Merge remote-tracking branch 'pr/19106' into release-2.3-dev
This commit is contained in:
Roland Kuhn
commit
7132e8130c
20 changed files with 926 additions and 470 deletions
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@ -9,6 +9,12 @@ is sometimes necessary to define new transformation stages either because some f
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stock operations, or for performance reasons. In this part we show how to build custom processing stages and graph
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junctions of various kinds.
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.. note::
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A custom graph stage should not be the first tool you reach for, defining graphs using flows
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and the graph DSL is in general easier and does to a larger extent protect you from mistakes that
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might be easy to make with a custom :class:`GraphStage`
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.. _graphstage-java:
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Custom processing with GraphStage
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@ -79,7 +85,7 @@ in that state.
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.. image:: ../images/outport_transitions.png
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:align: center
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:align: center
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@ -115,7 +121,7 @@ in that state.
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.. image:: ../images/inport_transitions.png
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:align: center
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:align: center
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@ -125,22 +131,160 @@ Finally, there are two methods available for convenience to complete the stage a
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* ``failStage(exception)`` is equivalent to failing all output ports and cancelling all input ports.
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In some cases it is inconvenient and error prone to react on the regular state machine events with the
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signal based API described above. For those cases there is a API which allows for a more declarative sequencing
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of actions which will greatly simplify some use cases at the cost of some extra allocations. The difference
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between the two APIs could be described as that the first one is signal driven from the outside, while this API
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is more active and drives its surroundings.
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The operations of this part of the :class:``GraphStage`` API are:
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* ``emit(out, elem)`` and ``emitMultiple(out, Iterable(elem1, elem2))`` replaces the ``OutHandler`` with a handler that emits
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one or more elements when there is demand, and then reinstalls the current handlers
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* ``read(in)(andThen)`` and ``readN(in, n)(andThen)`` replaces the ``InHandler`` with a handler that reads one or
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more elements as they are pushed and allows the handler to react once the requested number of elements has been read.
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* ``abortEmitting()`` and ``abortReading()`` which will cancel an ongoing emit or read
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Note that since the above methods are implemented by temporarily replacing the handlers of the stage you should never
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call ``setHandler`` while they are running ``emit`` or ``read`` as that interferes with how they are implemented.
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The following methods are safe to call after invoking ``emit`` and ``read`` (and will lead to actually running the
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operation when those are done): ``complete(out)``, ``completeStage()``, ``emit``, ``emitMultiple``, ``abortEmitting()``
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and ``abortReading()``
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An example of how this API simplifies a stage can be found below in the second version of the :class:``Duplicator``.
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Custom linear processing stages using GraphStage
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------------------------------------------------
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Graph stages allows for custom linear processing stages through letting them
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have one input and one output and using :class:`FlowShape` as their shape.
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Such a stage can be illustrated as a box with two flows as it is
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seen in the illustration below. Demand flowing upstream leading to elements
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flowing downstream.
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.. image:: ../images/graph_stage_conceptual.png
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:align: center
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:width: 500
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To illustrate these concepts we create a small :class:`GraphStage` that implements the ``map`` transformation.
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.. image:: ../images/graph_stage_map.png
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:align: center
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:width: 300
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Map calls ``push(out)`` from the ``onPush()`` handler and it also calls ``pull()`` from the ``onPull`` handler resulting in the
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conceptual wiring above, and fully expressed in code below:
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#one-to-one
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Map is a typical example of a one-to-one transformation of a stream where
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demand is passed along upstream elements passed on downstream.
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To demonstrate a many-to-one stage we will implement
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filter. The conceptual wiring of ``Filter`` looks like this:
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|
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.. image:: ../images/graph_stage_filter.png
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:align: center
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:width: 300
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As we see above, if the given predicate matches the current element we are propagating it downwards, otherwise
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we return the “ball” to our upstream so that we get the new element. This is achieved by modifying the map
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example by adding a conditional in the ``onPush`` handler and decide between a ``pull(in)`` or ``push(out)`` call
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(and of course not having a mapping ``f`` function).
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#many-to-one
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To complete the picture we define a one-to-many transformation as the next step. We chose a straightforward example stage
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that emits every upstream element twice downstream. The conceptual wiring of this stage looks like this:
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|
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.. image:: ../images/graph_stage_duplicate.png
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:align: center
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:width: 300
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This is a stage that has state: an option with the last element it has seen indicating if it
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has duplicated this last element already or not. We must also make sure to emit the extra element
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if the upstream completes.
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#one-to-many
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In this case a pull from downstream might be consumed by the stage itself rather
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than passed along upstream as the stage might contain an element it wants to
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push. Note that we also need to handle the case where the upstream closes while
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the stage still has elements it wants to push downstream. This is done by
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overriding `onUpstreamFinish` in the `AbstractInHandler` and provide custom logic
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that should happen when the upstream has been finished.
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This example can be simplified by replacing the usage of a mutable state with calls to
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``emitMultiple`` which will replace the handlers, emit each of multiple elements and then
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reinstate the original handlers:
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#simpler-one-to-many
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Finally, to demonstrate all of the stages above, we put them together into a processing chain,
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which conceptually would correspond to the following structure:
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|
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.. image:: ../images/graph_stage_chain.png
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:align: center
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:width: 700
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In code this is only a few lines, using the ``via`` use our custom stages in a stream:
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#graph-stage-chain
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If we attempt to draw the sequence of events, it shows that there is one "event token"
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in circulation in a potential chain of stages, just like our conceptual "railroad tracks" representation predicts.
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|
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.. image:: ../images/graph_stage_tracks_1.png
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:align: center
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:width: 700
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Completion
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----------
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**This section is a stub and will be extended in the next release**
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Completion handling usually (but not exclusively) comes into the picture when processing stages need to emit
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a few more elements after their upstream source has been completed. We have seen an example of this in our
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first :class:`Duplicator` implementation where the last element needs to be doubled even after the upstream neighbor
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stage has been completed. This can be done by overriding the ``onUpstreamFinish`` method in ``AbstractInHandler``.
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Stages by default automatically stop once all of their ports (input and output) have been closed externally or internally.
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It is possible to opt out from this behavior by overriding ``keepGoingAfterAllPortsClosed`` and returning true in
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the :class:`GraphStageLogic` implementation. In this case the stage **must** be explicitly closed by calling ``completeStage()``
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It is possible to opt out from this behavior by invoking ``setKeepGoing(true)`` (which is not supported from the stage’s
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constructor and usually done in ``preStart``). In this case the stage **must** be explicitly closed by calling ``completeStage()``
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or ``failStage(exception)``. This feature carries the risk of leaking streams and actors, therefore it should be used
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with care.
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Using timers
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------------
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**This section is a stub and will be extended in the next release**
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It is possible to use timers in :class:`GraphStages` by using :class:`TimerGraphStageLogic` as the base class for
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the returned logic. Timers can be scheduled by calling one of ``scheduleOnce(key,delay)``, ``schedulePeriodically(key,period)`` or
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``schedulePeriodicallyWithInitialDelay(key,delay,period)`` and passing an object as a key for that timer (can be any object, for example
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@ -151,11 +295,14 @@ fires. It is possible to cancel a timer using ``cancelTimer(key)`` and check the
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Timers can not be scheduled from the constructor of the logic, but it is possible to schedule them from the
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``preStart()`` lifecycle hook.
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In this sample the stage toggles between open and closed, where open means no elements are passed through. The
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stage starts out as closed but as soon as an element is pushed downstream the gate becomes open for a duration
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of time during which it will consume and drop upstream messages:
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#timed
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Using asynchronous side-channels
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--------------------------------
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**This section is a stub and will be extended in the next release**
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In order to receive asynchronous events that are not arriving as stream elements (for example a completion of a future
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or a callback from a 3rd party API) one must acquire a :class:`AsyncCallback` by calling ``getAsyncCallback()`` from the
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stage logic. The method ``getAsyncCallback`` takes as a parameter a callback that will be called once the asynchronous
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@ -167,6 +314,13 @@ implementation.
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Sharing the AsyncCallback from the constructor risks race conditions, therefore it is recommended to use the
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``preStart()`` lifecycle hook instead.
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This example shows an asynchronous side channel graph stage that starts dropping elements
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when a future completes:
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#async-side-channel
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Integration with actors
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-----------------------
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@ -188,8 +342,6 @@ or ``unwatch(ref)`` methods. The reference can be also watched by external actor
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Custom materialized values
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--------------------------
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**This section is a stub and will be extended in the next release**
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Custom stages can return materialized values instead of ``Unit`` by inheriting from :class:`GraphStageWithMaterializedValue`
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instead of the simpler :class:`GraphStage`. The difference is that in this case the method
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``createLogicAndMaterializedValue(inheritedAttributes)`` needs to be overridden, overridden, and in addition to the
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@ -200,6 +352,10 @@ stage logic the materialized value must be provided
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the thread that got hold of the materialized value. It is the responsibility of the programmer to add the
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necessary (non-blocking) synchronization and visibility guarantees to this shared object.
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In this sample the materialized value is a future containing the first element to go through the stream:
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.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/GraphStageDocTest.java#materialized
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Using attributes to affect the behavior of a stage
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--------------------------------------------------
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@ -213,237 +369,52 @@ decision.
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See :ref:`composition-java` for an explanation on how attributes work.
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Custom linear processing stages
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===============================
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Rate decoupled graph stages
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---------------------------
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To extend the available transformations on a :class:`Flow` or :class:`Source` one can use the ``transform()`` method
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which takes a factory function returning a :class:`Stage`. Stages come in different flavors swhich we will introduce in this
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page.
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Sometimes it is desirable to *decouple* the rate of the upstream and downstream of a stage, synchronizing only
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when needed.
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.. _stream-using-push-pull-stage-java:
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This is achieved in the model by representing a :class:`GraphStage` as a *boundary* between two regions where the
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demand sent upstream is decoupled from the demand that arrives from downstream. One immediate consequence of this
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difference is that an ``onPush`` call does not always lead to calling ``push`` and an ``onPull`` call does not always
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lead to calling ``pull``.
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Using PushPullStage
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-------------------
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The most elementary transformation stage is the :class:`PushPullStage` which can express a large class of algorithms
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working on streams. A :class:`PushPullStage` can be illustrated as a box with two "input" and two "output ports" as it is
|
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seen in the illustration below.
|
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|
||||
|
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|
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.. image:: ../images/stage_conceptual.png
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:align: center
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:width: 600
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|
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|
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|
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The "input ports" are implemented as event handlers ``onPush(elem,ctx)`` and ``onPull(ctx)`` while "output ports"
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correspond to methods on the :class:`Context` object that is handed as a parameter to the event handlers. By calling
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exactly one "output port" method we wire up these four ports in various ways which we demonstrate shortly.
|
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|
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.. warning::
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There is one very important rule to remember when working with a ``Stage``. **Exactly one** method should be called
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on the **currently passed** :class:`Context` **exactly once** and as the **last statement of the handler** where the return type
|
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of the called method **matches the expected return type of the handler**. Any violation of this rule will
|
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almost certainly result in unspecified behavior (in other words, it will break in spectacular ways). Exceptions
|
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to this rule are the query methods ``isHolding()`` and ``isFinishing()``
|
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|
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To illustrate these concepts we create a small :class:`PushPullStage` that implements the ``map`` transformation.
|
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|
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|
|
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|
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.. image:: ../images/stage_map.png
|
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:align: center
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:width: 300
|
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|
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|
|
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|
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Map calls ``ctx.push()`` from the ``onPush()`` handler and it also calls ``ctx.pull()`` form the ``onPull``
|
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handler resulting in the conceptual wiring above, and fully expressed in code below:
|
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|
||||
.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/FlowStagesDocTest.java#one-to-one
|
||||
|
||||
Map is a typical example of a one-to-one transformation of a stream. To demonstrate a many-to-one stage we will implement
|
||||
filter. The conceptual wiring of ``Filter`` looks like this:
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_filter.png
|
||||
:align: center
|
||||
:width: 300
|
||||
|
||||
|
|
||||
|
||||
As we see above, if the given predicate matches the current element we are propagating it downwards, otherwise
|
||||
we return the "ball" to our upstream so that we get the new element. This is achieved by modifying the map
|
||||
example by adding a conditional in the ``onPush`` handler and decide between a ``ctx.pull()`` or ``ctx.push()`` call
|
||||
(and of course not having a mapping ``f`` function).
|
||||
|
||||
.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/FlowStagesDocTest.java#many-to-one
|
||||
|
||||
To complete the picture we define a one-to-many transformation as the next step. We chose a straightforward example stage
|
||||
that emits every upstream element twice downstream. The conceptual wiring of this stage looks like this:
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_doubler.png
|
||||
:align: center
|
||||
:width: 300
|
||||
|
||||
|
|
||||
|
||||
This is a stage that has state: the last element it has seen, and a flag ``oneLeft`` that indicates if we
|
||||
have duplicated this last element already or not. Looking at the code below, the reader might notice that our ``onPull``
|
||||
method is more complex than it is demonstrated by the figure above. The reason for this is completion handling, which we
|
||||
will explain a little bit later. For now it is enough to look at the ``if(!ctx.isFinishing)`` block which
|
||||
corresponds to the logic we expect by looking at the conceptual picture.
|
||||
|
||||
.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/FlowStagesDocTest.java#one-to-many
|
||||
|
||||
Finally, to demonstrate all of the stages above, we put them together into a processing chain, which conceptually
|
||||
would correspond to the following structure:
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_chain.png
|
||||
:align: center
|
||||
:width: 650
|
||||
|
||||
|
|
||||
|
||||
In code this is only a few lines, using the ``transform`` method to inject our custom processing into a stream:
|
||||
|
||||
.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/FlowStagesDocTest.java#stage-chain
|
||||
|
||||
If we attempt to draw the sequence of events, it shows that there is one "event token"
|
||||
in circulation in a potential chain of stages, just like our conceptual "railroad tracks" representation predicts.
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_msc_general.png
|
||||
:align: center
|
||||
|
||||
|
|
||||
|
||||
Completion handling
|
||||
^^^^^^^^^^^^^^^^^^^
|
||||
|
||||
Completion handling usually (but not exclusively) comes into the picture when processing stages need to emit a few
|
||||
more elements after their upstream source has been completed. We have seen an example of this in our ``Duplicator`` class
|
||||
where the last element needs to be doubled even after the upstream neighbor stage has been completed. Since the
|
||||
``onUpstreamFinish()`` handler expects a :class:`TerminationDirective` as the return type we are only allowed to call
|
||||
``ctx.finish()``, ``ctx.fail()`` or ``ctx.absorbTermination()``. Since the first two of these available methods will
|
||||
immediately terminate, our only option is ``absorbTermination()``. It is also clear from the return type of
|
||||
``onUpstreamFinish`` that we cannot call ``ctx.push()`` but we need to emit elements somehow! The trick is that after
|
||||
calling ``absorbTermination()`` the ``onPull()`` handler will be called eventually, and at the same time
|
||||
``ctx.isFinishing`` will return true, indicating that ``ctx.pull()`` cannot be called anymore. Now we are free to
|
||||
emit additional elementss and call ``ctx.finish()`` or ``ctx.pushAndFinish()`` eventually to finish processing.
|
||||
|
||||
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. 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
|
||||
*below* (which means that it will come back eventually, so the environment does not need to call anything yet).
|
||||
|
||||
The first of the two scenarios is when a termination signal arrives after a stage passed the event to its downstream. As
|
||||
we can see in the following diagram, there is no need to do anything by ``absorbTermination()`` since the black arrows
|
||||
representing the movement of the "event token" is uninterrupted.
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_msc_absorb_1.png
|
||||
:align: center
|
||||
|
||||
|
|
||||
|
||||
In the second scenario the "event token" is somewhere upstream when the termination signal arrives. In this case
|
||||
``absorbTermination`` needs to ensure that a new "event token" is generated replacing the old one that is forever gone
|
||||
(since the upstream finished). This is done by calling the ``onPull()`` event handler of the stage.
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_msc_absorb_2.png
|
||||
:align: center
|
||||
|
||||
|
|
||||
|
||||
Observe, that in both scenarios ``onPull()`` kicks off the continuation of the processing logic, the only difference is
|
||||
whether it is the downstream or the ``absorbTermination()`` call that calls the event handler.
|
||||
|
||||
.. warning::
|
||||
It is not allowed to call ``absorbTermination()`` from ``onDownstreamFinish()``. If the method is called anyway,
|
||||
it will be logged at ``ERROR`` level, but no further action will be taken as at that point there is no active
|
||||
downstream to propagate the error to. Cancellation in the upstream direction will continue undisturbed.
|
||||
|
||||
Using PushStage
|
||||
---------------
|
||||
|
||||
Many one-to-one and many-to-one transformations do not need to override the ``onPull()`` handler at all since all
|
||||
they do is just propagate the pull upwards. For such transformations it is better to extend PushStage directly. For
|
||||
example our ``Map`` and ``Filter`` would look like this:
|
||||
|
||||
.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/FlowStagesDocTest.java#pushstage
|
||||
|
||||
The reason to use ``PushStage`` is not just cosmetic: internal optimizations rely on the fact that the onPull method
|
||||
only calls ``ctx.pull()`` and allow the environment do process elements faster than without this knowledge. By
|
||||
extending ``PushStage`` the environment can be sure that ``onPull()`` was not overridden since it is ``final`` on
|
||||
``PushStage``.
|
||||
|
||||
Using DetachedStage
|
||||
-------------------
|
||||
|
||||
The model described in previous sections, while conceptually simple, cannot describe all desired stages. The main
|
||||
limitation is the "single-ball" (single "event token") model which prevents independent progress of an upstream and
|
||||
downstream of a stage. Sometimes it is desirable to *detach* the progress (and therefore, rate) of the upstream and
|
||||
downstream of a stage, synchronizing only when needed.
|
||||
|
||||
This is achieved in the model by representing a :class:`DetachedStage` as a *boundary* between two "single-ball" regions.
|
||||
One immediate consequence of this difference is that **it is not allowed to call** ``ctx.pull()`` **from** ``onPull()`` **and
|
||||
it is not allowed to call** ``ctx.push()`` **from** ``onPush()`` as such combinations would "steal" a token from one region
|
||||
(resulting in zero tokens left) and would inject an unexpected second token to the other region. This is enforced
|
||||
by the expected return types of these callback functions.
|
||||
|
||||
One of the important use-cases for :class:`DetachedStage` is to build buffer-like entities, that allow independent progress
|
||||
One of the important use-case for this is to build buffer-like entities, that allow independent progress
|
||||
of upstream and downstream stages when the buffer is not full or empty, and slowing down the appropriate side if the
|
||||
buffer becomes empty or full. The next diagram illustrates the event sequence for a buffer with capacity of two elements.
|
||||
buffer becomes empty or full.
|
||||
|
||||
The next diagram illustrates the event sequence for a buffer with capacity of two elements in a setting where
|
||||
the downstream demand is slow to start and the buffer will fill up with upstream elements before any demand
|
||||
is seen from downstream.
|
||||
|
||||
|
|
||||
|
||||
.. image:: ../images/stage_msc_buffer.png
|
||||
:align: center
|
||||
.. image:: ../images/graph_stage_detached_tracks_1.png
|
||||
:align: center
|
||||
:width: 500
|
||||
|
||||
|
|
||||
|
||||
The very first difference we can notice is that our ``Buffer`` stage is automatically pulling its upstream on
|
||||
initialization. Remember that it is forbidden to call ``ctx.pull`` from ``onPull``, therefore it is the task of the
|
||||
framework to kick off the first "event token" in the upstream region, which will remain there until the upstream stages
|
||||
stop. The diagram distinguishes between the actions of the two regions by colors: *purple* arrows indicate the actions
|
||||
involving the upstream "event token", while *red* arrows show the downstream region actions. This demonstrates the clear
|
||||
separation of these regions, and the invariant that the number of tokens in the two regions are kept unchanged.
|
||||
Another scenario would be where the demand from downstream starts coming in before any element is pushed
|
||||
into the buffer stage.
|
||||
|
||||
For buffer it is necessary to detach the two regions, but it is also necessary to sometimes hold back the upstream
|
||||
or downstream. The new API calls that are available for :class:`DetachedStage` s are the various ``ctx.holdXXX()`` methods
|
||||
, ``ctx.pushAndPull()`` and variants, and ``ctx.isHoldingXXX()``.
|
||||
Calling ``ctx.holdXXX()`` from ``onPull()`` or ``onPush`` results in suspending the corresponding
|
||||
region from progress, and temporarily taking ownership of the "event token". This state can be queried by ``ctx.isHolding()``
|
||||
which will tell if the stage is currently holding a token or not. It is only allowed to suspend one of the regions, not
|
||||
both, since that would disable all possible future events, resulting in a dead-lock. Releasing the held token is only
|
||||
possible by calling ``ctx.pushAndPull()``. This is to ensure that both the held token is released, and the triggering region
|
||||
gets its token back (one inbound token + one held token = two released tokens).
|
||||
|
||||
The following code example demonstrates the buffer class corresponding to the message sequence chart we discussed.
|
||||
|
|
||||
|
||||
.. includecode:: ../../../akka-samples/akka-docs-java-lambda/src/test/java/docs/stream/FlowStagesDocTest.java#detached
|
||||
.. image:: ../images/graph_stage_detached_tracks_2.png
|
||||
:align: center
|
||||
:width: 500
|
||||
|
||||
.. warning::
|
||||
If ``absorbTermination()`` is called on a :class:`DetachedStage` while it holds downstream (``isHoldingDownstream``
|
||||
returns true) then ``onPull()`` will be called on the stage. This ensures that the stage does not end up in a
|
||||
deadlocked case. Since at the point when the termination is absorbed there will be no way to get any callbacks because
|
||||
the downstream is held, so the framework invokes onPull() to avoid this situation. This is similar to the termination
|
||||
logic already shown for :class:`PushPullStage`.
|
||||
|
|
||||
|
||||
|
||||
The first difference we can notice is that our ``Buffer`` stage is automatically pulling its upstream on
|
||||
initialization. The buffer has demand for up to two elements without any downstream demand.
|
||||
|
||||
The following code example demonstrates a buffer class corresponding to the message sequence chart above.
|
||||
|
||||
.. includecode:: code/docs/stream/GraphStageDocSpec.scala#detached
|
||||
|
||||
Thread safety of custom processing stages
|
||||
=========================================
|
||||
|
|
@ -457,7 +428,7 @@ In essence, the above guarantees are similar to what :class:`Actor` s provide, i
|
|||
stage as state of an actor, and the callbacks as the ``receive`` block of the actor.
|
||||
|
||||
.. warning::
|
||||
It is **not safe** to access the state of any custom stage outside of the callbacks that it provides, just like it
|
||||
is unsafe to access the state of an actor from the outside. This means that Future callbacks should **not close over**
|
||||
internal state of custom stages because such access can be concurrent with the provided callbacks, leading to undefined
|
||||
behavior.
|
||||
It is **not safe** to access the state of any custom stage outside of the callbacks that it provides, just like it
|
||||
is unsafe to access the state of an actor from the outside. This means that Future callbacks should **not close over**
|
||||
internal state of custom stages because such access can be concurrent with the provided callbacks, leading to undefined
|
||||
behavior.
|
||||
|
|
|
|||
Loading…
Add table
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Reference in a new issue