Currently I'm working on a lot of network-related features. At the moment, I'm dealing with a network channel that allows me to send 1 single piece of information at a time, and I have to wait for it to be acknowledged before I can send the next piece of information. I'm representing the server with 1..n connected clients.
Some of these messages, I have to send in chunks, which is fairly easy to do with RxJava. Currently my "writing" method looks sort of like this:
fun write(bytes: ByteArray, ignoreMtu: Boolean) =
server.deviceList()
.first(emptyList())
.flatMapObservable { devices ->
Single.fromCallable {
if (ignoreMtu) {
bytes.size
} else {
devices.minBy { device -> device.mtu }?.mtu ?: DEFAULT_MTU
}
}
.flatMapObservable { minMtu ->
Observable.fromIterable(bytes.asIterable())
.buffer(minMtu)
}
.map { it.toByteArray() }
.doOnNext { server.currentData = bytes }
.map { devices }
// part i've left out: waiting for each device acknowledging the message, timeouts, etc.
}
What's missing in here is the part where I only allow one piece of information to be sent at the same time. Also, what I require is that if I'm adding a message into my queue, I have to be able to observe the status of only this message (completed, error).
I've thought about what's the most elegant way to achieve this. Solutions I've came up with include for example a PublishSubject<ByteArray> in which I push the messages (queue-like), add a subscriber and observe it - but this would throw for example onError if the previous message failed.
Another way that crossed my mind was to give each message a number upon creating / queueing it, and have a global "message-counter" Observable which I'd hook into the chain's beginning with a filter for the currently sent message == MY_MESSAGE_ID. But this feels kind of fragile. I could increment the counter whenever the subscription terminates, but I'm sure there must be a better way to achieve my goal.
Thanks for your help.
For future reference: The most straight-forward approach I've found is to add a scheduler that's working on a single thread, thus working each task sequential.
Related
Assuming that I like 100000 events on my rabbitmq queue, what is the best way to limit a system to handle them in series vs trying to consume all at once?
I'm trying several options, however, the machine freezes trying to handle them all at once.
You can do ( assuming you're using amqplib)
channel.get('queueName', (err, msgOrFalse) => {
if (err) {
// Handle err
} else if (msgOrFalse) {
// Handle message
}
};
This gets messages one by one, so it's not all at once. You need to call repeatedly of course.
I've found my answer, I just need to use prefetch to ensure that I can handle n number of values at once.
I am having a great experience with ServiceStack & Redis, but I'm confused by ThreadPool and Pub/Sub within a thread, and an apparent limitation for accessing Redis within a message callback. The actual error I get states that I can only call "Subscribe" or "Publish" within the "current context". This happens when I try to do another Redis action from the message callback.
I have a process that must run continuously. In my case I can't just service a request one time, but must keep a thread alive all the time doing calculations (and controlling these threads from a REST API route is ideal). Data must come in to the process on a regular basis, and data must be published. The process must also store and retrieve data from Redis. I am using routes and services to take data in and store it in Redis, so this must take place async from the "calculation" process. I thought pub/sub would be the answer to glue the pieces together, but so far that does not seem possible.
Here is how my code is currently structured (the code with the above error). This is the callback for the route that starts the long term "calculation" thread:
public object Get(SystemCmd request)
{
object ctx = new object();
TradingSystemCmd SystemCmd = new TradingSystemCmd(request, ctx);
ThreadPool.QueueUserWorkItem(x =>
{
SystemCmd.signalEngine();
});
return (retVal); // retVal defined elsewhere
}
Here is the SystemCmd.signalEngine():
public void signalEngine(){
using (var subscription = Redis.CreateSubscription())
{
subscription.OnSubscribe = channel =>
{
};
subscription.OnUnSubscribe = channel =>
{
};
subscription.OnMessage = (channel, msg) =>
{
TC_CalcBar(channel, redisTrade);
};
subscription.SubscribeToChannels(dmx_key); //blocking
}
}
The "TC_CalcBar" call does processing on data as it becomes available. Within this call is a call to Redis for a regular database accesses (and the error). What I could do would be to remove the Subscription and use another method to block on data being available in Redis. But the current approach seemed quite nice until it failed to work. :-)
I also don't know if the ThreadPool has anything to do with the error, or not.
As per Redis documentation:
Once the client enters the subscribed state it is not supposed to
issue any other commands, except for additional SUBSCRIBE, PSUBSCRIBE,
UNSUBSCRIBE and PUNSUBSCRIBE commands.
Source : http://redis.io/commands/subscribe
I am fairly new to Scala and I'm working on an application (library) which is a client to a 3rd-party service (I'm not able to modify the server side and it uses custom binary protocol). I use Netty for networking.
I want to design an API which should allow users to:
Send requests to the server
Send requests to the server and get the response asynchronously
Subscribe to events triggered by the server (having multiple asynchronous event handlers which should be able to send requests as well)
I am not sure how should I design it. Exploring Scala, I stumble upon a bunch of information about Actor model, but I am not sure if it can be applied there and if it can, how.
I'd like to get some recommendations on the way I should take.
In general, the Scala-ish way to expose asynchronous functionality to user code is to return a scala.concurrent.Future[T].
If you're going the actor route, you might consider encapsulating the binary communication within the context of a single actor class. You can scale the instances of this proxy actor using Akka's router support, and you could produce response futures easily using the ask pattern. There are a few nice libraries (Spray, Play Framework) that make wrapping e.g. a RESTful or even WebSocket layer over Akka almost trivial.
A nice model for the pub-sub functionality might be to define a Publisher trait that you can mix in to some actor subclasses. This could define some state to keep track of subscribers, handle Subscribe and Unsubscribe messages, and provide some sort of convenient method for broadcasting messages:
/**
* Sends a copy of the supplied event object to every subscriber of
* the event object class and superclasses.
*/
protected[this] def publish[T](event: T) {
for (subscriber <- subscribersFor(event)) subscriber ! event
}
These are just some ideas based on doing something similar in some recent projects. Feel free to elaborate on your use case if you need more specific direction. Also, the Akka user list is a great resource for general questions like this, if indeed you're interested in exploring actors in Scala.
Observables
This looks like a good example for the Obesrvable pattern. This pattern comes from the Reactive Extensions of .NET, but is also available for Java and Scala. The library is provided by Netflix and has a really good quality.
This pattern has a good theoretical foundation --- it is the dual to the iterator in the category theoretical sense. But more important, it has a lot of practical ideas in it. Especially it handles time very good, e.g. you can limit the event rate you want to get.
With an observable you can process events on avery high level. In .NET it looks a lot like an SQL query. You can register for certain events ("FROM"), filter them ("WHERE") and finally process them ("SELECT"). In Scala you can use standard monadic API (map, filter, flatMap) and of course "for expressions".
An example can look like
stackoverflowQuestions.filter(_.tag == "Scala").map(_.subject).throttleLast(1 second).subscribe(println _)
Obeservables take away a lot of problems you will have with event based systems
Handling subsrcriptions
Handling errors
Filtering and pre-processing events
Buffering events
Structuring the API
Your API should provide an obesrvable for each event source you have. For procedure calls you provide a function that will map the function call to an obesrvable. This function will call the remote procedure and provide the result through the obeservable.
Implementation details
Add the following dependency to your build.sbt:
libraryDependencies += "com.netflix.rxjava" % "rxjava-scala" % "0.15.0"
You can then use the following pattern to convert a callback to an obeservable (given your remote API has some way to register and unregister a callback):
private val callbackFunc : (rx.lang.scala.Observer[String]) => rx.lang.scala.Subscription = { o =>
val listener = {
case Value(s) => o.onNext(s)
case Error(e) => o.onError(o)
}
remote.subscribe(listener)
// Return an interface to cancel the subscription
new Subscription {
val unsubscribed = new AtomicBoolean(false)
def isUnsubscribed: Boolean = unsubscribed.get()
val asJavaSubscription: rx.Subscription = new rx.Subscription {
def unsubscribe() {
remote.unsubscribe(listener)
unsubscribed.set(true)
}
}
}
If you have some specific questions, just ask and I can refine the answer
Additional ressources
There is a very nice course from Martin Odersky et al. at coursera, covering Observables and other reactive techniques.
Take a look at the spray-client library. This provides HTTP request functionality (I'm assuming the server you want to talk to is a web service?). It gives you a pretty nice DSL for building requests and is all about being asynchronous. It does use the akka Actor model behind the scenes, but you do not have to build your own Actors to use it. Instead the you can just use scala's Future model for handling things asynchronously. A good introduction to the Future model is here.
The basic building block of spray-client is a "pipeline" which maps an HttpRequest to a Future containing an HttpResponse:
// this is from the spray-client docs
val pipeline: HttpRequest => Future[HttpResponse] = sendReceive
val response: Future[HttpResponse] = pipeline(Get("http://spray.io/"))
You can take this basic building block and build it up into a client API in a couple of steps. First, make a class that sets up a pipeline and defines some intermediate helpers demonstrating ResponseTransformation techniques:
import scala.concurrent._
import spray.can.client.HttpClient
import spray.client.HttpConduit
import spray.client.HttpConduit._
import spray.http.{HttpRequest, HttpResponse, FormData}
import spray.httpx.unmarshalling.Unmarshaller
import spray.io.IOExtension
type Pipeline = (HttpRequest) => Future[HttpResponse]
// this is basically spray-client boilerplate
def createPipeline(system: ActorSystem, host: String, port: Int): Pipeline = {
val httpClient = system.actorOf(Props(new HttpClient(IOExtension(system).ioBridge())))
val conduit = system.actorOf(props = Props(new HttpConduit(httpClient, host, port)))
sendReceive(conduit)
}
private var pipeline: Pipeline = _
// unmarshalls to a specific type, e.g. a case class representing a datamodel
private def unmarshallingPipeline[T](implicit ec:ExecutionContext, um:Unmarshaller[T]) = (pipeline ~> unmarshal[T])
// for requests that don't return any content. If you get a successful Future it worked; if there's an error you'll get a failed future from the errorFilter below.
private def unitPipeline(implicit ec:ExecutionContext) = (pipeline ~> { _:HttpResponse => () })
// similar to unitPipeline, but where you care about the specific response code.
private def statusPipeline(implicit ec:ExecutionContext) = (pipeline -> {r:HttpResponse => r.status})
// if you want standard error handling create a filter like this
// RemoteServerError and RemoteClientError are custom exception classes
// not shown here.
val errorFilter = { response:HttpResponse =>
if(response.status.isSuccess) response
else if(response.status.value >= 500) throw RemoteServerError(response)
else throw RemoteClientError(response)
}
pipeline = (createPipeline(system, "yourHost", 8080) ~> errorFilter)
Then you can use wrap these up in methods tied to specific requests/responses that becomes the public API. For example, suppose the service has a "ping" GET endpoint that returns a string ("pong") and a "form" POST endpoint where you post form data and receive a DataModel in return:
def ping()(implicit ec:ExecutionContext, um:Unmarshaller[String]): Future[String] =
unmarshallingPipeline(Get("/ping"))
def form(formData: Map[String, String])(implicit ec:ExecutionContext, um:Unmarshaller[DataModel]): Future[DataModel] =
unmarshallingPipeline(Post("/form"), FormData(formData))
And then someone could use the API like this:
import scala.util.{Failure, Success}
API.ping() foreach(println) // will print out "pong" when response comes back
API.form(Map("a" -> "b") onComplete {
case Success(dataModel) => println("Form accepted. Server returned DataModel: " + dataModel)
case Failure(e) => println("Oh noes, the form didn't go through! " + e)
}
I'm not sure if you will find direct support in spray-client for your third bullet point about subscribing to events. Are these events being generated by the server and somehow sent to your client outside the scope of a specific HTTP request? If so, then spray-client will probably not be able to help directly (though your event handlers could still use it to send requests). Are the events occurring on the client side, e.g. the completion of deferred processing initially triggered by a response from the server? If so, you could actually probably get pretty far just by using the functionality in Future, but depending on your use cases, using Actors might make sense.
Say I use the deferred messaging feature to send a message at some later future point in time, but then later I might want to cancel that message.
Question 1 - When making the original bus.Defer(...) call, how do I get a unique identifier back for that message? I would expect there to be a message id or a timeout id of some sort.
Question 2 - Short of calling the RavenDB database directly, is there a way to query the bus to get back all pending deferred messages?
Question 3 - Is there some way to cancel a deferred message? I would expect something like bus.CancelDeferred(messageid)
Is any of this available, or are there any other mechanisms I can use to achieve similar results?
I've had the need to abandon deferred messages and outstanding replies a few times, and I did it by "incrementing the correlation ID" on my saga. You don't mention sagas though, so I'm not sure if this solution will be usable to you. I do think, however, that it goes under "any other mechanisms" that you ask for :)
Check out this example - here I have the state of my saga which, among other things, contains a custom CorrelationId:
public class MySagaData : ISagaData
{
// ... the usual stuff here
public string CorrelationId { get; set; }
}
and then, each time I defer a message or request something, I correlate the deferred message and/or reply with the current value of the correlation ID:
bus.Defer(time, new Something { CorrelationId = Data.CorrelationId });
bus.Send(new SomeRequest { CorrelationId = Data.CorrelationId });
thus conceptually correlating the deferred message and the reply with the current state of the saga.
And then, in cases where I want to abandon all outstanding messages, I simply re-set the saga's correlation ID to a new value - I usually set the value to something like somethingWithBusinessMeaning/timestamp.
This way, abandoned messages will not correlate with any saga instance, effectively being ignored.
Does it make sense?
1) There is currently no way to do this. You could add your own header with a app specific id if you need to keep track of them
2) No, you have to query the storage as you mention. That said what would be the use case for this?
3) No, and this is by design. Given that you can't assume when a message will arrive you can't rely on timeouts being canceled since a defered message might be stuck in a queue and processed right after you cancel. The "cancel" message might also get lost.
In short: your code needs to be prepared to discard "invalid" messages no matter what.
I have a Windows service using NServiceBus to handle incoming messages.
While processing a message, I would like to check to see if there are any other remaining messages on the queue to process.
What is the best way to approach this?
For this specific scenario I'd say that a saga could be appropriate where it is created by the first message received, opens a timeout (for let's say one minute), collects all messages during that period of time, then Bus.SendLocal's a message containing all rows, for which another handler creates the spreadsheet and uploads.
Since, NServiceBus is using MSMQ, you can use the methods from System.Messaging.
Included is a modified method, I'm currently working on, to do a kind of batch processing.
using System.Messaging;
public int PeekAtQueue()
{
const string QUEUE_NAME = "private$\\you_precious_queuname";
if (!MessageQueue.Exists(".\\" + QUEUE_NAME))
return 0;
var messageQueues = MessageQueue.GetPrivateQueuesByMachine(Environment.MachineName);
var queue = messageQueues.Single(x => x.QueueName == QUEUE_NAME);
return queue.GetAllMessages().Count();
}
Modified here itself in the editor. Hope it still compiles :)
Found a similar discussion here, by the way:
http://jopinblog.wordpress.com/2008/03/12/counting-messages-in-an-msmq-messagequeue-from-c/