object Source
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def
actorRef[T](bufferSize: Int, overflowStrategy: OverflowStrategy): Source[T, ActorRef]
Creates a
Source
that is materialized as an akka.actor.ActorRef.Creates a
Source
that is materialized as an akka.actor.ActorRef. Messages sent to this actor will be emitted to the stream if there is demand from downstream, otherwise they will be buffered until request for demand is received.Depending on the defined akka.stream.OverflowStrategy it might drop elements if there is no space available in the buffer.
The strategy akka.stream.OverflowStrategy.backpressure is not supported, and an IllegalArgument("Backpressure overflowStrategy not supported") will be thrown if it is passed as argument.
The buffer can be disabled by using
bufferSize
of 0 and then received messages are dropped if there is no demand from downstream. WhenbufferSize
is 0 theoverflowStrategy
does not matter. An async boundary is added after this Source; as such, it is never safe to assume the downstream will always generate demand.The stream can be completed successfully by sending the actor reference a akka.actor.Status.Success (whose content will be ignored) in which case already buffered elements will be signaled before signaling completion.
The stream can be completed successfully by sending the actor reference a akka.actor.Status.Success. If the content is akka.stream.CompletionStrategy.immediately the completion will be signaled immidiately, otherwise if the content is akka.stream.CompletionStrategy.draining (or anything else) already buffered elements will be signaled before siganling completion. Sending akka.actor.PoisonPill will signal completion immediately but this behavior is deprecated and scheduled to be removed.
The stream can be completed with failure by sending a akka.actor.Status.Failure to the actor reference. In case the Actor is still draining its internal buffer (after having received a akka.actor.Status.Success) before signaling completion and it receives a akka.actor.Status.Failure, the failure will be signaled downstream immediately (instead of the completion signal).
Note that terminating the actor without first completing it, either with a success or a failure, will prevent the actor triggering downstream completion and the stream will continue to run even though the source actor is dead. Therefore you should **not** attempt to manually terminate the actor such as with a akka.actor.PoisonPill.
The actor will be stopped when the stream is completed, failed or canceled from downstream, i.e. you can watch it to get notified when that happens.
See also akka.stream.javadsl.Source.queue.
- bufferSize
The size of the buffer in element count
- overflowStrategy
Strategy that is used when incoming elements cannot fit inside the buffer
-
def
actorRefWithAck[T](ackMessage: Any): Source[T, ActorRef]
Creates a
Source
that is materialized as an akka.actor.ActorRef.Creates a
Source
that is materialized as an akka.actor.ActorRef. Messages sent to this actor will be emitted to the stream if there is demand from downstream, and a new message will only be accepted after the previous messages has been consumed and acknowledged back. The stream will complete with failure if a message is sent before the acknowledgement has been replied back.The stream can be completed successfully by sending the actor reference a akka.actor.Status.Success. If the content is akka.stream.CompletionStrategy.immediately the completion will be signaled immidiately, otherwise if the content is akka.stream.CompletionStrategy.draining (or anything else) already buffered element will be signaled before siganling completion.
The stream can be completed with failure by sending a akka.actor.Status.Failure to the actor reference. In case the Actor is still draining its internal buffer (after having received a akka.actor.Status.Success) before signaling completion and it receives a akka.actor.Status.Failure, the failure will be signaled downstream immediately (instead of the completion signal).
The actor will be stopped when the stream is completed, failed or canceled from downstream, i.e. you can watch it to get notified when that happens.
-
def
asSubscriber[T](): Source[T, Subscriber[T]]
Creates a
Source
that is materialized as a org.reactivestreams.Subscriber -
def
combine[T, U](first: Source[T, _], second: Source[T, _], rest: List[Source[T, _]], strategy: Function[Integer, _ <: Graph[UniformFanInShape[T, U], NotUsed]]): Source[U, NotUsed]
Combines several sources with fan-in strategy like
Merge
orConcat
and returnsSource
. -
def
combineMat[T, U, M1, M2, M](first: Source[T, M1], second: Source[T, M2], strategy: Function[Integer, _ <: Graph[UniformFanInShape[T, U], NotUsed]], combine: Function2[M1, M2, M]): Source[U, M]
Combines two sources with fan-in strategy like
Merge
orConcat
and returnsSource
with a materialized value. -
def
cycle[O](f: Creator[Iterator[O]]): Source[O, NotUsed]
Helper to create 'cycled' Source from iterator provider.
Helper to create 'cycled' Source from iterator provider. Example usage:
Source.cycle(() -> Arrays.asList(1, 2, 3).iterator());
Start a new 'cycled'
Source
from the given elements. The producer stream of elements will continue infinitely by repeating the sequence of elements provided by function parameter. -
def
empty[T](clazz: Class[T]): Source[T, NotUsed]
Create a
Source
with no elements.Create a
Source
with no elements. The result is the same as callingSource.<O>empty()
-
def
empty[O](): Source[O, NotUsed]
Create a
Source
with no elements, i.e.Create a
Source
with no elements, i.e. an empty stream that is completed immediately for every connectedSink
. -
def
failed[T](cause: Throwable): Source[T, NotUsed]
Create a
Source
that immediately ends the stream with thecause
failure to every connectedSink
. -
def
from[O](iterable: Iterable[O]): Source[O, NotUsed]
Helper to create Source from
Iterable
.Helper to create Source from
Iterable
. Example usage:List<Integer> data = new ArrayList<Integer>(); data.add(1); data.add(2); data.add(3); Source.from(data);
Starts a new
Source
from the givenIterable
. This is like starting from an Iterator, but every Subscriber directly attached to the Publisher of this stream will see an individual flow of elements (always starting from the beginning) regardless of when they subscribed.Make sure that the
Iterable
is immutable or at least not modified after being used as aSource
. Otherwise the stream may fail withConcurrentModificationException
or other more subtle errors may occur. -
def
fromCompletionStage[O](future: CompletionStage[O]): Source[O, NotUsed]
Starts a new
Source
from the givenCompletionStage
.Starts a new
Source
from the givenCompletionStage
. The stream will consist of one element when theCompletionStage
is completed with a successful value, which may happen before or after materializing theFlow
. The stream terminates with a failure if theCompletionStage
is completed with a failure. -
def
fromFuture[O](future: Future[O]): Source[O, NotUsed]
Start a new
Source
from the givenFuture
.Start a new
Source
from the givenFuture
. The stream will consist of one element when theFuture
is completed with a successful value, which may happen before or after materializing theFlow
. The stream terminates with a failure if theFuture
is completed with a failure. -
def
fromFutureSource[T, M](future: Future[_ <: Graph[SourceShape[T], M]]): Source[T, Future[M]]
Streams the elements of the given future source once it successfully completes.
Streams the elements of the given future source once it successfully completes. If the Future fails the stream is failed with the exception from the future. If downstream cancels before the stream completes the materialized Future will be failed with a StreamDetachedException.
-
def
fromGraph[T, M](g: Graph[SourceShape[T], M]): Source[T, M]
A graph with the shape of a source logically is a source, this method makes it so also in type.
-
def
fromIterator[O](f: Creator[Iterator[O]]): Source[O, NotUsed]
Helper to create Source from
Iterator
.Helper to create Source from
Iterator
. Example usage:List<Integer> data = new ArrayList<Integer>(); data.add(1); data.add(2); data.add(3); Source.from(() -> data.iterator());
Start a new
Source
from the given Iterator. The produced stream of elements will continue until the iterator runs empty or fails during evaluation of thenext()
method. Elements are pulled out of the iterator in accordance with the demand coming from the downstream transformation steps. -
def
fromPublisher[O](publisher: Publisher[O]): Source[O, NotUsed]
Helper to create Source from
Publisher
.Helper to create Source from
Publisher
.Construct a transformation starting with given publisher. The transformation steps are executed by a series of org.reactivestreams.Processor instances that mediate the flow of elements downstream and the propagation of back-pressure upstream.
-
def
fromSourceCompletionStage[T, M](completion: CompletionStage[_ <: Graph[SourceShape[T], M]]): Source[T, CompletionStage[M]]
Streams the elements of an asynchronous source once its given CompletionStage completes.
Streams the elements of an asynchronous source once its given CompletionStage completes. If the CompletionStage fails the stream is failed with the exception from the future. If downstream cancels before the stream completes the materialized CompletionStage will be failed with a StreamDetachedException
-
def
lazily[T, M](create: Creator[Source[T, M]]): Source[T, CompletionStage[M]]
Creates a
Source
that is not materialized until there is downstream demand, when the source gets materialized the materialized future is completed with its value, if downstream cancels or fails without any demand thecreate
factory is never called and the materializedCompletionStage
is failed. -
def
lazilyAsync[T](create: Creator[CompletionStage[T]]): Source[T, Future[NotUsed]]
Creates a
Source
from supplied future factory that is not called until downstream demand.Creates a
Source
from supplied future factory that is not called until downstream demand. When source gets materialized the materialized future is completed with the value from the factory. If downstream cancels or fails without any demand the create factory is never called and the materializedFuture
is failed.- See also
-
def
maybe[T]: Source[T, CompletableFuture[Optional[T]]]
Create a
Source
which materializes a java.util.concurrent.CompletableFuture which controls what element will be emitted by the Source.Create a
Source
which materializes a java.util.concurrent.CompletableFuture which controls what element will be emitted by the Source. If the materialized promise is completed with a filled Optional, that value will be produced downstream, followed by completion. If the materialized promise is completed with an empty Optional, no value will be produced downstream and completion will be signalled immediately. If the materialized promise is completed with a failure, then the returned source will terminate with that error. If the downstream of this source cancels before the promise has been completed, then the promise will be completed with an empty Optional. -
def
queue[T](bufferSize: Int, overflowStrategy: OverflowStrategy): Source[T, SourceQueueWithComplete[T]]
Creates a
Source
that is materialized as an akka.stream.javadsl.SourceQueue.Creates a
Source
that is materialized as an akka.stream.javadsl.SourceQueue. You can push elements to the queue and they will be emitted to the stream if there is demand from downstream, otherwise they will be buffered until request for demand is received. Elements in the buffer will be discarded if downstream is terminated.Depending on the defined akka.stream.OverflowStrategy it might drop elements if there is no space available in the buffer.
Acknowledgement mechanism is available. akka.stream.javadsl.SourceQueue.offer returns
CompletionStage<QueueOfferResult>
which completes withQueueOfferResult.enqueued
if element was added to buffer or sent downstream. It completes withQueueOfferResult.dropped
if element was dropped. Can also complete withQueueOfferResult.Failure
- when stream failed orQueueOfferResult.QueueClosed
when downstream is completed.The strategy akka.stream.OverflowStrategy.backpressure will not complete last
offer():CompletionStage
call when buffer is full.You can watch accessibility of stream with akka.stream.javadsl.SourceQueue.watchCompletion. It returns a future that completes with success when this operator is completed or fails when stream is failed.
The buffer can be disabled by using
bufferSize
of 0 and then received message will wait for downstream demand unless there is another message waiting for downstream demand, in that case offer result will be completed according to the overflow strategy.SourceQueue that current source is materialized to is for single thread usage only.
- bufferSize
size of buffer in element count
- overflowStrategy
Strategy that is used when incoming elements cannot fit inside the buffer
-
def
range(start: Int, end: Int, step: Int): Source[Integer, NotUsed]
Creates Source that represents integer values in range [start;end], with the given step.
Creates Source that represents integer values in range [start;end], with the given step. It allows to create
Source
out of range as simply as on ScalaSource(1 to N)
Uses Int, Int) internally
- See also
Int, Int)
-
def
range(start: Int, end: Int): Source[Integer, NotUsed]
Creates Source that represents integer values in range [start;end], step equals to 1.
Creates Source that represents integer values in range [start;end], step equals to 1. It allows to create
Source
out of range as simply as on ScalaSource(1 to N)
Uses Int) internally
- See also
Int)
-
def
repeat[T](element: T): Source[T, NotUsed]
Create a
Source
that will continually emit the given element. -
def
setup[T, M](factory: BiFunction[ActorMaterializer, Attributes, Source[T, M]]): Source[T, CompletionStage[M]]
Defers the creation of a Source until materialization.
Defers the creation of a Source until materialization. The
factory
function exposes ActorMaterializer which is going to be used during materialization and Attributes of the Source returned by this method. -
def
single[T](element: T): Source[T, NotUsed]
Create a
Source
with one element.Create a
Source
with one element. Every connectedSink
of this stream will see an individual stream consisting of one element. -
def
tick[O](initialDelay: Duration, interval: Duration, tick: O): Source[O, Cancellable]
Elements are emitted periodically with the specified interval.
Elements are emitted periodically with the specified interval. The tick element will be delivered to downstream consumers that has requested any elements. If a consumer has not requested any elements at the point in time when the tick element is produced it will not receive that tick element later. It will receive new tick elements as soon as it has requested more elements.
- Annotations
- @silent()
-
def
unfold[S, E](s: S, f: Function[S, Optional[Pair[S, E]]]): Source[E, NotUsed]
Create a
Source
that will unfold a value of typeS
into a pair of the next stateS
and output elements of typeE
. -
def
unfoldAsync[S, E](s: S, f: Function[S, CompletionStage[Optional[Pair[S, E]]]]): Source[E, NotUsed]
Same as unfold, but uses an async function to generate the next state-element tuple.
-
def
unfoldResource[T, S](create: Creator[S], read: Function[S, Optional[T]], close: Procedure[S]): Source[T, NotUsed]
Start a new
Source
from some resource which can be opened, read and closed.Start a new
Source
from some resource which can be opened, read and closed. Interaction with resource happens in a blocking way.Example:
Source.unfoldResource( () -> new BufferedReader(new FileReader("...")), reader -> reader.readLine(), reader -> reader.close())
You can use the supervision strategy to handle exceptions for
read
function. All exceptions thrown bycreate
orclose
will fail the stream.Restart
supervision strategy will close and create blocking IO again. Default strategy isStop
which means that stream will be terminated on error inread
function by default.You can configure the default dispatcher for this Source by changing the
akka.stream.materializer.blocking-io-dispatcher
or set it for a given Source by using ActorAttributes.Adheres to the ActorAttributes.SupervisionStrategy attribute.
- create
- function that is called on stream start and creates/opens resource.
- read
- function that reads data from opened resource. It is called each time backpressure signal is received. Stream calls close and completes when
read
returns None.- close
- function that closes resource
-
def
unfoldResourceAsync[T, S](create: Creator[CompletionStage[S]], read: Function[S, CompletionStage[Optional[T]]], close: Function[S, CompletionStage[Done]]): Source[T, NotUsed]
Start a new
Source
from some resource which can be opened, read and closed.Start a new
Source
from some resource which can be opened, read and closed. It's similar tounfoldResource
but takes functions that returnCompletionStage
instead of plain values.You can use the supervision strategy to handle exceptions for
read
function or failures of producedFutures
. All exceptions thrown bycreate
orclose
as well as fails of returned futures will fail the stream.Restart
supervision strategy will close and create resource. Default strategy isStop
which means that stream will be terminated on error inread
function (or future) by default.You can configure the default dispatcher for this Source by changing the
akka.stream.materializer.blocking-io-dispatcher
or set it for a given Source by using ActorAttributes.Adheres to the ActorAttributes.SupervisionStrategy attribute.
- create
- function that is called on stream start and creates/opens resource.
- read
- function that reads data from opened resource. It is called each time backpressure signal is received. Stream calls close and completes when
CompletionStage
from read function returns None.- close
- function that closes resource
-
def
upcast[SuperOut, Out <: SuperOut, Mat](source: Source[Out, Mat]): Source[SuperOut, Mat]
Upcast a stream of elements to a stream of supertypes of that element.
Upcast a stream of elements to a stream of supertypes of that element. Useful in combination with fan-in operators where you do not want to pay the cost of casting each element in a
map
.Example:
Source<Apple, NotUsed> apples = Source.single(new Apple()); Source<Orange, NotUsed> oranges = Source.single(new Orange()); Source<Fruit, NotUsed> appleFruits = Source.upcast(apples); Source<Fruit, NotUsed> orangeFruits = Source.upcast(oranges); Source<Fruit, NotUsed> fruits = appleFruits.merge(orangeFruits);
- SuperOut
a supertype to the type of elements in stream
- returns
A source with the supertype as elements
-
def
zipN[T](sources: List[Source[T, _]]): Source[List[T], NotUsed]
Combine the elements of multiple streams into a stream of lists.
- def zipWithN[T, O](zipper: Function[List[T], O], sources: List[Source[T, _]]): Source[O, NotUsed]
Deprecated Value Members
-
def
actorPublisher[T](props: Props): Source[T, ActorRef]
Creates a
Source
that is materialized to an akka.actor.ActorRef which points to an Actor created according to the passed in akka.actor.Props.Creates a
Source
that is materialized to an akka.actor.ActorRef which points to an Actor created according to the passed in akka.actor.Props. Actor created by theprops
should be akka.stream.actor.ActorPublisher.- Annotations
- @deprecated
- Deprecated
(Since version 2.5.0) Use
akka.stream.stage.GraphStage
andfromGraph
instead, it allows for all operations an Actor would and is more type-safe as well as guaranteed to be ReactiveStreams compliant.
-
def
tick[O](initialDelay: FiniteDuration, interval: FiniteDuration, tick: O): Source[O, Cancellable]
Elements are emitted periodically with the specified interval.
Elements are emitted periodically with the specified interval. The tick element will be delivered to downstream consumers that has requested any elements. If a consumer has not requested any elements at the point in time when the tick element is produced it will not receive that tick element later. It will receive new tick elements as soon as it has requested more elements.
- Annotations
- @Deprecated @deprecated
- Deprecated
(Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.