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Merge pull request #16778 from akka/wip-16652-stream-docs-java-6-patriknw

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=str #16652 Add java docs for 'Basics and working with Flows'
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Patrik Nordwall 2015-02-06 10:08:55 +01:00
commit 2e94356fcd
5 changed files with 220 additions and 4 deletions
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2
akka-docs-dev/rst/scala/code/docs/stream/FlowDocSpec.scala
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@ -86,7 +86,7 @@ class FlowDocSpec extends AkkaSpec {
//#compound-source-is-not-keyed-runWith
//#compound-source-is-not-keyed-run
// retain the materialized map, in order to retrieve the timers Cancellable
// retain the materialized map, in order to retrieve the timer's Cancellable
val materialized = timerMap.to(Sink.ignore).run()
val timerCancellable = materialized.get(timer)
timerCancellable.cancel()

2
akka-docs-dev/rst/scala/stream-customize.rst
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@ -109,7 +109,7 @@ emit additional elementss and call ``ctx.finish()`` or ``ctx.pushAndFinish()`` e
The reason for this slightly complex termination sequence is that the underlying ``onComplete`` signal of
Reactive Streams may arrive without any pending demand, i.e. without respecting backpressure. This means that
our push/pull structure that was illustrated in the figure of our custom processing chain does not
apply to termination. Unlike our neat model that is analogous to a ball that bounces back-and-forth in a
apply to termination. Our neat model that is analogous to a ball that bounces back-and-forth in a
pipe (it bounces back on ``Filter``, ``Duplicator`` for example) cannot describe the termination signals. By calling
``absorbTermination()`` the execution environment checks if the conceptual token was *above* the current stage at
that time (which means that it will never come back, so the environment immediately calls ``onPull``) or it was

1
akka-docs-dev/rst/scala/stream-flows-and-basics.rst
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@ -177,7 +177,6 @@ this mode of operation is referred to as pull-based back-pressure.
Stream Materialization
----------------------
**TODO - write me (feel free to move around as well)**
When constructing flows and graphs in Akka Streams think of them as preparing a blueprint, an execution plan.
Stream materialization is the process of taking a stream description (the graph) and allocating all the necessary resources