An Activator template that can be used during Reactive Application workshops.
Below are some hints for each step in the tutorial.
Each step has a corresponding git commit for peeps who just want to get to the code without pressing to many keys...
See git branch for the available steps.
To jump to a specific step git checkout <step name>
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Two ways of working with this tutorial (I will show both):
- 1: Use terminal windows + any IDE of your choice
- 2: Use Activator UI to develop, test and run the tutorial
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Start the Activator UI:
> <reactive-instrument-workshop-location>/activator ui -
Start your Play application and test endpoint http://localhost:9000
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In Activator: Run the project by clicking on the “Run” tab and then “Run”
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In Terminal:
> activator run
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Update “John Doe” in file app/controllers/Application.scala to your name, save the file and refresh the browser
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Create a controller in app/controllers named InstrumentController with the method:
def index : a simple Action that just returns a text
<h1>Instruments</h1> -
Amend the conf/routes file so that /start points to the above index method
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Start your Play application and test endpoint http://localhost:9000/start
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In Activator: Run the project by clicking on the “Run” tab and then “Run”
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In Terminal:
> activator run
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In the
app/controllers/InstrumentControlleradd the following method:-
def pricesthat wires up a web socket connection like this:WebSocket.acceptWithActor[String, String] { req => out => … } -
The prices method should return this (provided) actor
WebSocketHandler.props(out)
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Amend the routes file so that /prices points to the above prices method
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Start Play application, open a browser console and type the following:
> var ws = new WebSocket(“ws://localhost:9000/prices");> ws.onmessage = function(x){ console.log(“RESULT:", x); }When you’re done watching the output:
> ws.close();
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Dissect the following parts of the existing WebSocketHandler
- Actor base classes:
ActorRef,Actor,ActorLogging,Props - companion object pattern for
Props - actor context
- actor context.system
- Scheduler functionality
Wire up a new view for prices
- Update method index in
app/controllers/InstrumentControllerto use viewapp/views/price.scala.htmlfile- hint: Ok(price.view.html())
- Study how the Javascript websocket connection is created in the above view file
- hint:
<body onload=init()>is where things are wired up
- hint:
- Run Play and go to http//localhost:9000/start to see the new view
In this step we will wire up the communication between the price server and the client via our Play app.
A suggested pattern is to send messages to self, i.e. the actor you're in, for the different steps involved.
Make sure to add any case object/classes in the companion object of the actor class, i.e. object WebSocketHandler.
- Update prices in
app/controllers/InstrumentControllerto handleJsValueinstead ofString(both directions)- hint: see the
[String, String]syntax in there? It should takeJsValueinstead.
- hint: see the
- Implement the
app/actors/WebSocketHandlerfunctionality-
handle incoming JsValue message and extract instrument id
- hints:
- some good imports:
import play.api.libs.json._ - the receive method should no longer expect
StringbutJsValuefrom the client - parsing can be done with
(json \ "x").asOpt[String]where "x" is the JSON field you want to get (asOpt[String]means that the result will be either anOption[String]orNone) Optionhas a couple of useful methods that can be used to extract the data, e.g.isDefined,getor even bettermyOption map { value => ... }- make sure to set the instrument as local state in your actor (a var value in the class in other words)
- some good imports:
- hints:
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call price server (http://localhost:8080/instrument/id) with the Play WS util lib
- hints:
- some good imports:
import play.api.libs.ws.WS,import play.api.Play.current - WS usage:
WS.url("http://someurl").withRequestTimeout(5000).get-
the above will give you a
Future[WSResponse]back and the easiest way to handle futures is something like this:val myFuture = // some Future[WsResult] myFuture map { wsResult => val theBodyOfTheResponse = resp.body // do something with the value above } recover { case e: ConnectException => // stop this actor, see context.system.stop(...) case e: TimeoutException => // send error message back to web client } -
pro-tip for the above is to send the
resp.bodyas part of a case class to yourself
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- some good imports:
- hints:
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parse JSON result from WS call
- hints:
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some good imports:
import play.api.libs.json._andimport play.api.libs.functional.syntax._ -
parsing of JSON can be done like this
val instrument = (json \ "instrument").asOpt[String] -
if you want to make something more elaborate you can take a look at Reads, e.g.
case class PriceInfo(instrument: String, price: Int, timestamp: Long) implicit val priceInfoReads: Reads[PriceInfo] = ( (JsPath \ "instrument").read[String] and (JsPath \ "price").read[Int] and (JsPath \ "timestamp").read[Long] )(PriceInfo.apply _)
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- hints:
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calculate % fluctuation from last price update
- hint: actors can have state! Keep the last price around to be able to calculate the fluctuation.
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create JSON response and send to client via websocket
- hints:
Json.object("x" -> x, "y" -> y)is your friend- Payload should contain: instrument, price, timestamp and fluctuation
- hints:
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schedule fetching new price in 2 seconds
- hint: look at the Akka docs and use
context.system.scheduleto schedule a new retrieval of price in 2 seconds from the result being sent back to the web client.
- hint: look at the Akka docs and use
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Done! Now test the UI by starting the Price server:
> activator "runMain priceserver.frontend.RestMain"
The Play server:
> activator run
Browse to http://localhost:9000/prices and enter a instrument id (any random string will do).
Try this for a couple of different instrument ids. Do you notice that the initial response slows down? What happens if you enter more than five instrument ids? What's the reason for this?
As you could tell in Step 5 the solution we have created so far cannot cope with a lot of requests. This is due to a simulated slowness built into the class priceserver.backend.PriceController. In this step we will make sure that the application can handle more requests by using the Akka cluster feature. Instead of just having one price service node we will make sure that it is possible to use the number of nodes required to handle the load.
- Start off by creating a new main class used to run each node instance called
priceserver.backend.NodeMain-
Use
ClusterActorRefProviderand set remote configuration inapplication.conf:akka { actor { provider = "akka.cluster.ClusterActorRefProvider" } remote { log-remote-lifecycle-events = off netty.tcp { hostname = "127.0.0.1" port = 0 } } -
Ensure that the main class can take a port number as input
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- Create a
priceserver.backend.PriceServiceto manage all incoming requests to the cluster- Make sure to register the
PriceServiceactor withClusterReceptionistExtension - Create a router with
FromConfig.props(setting for this is done in the next step)
- Make sure to register the
- Go back to
NodeMainand set upClusterSingletonManagerandClusterSingletonProxyforPriceServiceto ensure that there is only onePriceServiceinstance running in the cluster at any point in time-
hint:
ClusterSingletonManagercode:system.actorOf(ClusterSingletonManager.props( singletonProps = PriceService.props, singletonName = "priceService", terminationMessage = PoisonPill, role = None), name = "singletonManager") -
hint:
ClusterSingletonProxycode:system.actorOf(ClusterSingletonProxy.props( singletonPath = "/user/singleton/priceService", role = None)) -
hint: Make
PriceServicecluster aware using the consistent-hashing-pool router:akka.actor.deployment { /singletonManager/priceService/instrumentActor { router = consistent-hashing-pool nr-of-instances = 10 cluster { enabled = on max-nr-of-instances-per-node = 2 allow-local-routees = on } } } -
hint: you must also configure some cluster seed nodes and add the cluster receptionist extension in the config file:
akka cluster { seed-nodes = [ "akka.tcp://[email protected]:2551", "akka.tcp://[email protected]:2552"] } extensions = ["akka.contrib.pattern.ClusterReceptionistExtension"] }
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- Final step for the backend is to handle incoming messages in
PriceServiceand to forward them with the help of the router- Forward a message of type
ConsistentHashableEnvelope
- Forward a message of type
- Now update the
priceserver.frontend.RestMainto useClusterClientto communicate with the actors in the cluster- Create a cluster client actor
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hint: use
Setthis as initial contacts:val initialContacts = Set( system.actorSelection("akka.tcp://[email protected]:2551/user/receptionist"), system.actorSelection("akka.tcp://[email protected]:2552/user/receptionist"))
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- Use the above cluster client when communicating by invoking an ask (
?) with the messageClusterCliend.Send- the actor address should be /user/singletonManager/priceService (see the code for
ClusterSingletonManagerabove)
- the actor address should be /user/singletonManager/priceService (see the code for
- Create a cluster client actor
To run you should first start a couple of nodes in the cluster. Let's start with the seed nodes:
> sbt "runMain priceserver.backend.NodeMain 2551"
and
> sbt "runMain priceserver.backend.NodeMain 2552"
Once the seed nodes are up and running you can start a couple of more nodes if you like:
> sbt "runMain priceserver.backend.NodeMain"
The next step is to start the price server front-end:
> activator "runMain priceserver.frontend.RestMain"
Finally run the Play server:
> activator run
Browse to http://localhost:9000/prices and enter a instrument id (any random string will do). Although we cheated in this step, by not using the PriceController which contains the slowdown code, I hope you do get that this solution can handle load much better. The more requests you have the more nodes you can start and the requests will be routed automatically to any new nodes in the cluster.
Background image in application from: