I think the answer is in the {Scala, Java}Docs of mapAsync:
Transform this stream by applying the given function to each of the
> elements as they pass through this processing step. The function returns a
> Future and the value of that future will be emitted downstreams. As many
> futures as requested elements by downstream may run in parallel and may
> complete in any order, but the elements that are emitted downstream are in
> the same order as received from upstream.
The section on rate goes into greater
detail:
http://doc.akka.io/docs/akka-stream-and-http-experimental/1.0-M4/scala/stream-rate.html
You can either go with the default demand as specified by your
Materialization settings, use the default settings (default values in
reference.conf), or manually specify a buffer downstream from your source
to have greater control over buffering and generated demand.
--
>>>>>>>>>> Read the docs: http://akka.io/docs/
>>>>>>>>>> Check the FAQ:
>>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
>>>>>>>>>> Search the archives: https://groups.google.com/group/akka-user
---
You received this message because you are subscribed to the Google Groups "Akka
User List" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to [email protected].
To post to this group, send email to [email protected].
Visit this group at http://groups.google.com/group/akka-user.
For more options, visit https://groups.google.com/d/optout.
