Can my spark job use the akka actor system or is that not possible and or a bad idea?
Can someone explain if it is a bad idea or not?
The challenge is that you would need to serialize your actor to send it to each node in the cluster. Actors are often used for things like sharing mutable state across threads, running in a single thread -- if the actor exists on every node in the cluster, that's not going to work. It's probably hypothetically possible to use an actor in a spark operation, but I'm not sure what problem it would solve taking into account the limitations you'd face.
Related
I have a REST service which services only one POST request. I want to use an actor to process the request. However I don't know if I should create one actor and derive all the requests using this actor or should I create an actor every time I get a request. What are the pros and cons of these choices.
Also, how is it parallel execution when I create one actor and use that actor to process all my requests. It certainly looks like sequential execution. I would want to understand this as well.
If you use one Actor requests are queued inside the actor mail box and are processed one by one by the actor. This is sequential and not recommended.
Thats why it is said
One actor is no actor.
Create a manager Actor which manages other actors. As actors are quite cheap you can create one actor for every request without any problem.
Do db interactions and other heavy computation using a future and direct results of the future to request handling actor using pipeTo pattern.
Use actors only to divide and distribute work and use Futures to do compute intensive work.
I would create an actor per request and use the "tell" pattern to delegate the work to the newly created actor. If the REST framework you use supports completing the request from another actor (Spray, Akka-HTTP does), then you can complete the request from this new actor. This way your request handling actor is free to handle the next request.
I find this a wonderful resource that explains the pros & cons of ask & tell and per-request-actors. It can be helpful to you.
I agree with what #pamu said. Actors are cheap. But be mindful that if ever you are gonna use a singleton Actor, do not make it stateful it will cause trouble.
And if you are gonna use Futures to do intensive work (which you should do). Make sure you give them specific ExecutionContext / Dispatcher. Using the global dispatcher or ExecutionContext is not good.
Or in each api you have, create a certain dispatcher to control the # of Actors that will work on that kind of endpoint / api.
For example you have "/get/transactions"
specify a dispatcher that would only spawn this # of thread. For this api.
The advantage of this is you can control the # of threads and resources your app uses. When it comes to dealing with heavy traffic. This is a good practice.
I am integrating the use of Akka actors and Spark in the following way: when a task is distributed among the Spark nodes, while processing that tasks, each node also periodically sends metrics data to a different collector process that sits somewhere else on the network through the use of an Akka actor (connecting to the remote process through akka-remote).
The actor-based metrics sending/receiving functionality works just fine when used in standalone mode, but when integrated in a Spark task the following error is thrown:
java.lang.IllegalStateException: Trying to deserialize a serialized ActorRef without an ActorSystem in scope. Use 'akka.serialization.Serialization.currentSystem.withValue(system) { ... }'
at akka.actor.SerializedActorRef.readResolve(ActorRef.scala:407) ~[akka-actor_2.10-2.3.11.jar:na]
If I understood it correctly, the source of the problem is the Spark node being unable to deserialize the ActorRef because it does not have the full information required to do it. I understand that putting an ActorSystem in scope would fix it, but I am not sure how to use the suggested akka.serialization.Serialization.currentSystem.withValue(system) { ... }
The Akka official docs are very good in pretty much all topics they cover. Unfortunately, the chapter devoted to Serialization could be improved IMHO.
Note: there is a similar SO question here but the accepted solution is too specific and thus not really useful in the general case
An ActorSystem is responsible for all of the functionality involved with ActorRef objects.
When you program something like
actorRef ! message
You're actually invoking a bunch of work within the ActorSystem, not the ActorRef, to put the message in the right mailbox, tee-up the Actor to run the receive method within the thread pool, etc... From the documentation:
An actor system manages the resources it is configured to use in order
to run the actors which it contains. There may be millions of actors
within one such system, after all the mantra is to view them as
abundant and they weigh in at an overhead of only roughly 300 bytes
per instance. Naturally, the exact order in which messages are
processed in large systems is not controllable by the application
author
That is why your code works fine "standalone", but not in Spark. Each of your Spark nodes is missing the ActorSystem machinery, therefore even if you could de-serialize the ActorRef in a node there would be no ActorSystem to process the ! in your node function.
You can establish an ActorSystem within each node and use (i) remoting to send messages to your ActorRef in the "master" ActorSystem via actorSelection or (ii) the serialization method you mentioned where each node's ActorSystem would be the system in the example you quoted.
i am new to scala actor programming. i encountered some questions when learning. please give me some help.
Q1. As i learned, messages in mailbox are processed by actor. But actually, the processing is executed by an underlying threadpool. then, if we implement some concurrent jobs by actor model and original java multi-thread model, the efficiency should not have much differency. am i right?
Q2. is akka actor suitable for online serving system? as i know, in a actor system, we have some extra overhead such as message enqueue/dequeue
Q3. akka provides an actor programming paradigm. it reduces issues we may make(such as deadlock ), be easy to scale up/down. if in identical condition, we can not count on actor to make our system better than that implemented by java multi-thread model, can we?
Overall, yes it is suitable.
A1. The most likely efficiency gain is from re-use of the threads in the pool. That is, creation of actors is cheaper than creation of threads.
A2. There is overhead from most abstractions; mailbox processing is no exception. Still, it is not nearly enough overhead to make a blanket statement that akka is not suitable for near-realtime systems.
A3. No, you cannot count on Akka to automatically make things better. The hope is that it will enable you to reason about concurrency in a way that helps you build a scalable system.
I am using akka 2.2.x. in cluster mode. My question is related to actors lookup.
I have two kind of actors:
processor. It accepts text and processes it somehow
result collector. Acceps messages from processor and summarize the results.
Processor actor needs to send message to result collector. So, I need to have ActorRef inside processor.
The queston is - how to pass/lookup this ActorRef to processor.
I have 3 different solutions for now:
Lookup ActorRef to processor in creation time and pass ActorRef as contructor parameter. Looks possibly wrong because it does not handle actor restart process and does not fit into cluster environment.
Lookup in preStart with context.actorSelection("../result-collector"). After this I have the object of ActorSelection and can send messages with !. In this solution I am aware of performance degradation because of lookup in cluster before every call. Or am I wrong here?
Lookup in preStart with context.actorSelection("../result-collector") and call resolveOne to obtain ActorRef. Looks ok, but may not handle akka cluster changes.
Thanks!
There is no problem, neither with restarts nor with clustering, when using #1. Lookups are only useful in those cases where the ActorRef is not available by any other means.
I'm new to the Akka framework and I'm building an HTTP server application on top of Netty + Akka.
My idea so far is to create an actor for each type of request. E.g. I would have an actor for a POST to /my-resource and another actor for a GET to /my-resource.
Where I'm confused is how I should go about actor creation? Should I:
Create a new actor for every request (by this I mean for every request should I do a TypedActor.newInstance() of the appropriate actor)? How expensive is it to create a new actor?
Create one instance of each actor on server start up and use that actor instance for every request? I've read that an actor can only process one message at a time, so couldn't this be a bottle neck?
Do something else?
Thanks for any feedback.
Well, you create an Actor for each instance of mutable state that you want to manage.
In your case, that might be just one actor if my-resource is a single object and you want to treat each request serially - that easily ensures that you only return consistent states between modifications.
If (more likely) you manage multiple resources, one actor per resource instance is usually ideal unless you run into many thousands of resources. While you can also run per-request actors, you'll end up with a strange design if you don't think about the state those requests are accessing - e.g. if you just create one Actor per POST request, you'll find yourself worrying how to keep them from concurrently modifying the same resource, which is a clear indication that you've defined your actors wrongly.
I usually have fairly trivial request/reply actors whose main purpose it is to abstract the communication with external systems. Their communication with the "instance" actors is then normally limited to one request/response pair to perform the actual action.
If you are using Akka, you can create an actor per request. Akka is extremely slim on resources and you can create literarily millions of actors on an pretty ordinary JVM heap. Also, they will only consume cpu/stack/threads when they actually do something.
A year ago I made a comparison between the resource consumption of the thread-based and event-based standard actors. And Akka is even better than the event-base.
One of the big points of Akka in my opinion is that it allows you to design your system as "one actor per usage" where earlier actor systems often forced you to do "use only actors for shared services" due to resource overhead.
I would recommend that you go for option 1.
Options 1) or 2) have both their drawbacks. So then, let's use options 3) Routing (Akka 2.0+)
Router is an element which act as a load balancer, routing the requests to other Actors which will perform the task needed.
Akka provides different Router implementations with different logic to route a message (for example SmallestMailboxPool or RoundRobinPool).
Every Router may have several children and its task is to supervise their Mailbox to further decide where to route the received message.
//This will create 5 instances of the actor ExampleActor
//managed and supervised by a RoundRobinRouter
ActorRef roundRobinRouter = getContext().actorOf(
Props.create(ExampleActor.class).withRouter(new RoundRobinRouter(5)),"router");
This procedure is well explained in this blog.
It's quite a reasonable option, but whether it's suitable depends on specifics of your request handling.
Yes, of course it could.
For many cases the best thing to do would be to just have one actor responding to every request (or perhaps one actor per type of request), but the only thing this actor does is to forward the task to another actor (or spawn a Future) which will actually do the job.
For scaling up the serial requests handling, add a master actor (Supervisor) which in turn will delegate to the worker actors (Children) (round-robin fashion).