=dat #3780 Deprecate dataflow
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Patrik Nordwall
parent
cdfd3f07c1
commit
66e4008494
8 changed files with 15 additions and 199 deletions
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@ -66,12 +66,11 @@ trait AskSupport {
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*
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* {{{
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* val f = ask(worker, request)(timeout)
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* flow {
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* EnrichedRequest(request, f())
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* f.map { response =>
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* EnrichedMessage(response)
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* } pipeTo nextActor
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* }}}
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*
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* See [[scala.concurrent.Future]] for a description of `flow`
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*/
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def ask(actorRef: ActorRef, message: Any)(implicit timeout: Timeout): Future[Any] = actorRef ? message
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@ -112,13 +111,12 @@ trait AskSupport {
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* <b>Recommended usage:</b>
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*
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* {{{
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* val f = ask(selection, request)(timeout)
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* flow {
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* EnrichedRequest(request, f())
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* val f = ask(worker, request)(timeout)
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* f.map { response =>
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* EnrichedMessage(response)
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* } pipeTo nextActor
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* }}}
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*
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* See [[scala.concurrent.Future]] for a description of `flow`
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*/
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def ask(actorSelection: ActorSelection, message: Any)(implicit timeout: Timeout): Future[Any] = actorSelection ? message
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}
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@ -28,6 +28,7 @@ package object dataflow {
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*
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* The Delimited Continuations compiler plugin must be enabled in order to use this method.
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*/
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@deprecated("dataflow is deprecated, superseded by Scala Async", "2.3")
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def flow[A](body: ⇒ A @cps[Future[Any]])(implicit executor: ExecutionContext): Future[A] = {
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val p = Promise[A]
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executor.execute(
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@ -43,6 +44,7 @@ package object dataflow {
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p.future
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}
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@deprecated("dataflow is deprecated, superseded by Scala Async", "2.3")
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implicit class DataflowPromise[T](val promise: Promise[T]) extends AnyVal {
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/**
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@ -90,6 +92,7 @@ package object dataflow {
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final def apply()(implicit ec: ExecutionContext): T @cps[Future[Any]] = shift(promise.future flatMap (_: T ⇒ Future[Any]))
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}
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@deprecated("dataflow is deprecated, superseded by Scala Async", "2.3")
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implicit class DataflowFuture[T](val future: Future[T]) extends AnyVal {
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/**
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* For use only within a Future.flow block or another compatible Delimited Continuations reset block.
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@ -34,9 +34,6 @@ Akka is very modular and consists of several JARs containing different features.
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- ``akka-cluster`` – Cluster membership management, elastic routers.
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- ``akka-dataflow`` – add-on to SIP-14 futures supporting implicit
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continuation-passing style
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- ``akka-file-mailbox`` – Akka durable mailbox (find more among community
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projects)
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@ -99,6 +99,12 @@ Changed cluster expected-response-after configuration
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Configuration property ``akka.cluster.failure-detector.heartbeat-request.expected-response-after``
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has been renamed to ``akka.cluster.failure-detector.expected-response-after``.
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Dataflow is Deprecated
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======================
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Akka dataflow is superseded by `Scala Async <https://github.com/scala/async>`_.
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Removed Deprecated Features
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===========================
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@ -1,76 +0,0 @@
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/**
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* Copyright (C) 2009-2013 Typesafe Inc. <http://www.typesafe.com>
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*/
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package docs.dataflow
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import language.postfixOps
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import scala.concurrent.duration._
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import scala.concurrent.{ Await, Future, Promise }
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import org.scalatest.WordSpec
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import org.scalatest.matchers.MustMatchers
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import scala.util.{ Try, Failure, Success }
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class DataflowDocSpec extends WordSpec with MustMatchers {
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//#import-akka-dataflow
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import akka.dataflow._ //to get the flow method and implicit conversions
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//#import-akka-dataflow
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//#import-global-implicit
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import scala.concurrent.ExecutionContext.Implicits.global
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//#import-global-implicit
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"demonstrate flow using hello world" in {
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def println[T](any: Try[T]): Unit = any.get must be === "Hello world!"
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//#simplest-hello-world
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flow { "Hello world!" } onComplete println
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//#simplest-hello-world
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//#nested-hello-world-a
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flow {
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val f1 = flow { "Hello" }
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f1() + " world!"
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} onComplete println
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//#nested-hello-world-a
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//#nested-hello-world-b
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flow {
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val f1 = flow { "Hello" }
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val f2 = flow { "world!" }
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f1() + " " + f2()
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} onComplete println
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//#nested-hello-world-b
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}
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"demonstrate the use of dataflow variables" in {
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val result = Promise[Int]()
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def println(any: Try[Int]): Unit = result.complete(any)
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//#dataflow-variable-a
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val v1, v2 = Promise[Int]()
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flow {
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// v1 will become the value of v2 + 10 when v2 gets a value
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v1 << 10 + v2()
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v1() + v2()
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} onComplete println
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flow { v2 << 5 } // As you can see, no blocking above!
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//#dataflow-variable-a
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Await.result(result.future, 10.seconds) must be === 20
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}
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"demonstrate the difference between for and flow" in {
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val result = Promise[Int]()
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def println(any: Try[Int]): Unit = result.tryComplete(any)
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//#for-vs-flow
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val f1, f2 = Future { 1 }
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val usingFor = for { v1 <- f1; v2 <- f2 } yield v1 + v2
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val usingFlow = flow { f1() + f2() }
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usingFor onComplete println
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usingFlow onComplete println
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//#for-vs-flow
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Await.result(result.future, 10.seconds) must be === 2
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}
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}
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@ -1,111 +0,0 @@
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Dataflow Concurrency
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============================
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Description
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-----------
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Akka implements `Oz-style dataflow concurrency <http://www.mozart-oz.org/documentation/tutorial/node8.html#chapter.concurrency>`_
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by using a special API for :ref:`futures-scala` that enables a complementary way of writing synchronous-looking code that in reality is asynchronous.
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The benefit of Dataflow concurrency is that it is deterministic; that means that it will always behave the same.
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If you run it once and it yields output 5 then it will do that **every time**, run it 10 million times - same result.
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If it on the other hand deadlocks the first time you run it, then it will deadlock **every single time** you run it.
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Also, there is **no difference** between sequential code and concurrent code. These properties makes it very easy to reason about concurrency.
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The limitation is that the code needs to be side-effect free, i.e. deterministic.
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You can't use exceptions, time, random etc., but need to treat the part of your program that uses dataflow concurrency as a pure function with input and output.
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The best way to learn how to program with dataflow variables is to read the fantastic book `Concepts, Techniques, and Models of Computer Programming <http://www.info.ucl.ac.be/%7Epvr/book.html>`_. By Peter Van Roy and Seif Haridi.
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Getting Started (SBT)
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---------------------
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Scala's Delimited Continuations plugin is required to use the Dataflow API. To enable the plugin when using sbt, your project must inherit the ``AutoCompilerPlugins`` trait and contain a bit of configuration as is seen in this example:
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.. code-block:: scala
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autoCompilerPlugins := true,
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libraryDependencies <+= scalaVersion {
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v => compilerPlugin("org.scala-lang.plugins" % "continuations" % "@scalaVersion@")
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},
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scalacOptions += "-P:continuations:enable",
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You will also need to include a dependency on ``akka-dataflow``:
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.. code-block:: scala
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"com.typesafe.akka" %% "akka-dataflow" % "@version@" @crossString@
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Dataflow variables
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------------------
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A Dataflow variable can be read any number of times but only be written to once, which maps very well to the concept of Futures/Promises :ref:`futures-scala`.
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Conversion from ``Future`` and ``Promise`` to Dataflow Variables is implicit and is invisible to the user (after importing akka.dataflow._).
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The mapping from ``Promise`` and ``Future`` is as follows:
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- Futures are readable-many, using the ``apply`` method, inside ``flow`` blocks.
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- Promises are readable-many, just like Futures.
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- Promises are writable-once, using the ``<<`` operator, inside ``flow`` blocks.
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Writing to an already written Promise throws a ``java.lang.IllegalStateException``,
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this has the effect that races to write a promise will be deterministic,
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only one of the writers will succeed and the others will fail.
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The flow
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--------
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The ``flow`` method acts as the delimiter of dataflow expressions (this also neatly aligns with the concept of delimited continuations),
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and flow-expressions compose. At this point you might wonder what the ``flow``-construct brings to the table that for-comprehensions don't,
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and that is the use of the CPS plugin that makes the *look like* it is synchronous, but in reality is asynchronous and non-blocking.
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The result of a call to ``flow`` is a Future with the resulting value of the flow.
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To be able to use the ``flow`` method, you need to import:
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: import-akka-dataflow
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The ``flow`` method will, just like Futures and Promises, require an implicit ``ExecutionContext`` in scope.
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For the examples here we will use:
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: import-global-implicit
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Using flow
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~~~~~~~~~~
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First off we have the obligatory "Hello world!":
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: simplest-hello-world
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You can also refer to the results of other flows within flows:
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: nested-hello-world-a
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… or:
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: nested-hello-world-b
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Working with variables
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~~~~~~~~~~~~~~~~~~~~~~
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Inside the flow method you can use Promises as Dataflow variables:
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: dataflow-variable-a
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Flow compared to for
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--------------------
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Should I use Dataflow or for-comprehensions?
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.. includecode:: code/docs/dataflow/DataflowDocSpec.scala
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:include: for-vs-flow
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Conclusions:
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- Dataflow has a smaller code footprint and arguably is easier to reason about.
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- For-comprehensions are more general than Dataflow, and can operate on a wide array of types.
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@ -5,7 +5,6 @@ Futures and Agents
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:maxdepth: 2
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futures
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dataflow
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stm
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agents
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transactors
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@ -619,7 +619,7 @@ object AkkaBuild extends Build {
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id = "akka-docs",
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base = file("akka-docs"),
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dependencies = Seq(actor, testkit % "test->test", mailboxesCommon % "compile;test->test", channels,
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remote % "compile;test->test", cluster, slf4j, agent, dataflow, transactor, fileMailbox, zeroMQ, camel, osgi, osgiAries,
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remote % "compile;test->test", cluster, slf4j, agent, transactor, fileMailbox, zeroMQ, camel, osgi, osgiAries,
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persistence % "compile;test->test"),
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settings = defaultSettings ++ docFormatSettings ++ site.settings ++ site.sphinxSupport() ++ site.publishSite ++ sphinxPreprocessing ++ cpsPlugin ++ Seq(
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sourceDirectory in Sphinx <<= baseDirectory / "rst",
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