I am new in Akka actors and I am doing some tests. Suppose I have actors performing long running tasks like following:
override def receive = {
case email: Email => /*Future*/ {
Thread sleep 3000
}
}
I ran a stress test (remote actos on another machine in network) and I receive the following error:
akka.remote.EndpointAssociationException: Association failed with [akka.tcp://EmailSystem#192.168.1.6:5000]
Caused by: akka.remote.transport.AkkaProtocolException: No response from remote. Handshake timed out
How can I configure this to don't get this error again? Should I use a future in the receive method instead of normal code (as on comment above)? What is the impact of doing that?
It's a really bad idea to have an actor that blocks for a long time like that, since it cannot respond to messages and additionally the akka default threadpool is one thread per core of your computer so you might also be stopping other actors from processing any messages.
Fork that blocking job on a separate execution context/thread pool instead (and make sure to limit how many threads there is in that threadpool). You can then notify the actor using pipeTo:
import akka.pattern.pipe
case email: Email =>
val futureEmail = Future {
... send email and then ...
EmailSent()
}
futureEmail pipeTo sender
Related
I have a load test where three sets of users create something and a different set of users perform some actions on them.
What is the recommended way to co-ordinate this behaviour in Gatling?
I'm currently using an object which contains a LinkedBlockingQueue which the "producers" put the ID and consumers take, see below.
However, it causes the test to hang after ~20s (targeting 1tps).
I've also tried using poll with a timeout, but instead of hanging the poll almost always fails (after 30s) or causes a hang if the timeout is larger (1m+).
This seems to be because all the threads are blocked waiting for something from the queue so isn't compatible with the way Gatling tests run (i.e. not 1 thread per user). Is there a non-blocking way to wait in the Gatling DSL?
Producer.scala
// ...
scenario("Produce stuff")
.exec(/* HTTP call which extracts an ID*/)
.exec(session => Queue.ids.put(session("my-id").as[String])
// ...
Consumer.scala
// ...
scenario("Consume stuff")
.exec(session => session.set("my-id", Queue.ids.take()))
.exec(/* HTTP call which users ID*/)
// ...
Queue.scala
object Queue {
val ids = new LinkedBlockingQueue[String]()
}
As an alternative I've tried to use the application functionality but it seems a harder problem to ensure that each user picks a unique item from the app.
Acknowledging this is all a hack, my current solution in Consumer.scala is:
doIf(_ => Queue.ids.size() < MIN_COUNT)(
pause(30) // wait for 30s if queue is initially too small
)
.doWhile(_ => Queue.ids.size() >= MIN_COUNT)(
exec(session => session.set("my-id", Queue.ids.take()))
.exec(...)
.pause(30)
)
In my project, I created UserRepositoryActor which create their own router with 10 UserRepositoryWorkerActor instances as routee, see hierarchy below:
As you see, if any error occur while fetching data from database, it will occur at worker.
Once I want to fetch user from database, I send message to UserRepositoryActor with this command:
val resultFuture = userRepository ? FindUserById(1)
and I set 10 seconds for timeout.
In case of network connection has problem, UserRepositoryWorkerActor immediately get ConnectionException from underlying database driver and then (what I think) router will restart current worker and send FindUserById(1) command to other worker that available and resultFuture will get AskTimeoutException after 10 seconds passed. Then some time later, once connection back to normal, UserRepositoryWorkerActor successfully fetch data from database and then try to send result back to the caller and found that resultFuture was timed out.
I want to propagate error from UserRepositoryWorkerActor up to the caller immediately after exception occur, so that will prevent resultFuture to wait for 10 seconds and stop UserRepositoryWorkerActor to try to fetch data again and again.
How can I do that?
By the way, if you have any suggestions to my current design, please suggest me. I'm very new to Akka.
Your assumption about Router resending the message is wrong. Router has already passed the message to routee and it doesnt have it any more.
As far as ConnectionException is concerned, you could wrap in a scala.util.Try and send response to sender(). Something like,
Try(SomeDAO.getSomeObjectById(id)) match {
case Success(s) => sender() ! s
case Failure(e) => sender() ! e
}
You design looks correct. Having a router allows you to distribute work and also to limit number of concurrent workers accessing the database.
Option 1
You can make your router watch its children and act accordingly when they are terminated. For example (taken from here):
import akka.routing.{ ActorRefRoutee, RoundRobinRoutingLogic, Router }
class Master extends Actor {
var router = {
val routees = Vector.fill(5) {
val r = context.actorOf(Props[Worker])
context watch r
ActorRefRoutee(r)
}
Router(RoundRobinRoutingLogic(), routees)
}
def receive = {
case w: Work =>
router.route(w, sender())
case Terminated(a) =>
router = router.removeRoutee(a)
val r = context.actorOf(Props[Worker])
context watch r
router = router.addRoutee(r)
}
}
In your case you can send some sort of a failed message from the repository actor to the client. Repository actor can maintain a map of worker ref to request id to know which request failed when worker terminates. It can also record the time between the start of the request and actor termination to decide whether it's worth retrying it with another worker.
Option 2
Simply catch all non-fatal exceptions in your worker actor and reply with appropriate success/failed messages. This is much simpler but you might still want to restart the worker to make sure it's in a good state.
p.s. Router will not restart failed workers, neither it will try to resend messages to them by default. You can take a look at supervisor strategy and Option 1 above on how to achieve that.
When I run my app using akka, it fails with the following exception:
Event Handler specified in config can't be loaded [com.despegar.hasp.impl.DummyLogEventHandler] due to [a06c8d75-0f07-40db-883a-16dc2914934bakka.event.Logging$LoggerInitializationException: Logger log1-DummyLogEventHandler did not respond with LoggerInitialized, sent instead [TIMEOUT]
DummyLogEventHandler is defined as:
class DummyLogEventHandler extends Actor {
def receive = {
case InitializeLogger(_) => sender ! LoggerInitialized
case Error(cause, logSource, logClass, message) =>
case Warning(logSource, logClass, message) =>
case Info(logSource, logClass, message) =>
case Debug(logSource, logClass, message) =>
}
}
My configuration has the following lines:
event-handlers = ["my.app.DummyLogEventHandler"]
event-handler-startup-timeout = 15s
But I've also tried with the default logger:
event-handlers = []
and with slf4j (my app is using the logback backend and logging works ok):
event-handlers = ["akka.event.slf4j.Slf4jEventHandler"]
Neither of those event-handlers nor incrementing the timeout to 60 seconds have worked so far. Moreover, the timeout is thrown sporadically. When I ran a test suite, the exception is thrown in different tests every time.
Can you help me find a solution?
Thanks,
Alex.
Try to set a larger timeout for the logger initialization :
For example in the conf file :
akka {logger-startup-timeout = 25s }
checkout the doc
http://doc.akka.io/docs/akka/snapshot/general/configuration.html
After discussion on akka-user the following was found.
This problem is a symptom of configuring the akka.actor.default-dispatcher to be of type = BalancingDispatcher, which cannot work, see the docs for that dispatcher type:
All the actors share a single Mailbox that they get their messages from.
It is assumed that all actors using the same instance of this dispatcher can process all messages that have been sent to one of the actors; i.e. the actors belong to a pool of actors, and to the client there is no guarantee about which actor instance actually processes a given message.
Sharability: Actors of the same type only
In my case, adding the timeout setting in conf does not work, but setting system property directly like below works.
System.setProperty("akka.logger-startup-timeout", "30s")
I need to write a client that continuously polls a web server for commands. A response from the server indicates that a command is available (in which case the response contains the command) or an instruction that no command is available, and you should fire off a new request for incoming commands.
I'm trying to figure out how to do it using spray-client and Akka, and I can think of ways to do it, but none of them look like they're the idiomatic way to get it done. So the question is:
what's the most sensible way to have a couple of threads poll the same web server for incoming commands and hand the commands off to an actor?
This example uses spray-client, scala futures, and Akka scheduler.
Implementation varies depending on desired behavior (execute many requests in parallel at the same time, execute in different intervals, send responses to one actor to process one response at a time, send responses to many actors to process in parallel... etc).
This particular example shows how execute many requests in parallel at the same time, and then do something with each result as it completes, without waiting for any other requests that were fired off at the same time to complete.
The code below will execute two HTTP requests every 5 seconds to 0.0.0.0:9000/helloWorld and 0.0.0.0:9000/goodbyeWorld in parallel.
Tested in Scala 2.10, Spray 1.1-M7, and Akka 2.1.2:
Actual scheduling code that handles periodic job execution:
// Schedule a periodic task to occur every 5 seconds, starting as soon
// as this schedule is registered
system.scheduler.schedule(initialDelay = 0 seconds, interval = 5 seconds) {
val paths = Seq("helloWorld", "goodbyeWorld")
// perform an HTTP request to 0.0.0.0:9000/helloWorld and
// 0.0.0.0:9000/goodbyeWorld
// in parallel (possibly, depending on available cpu and cores)
val retrievedData = Future.traverse(paths) { path =>
val response = fetch(path)
printResponse(response)
response
}
}
Helper methods / boilerplate setup:
// Helper method to fetch the body of an HTTP endpoint as a string
def fetch(path: String): Future[String] = {
pipeline(HttpRequest(method = GET, uri = s"/$path"))
}
// Helper method for printing a future'd string asynchronously
def printResponse(response: Future[String]) {
// Alternatively, do response.onComplete {...}
for (res <- response) {
println(res)
}
}
// Spray client boilerplate
val ioBridge = IOExtension(system).ioBridge()
val httpClient = system.actorOf(Props(new HttpClient(ioBridge)))
// Register a "gateway" to a particular host for HTTP requests
// (0.0.0.0:9000 in this case)
val conduit = system.actorOf(
props = Props(new HttpConduit(httpClient, "0.0.0.0", 9000)),
name = "http-conduit"
)
// Create a simple pipeline to deserialize the request body into a string
val pipeline: HttpRequest => Future[String] = {
sendReceive(conduit) ~> unmarshal[String]
}
Some notes:
Future.traverse is used for running futures in parallel (ignores order). Using a for comprehension on a list of futures will execute one future at a time, waiting for each to complete.
// Executes `oneThing`, executes `andThenAnother` when `oneThing` is complete,
// then executes `finally` when `andThenAnother` completes.
for {
oneThing <- future1
andThenAnother <- future2
finally <- future3
} yield (...)
system will need to be replaced with your actual Akka actor system.
system.scheduler.schedule in this case is executing an arbitrary block of code every 5 seconds -- there is also an overloaded version for scheduling messages to be sent to an actorRef.
system.scheduler.schedule(
initialDelay = 0 seconds,
frequency = 30 minutes,
receiver = rssPoller, // an actorRef
message = "doit" // the message to send to the actorRef
)
For your particular case, printResponse can be replaced with an actor send instead: anActorRef ! response.
The code sample doesn't take into account failures -- a good place to handle failures would be in the printResponse (or equivalent) method, by using a Future onComplete callback: response.onComplete {...}
Perhaps obvious, but spray-client can be replaced with another http client, just replace the fetch method and accompanying spray code.
Update: Full running code example is here:
git clone the repo, checkout the specified commit sha, $ sbt run, navigate to 0.0.0.0:9000, and watch the code in the console where sbt run was executed -- it should print Hello World!\n'Goodbye World! OR Goodbye World!\nHelloWorld! (order is potentially random because of parallel Future.traverse execution).
You can use HTML5 Server-Sent Events. It is implemented in many Scala frameworks. For example in xitrum code looks like:
class SSE extends Controller {
def sse = GET("/sse") {
addConnectionClosedListener {
// The connection has been closed
// Unsubscribe from events, release resources etc.
}
future {
respondEventSource("command1")
//...
respondEventSource("command2")
//...
}
}
SSE is pretty simple and can be used in any software not only in browser.
Akka integrated in xitrum and we use it in similar system. But it uses netty for async server it is also good for processing thousands of request in 10-15 threads.
So in this way your client will keep connection with server and reconnect when connection will be broken.
I am new to scala and actors. I need to implement such hypothetical situation:
Server wait for messages, if it does not get any in say 10s period of time, it sends message to the Client. Otherwise it receives messages incoming. If it is inside processing some message and another message comes, it needs to be queued (I suppose that is done automatically by scala actors).
The second problem I am encountering is Sleeping. I need the actor to sleep for some constant period of time when it receives the message. But on the other hand I can't block, as I want incoming messages to be queued for further processing.
How about this?
loop {
reactWithin(10000) {
case TIMEOUT => // send message to client
case work => // do work
}
}
Daniel has provided a better answer to the no-input condition part of the question. So I've edited out my inferior solution.
As to the delayed response part of the question, the message queue doesn't block while an actor sleeps. It can just sleep and messages will still accumulate.
However, if you want a fixed delay from when you receive a message to when you process it, you can, for example, create an actor that works immediately but wraps the message in a request for a delay:
case class Delay(when: Long, what: Any) { }
// Inside class DelayingActor(workingActor: Actor)
case msg => workingActor ! Delay(delayValue + System.currentTimeMillis , msg)
Then, the working actor would
case Delay(t,msg) =>
val t0 = System.currentTimeMillis
if (t>t0) Thread.sleep( t - t0 )
msg match {
// Handle message
}