queue once a new element gets added from the 1st service, something like this:
RBlockingQueue<String> queue = redisClient.getRedissonClient().getBlockingDeque("ABC");
System.out.println("received: " + queue.poll(0, TimeUnit.SECONDS));
I was earlier dealing with RTopic and it was working fine but the use case has changed and now have to use RQueue instead. Not sure what I am doing wrong here.
Actually found what I was doing wrong.
Should be using subscribeOnElements(): it notifies the listener and polls the new element which can be accessed.
queue.subscribeOnElements((msg) -> {
//code
});

Quarkus: execute parallel unis

In a quarkus / kotlin application, I want to start multiple database requests concurrently. I am new at quarkys and I am not sure if I am doing things right:
val uni1 = Uni.createFrom().item(repo1).onItem().apply { it.request() }
val uni2 = Uni.createFrom().item(repo2).onItem().apply { it.request() }
return Uni.combine().all()
.unis(uni1, uni2)
.asTuple()
.onItem()
.apply { tuple ->
Result(tuple.item1, tuple.item2) }
.await()
.indefinitely()
Will the request() really be made in parallel? Is it the right way to do it in quarkus?
Yes, your code is right.
Uni.combine().all() runs all the passed Unis concurrently. You will get the tuple (containing the individual results) when all the Unis have completed (emitted a result).
From your code, you may remove the tuple step and use combineWith instead.
Finally, note that the await().indefinitely() blocks the caller thread, forever if one of the Uni does not complete (for whatever reason). I strongly recommend using await().atMost(...)

How to synchronize results from an observable in System.Reactive

So Rx is single-threaded by default. In the case of the Sample operator it's not. In my ASPNetCore application, I want to be able to have Subscribe run on the main thread (single thread). I tried using ObserveOn passing in SynchronizationContext.Current, but it's null in ASPNetCore.
A possible solution will be to push all items into BlockingCollection then read from it, but that kinda adds another layer of complexity.
Console.WriteLine ($"Main Thread: {Thread.CurrentThread.ManagedThreadId}");
var source = Observable
.Interval (TimeSpan.FromSeconds (1))
.Sample (TimeSpan.FromSeconds (2));
source
.Subscribe (
data => {
Console.WriteLine ($"{Thread.CurrentThread.ManagedThreadId}"); // different thread
// Here each onNext is invoked asynchronously
// But I have a shared resource that I would like to invoke synchronously.
}
);
Any recommendations will be greatly appreciated :).
If you want to schedule it on the main thread, you should specify a scheduler for your operators.
var source = Observable
.Interval(TimeSpan.FromSeconds(1))
.Sample(TimeSpan.FromSeconds(2), Scheduler.CurrentThread);
Please note that this is blocking (since it's doing work on the main thread) - which is similar to your enumerable sample.
Also see this answer by #Enigmativity.

Consumable channel

Use Case
Android fragment that consumes items of T from a ReceiveChannel<T>. Once consumed, the Ts should be removed from the ReceiveChannel<T>.
I need a ReceiveChannel<T> that supports consuming items from it. It should function as a FIFO queue.
I currently attach to the channel from my UI like:
launch(uiJob) { channel.consumeEach{ /** ... */ } }
I detach by calling uiJob.cancel().
Desired behavior:
val channel = Channel<Int>(UNLIMITED)
channel.send(1)
channel.send(2)
// ui attaches, receives `1` and `2`
channel.send(3) // ui immediately receives `3`
// ui detaches
channel.send(4)
channel.send(5)
// ui attaches, receiving `4` and `5`
Unfortunately, when I detach from the channel, the channel is closed. This causes .send(4) and .send(5) to throw exceptions because the channel is closed. I want to be able to detach from the channel and have it remain usable. How can I do this?
Channel<Int>(UNLIMITED) fits my use case perfect, except that is closes the channel when it is unsubscribed from. I want the channel to remain open. Is this possible?
Channel.consumeEach method calls Channel.consume method which has this line in documentation:
Makes sure that the given block consumes all elements from the given channel by always invoking cancel after the execution of the block.
So the solution is to simply not use consume[Each]. For example you can do:
launch(uiJob) { for (it in channel) { /** ... */ } }
You can use BroadcastChannel. However, you need to specify a limited size (such as 1), as UNLIMITED and 0 (for rendez-vous) are not supported by BroadcastChannel.
You can also use ConflatedBroadcastChannel which always gives the latest value it had to new subscribers, like LiveData is doing.
BTW, is it a big deal if you new Fragment instance receives only the latest value? If not, then just go with ConflatedBroadcastChannel. Otherwise, none of BroacastChannels may suit your use case (try it and see if you get the behavior you're looking for).