Source.queue
Materialize a BoundedSourceQueue
or SourceQueue
onto which elements can be pushed for emitting from the source.
Signature (BoundedSourceQueue
)
Description (BoundedSourceQueue
)
The BoundedSourceQueue
is an optimized variant of the SourceQueue
with OverflowStrategy.dropNew
. The BoundedSourceQueue
will give immediate, synchronous feedback whether an element was accepted or not and is therefore recommended for situations where overload and dropping elements is expected and needs to be handled quickly.
In contrast, the SourceQueue
offers more variety of OverflowStrategies
but feedback is only asynchronously provided through a Future
CompletionStage
value. In cases where elements need to be discarded quickly at times of overload to avoid out-of-memory situations, delivering feedback asynchronously can itself become a problem. This happens if elements come in faster than the feedback can be delivered in which case the feedback mechanism itself is part of the reason that an out-of-memory situation arises.
In summary, prefer BoundedSourceQueue
over SourceQueue
with OverflowStrategy.dropNew
especially in high-load scenarios. Use SourceQueue
if you need one of the other OverflowStrategies
.
The BoundedSourceQueue
contains a buffer that can be used by many producers on different threads. When the buffer is full, the BoundedSourceQueue
will not accept more elements. The return value of BoundedSourceQueue.offer()
immediately returns a QueueOfferResult
(as opposed to an asynchronous value returned by SourceQueue
). A synchronous result is important in order to avoid situations where offer acknowledgements are handled slower than the rate of which elements are offered, which will eventually lead to an Out Of Memory error.
Example (BoundedSourceQueue
)
- Scala
-
source
val bufferSize = 1000 val queue = Source .queue[Int](bufferSize) .map(x => x * x) .toMat(Sink.foreach(x => println(s"completed $x")))(Keep.left) .run() val fastElements = 1 to 10 fastElements.foreach { x => queue.offer(x) match { case QueueOfferResult.Enqueued => println(s"enqueued $x") case QueueOfferResult.Dropped => println(s"dropped $x") case QueueOfferResult.Failure(ex) => println(s"Offer failed ${ex.getMessage}") case QueueOfferResult.QueueClosed => println("Source Queue closed") } }
- Java
-
source
int bufferSize = 10; int elementsToProcess = 5; BoundedSourceQueue<Integer> sourceQueue = Source.<Integer>queue(bufferSize) .throttle(elementsToProcess, Duration.ofSeconds(3)) .map(x -> x * x) .to(Sink.foreach(x -> System.out.println("got: " + x))) .run(system); List<Integer> fastElements = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10); fastElements.stream() .forEach( x -> { QueueOfferResult result = sourceQueue.offer(x); if (result == QueueOfferResult.enqueued()) { System.out.println("enqueued " + x); } else if (result == QueueOfferResult.dropped()) { System.out.println("dropped " + x); } else if (result instanceof QueueOfferResult.Failure) { QueueOfferResult.Failure failure = (QueueOfferResult.Failure) result; System.out.println("Offer failed " + failure.cause().getMessage()); } else if (result instanceof QueueOfferResult.QueueClosed$) { System.out.println("Bounded Source Queue closed"); } });
Signature (SourceQueue
)
Source.queue
Source.queue
Source.queue
Source.queue
Description (SourceQueue
)
Materialize a SourceQueue
onto which elements can be pushed for emitting from the source. The queue contains a buffer, if elements are pushed onto the queue faster than the source is consumed the overflow will be handled with a strategy specified by the user. Functionality for tracking when an element has been emitted is available through SourceQueue.offer
.
Using Source.queue
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.
In combination with the queue, the throttle
operator can be used to control the processing to a given limit, e.g. 5 elements
per 3 seconds
.
Example (SourceQueue
)
- Scala
-
source
val bufferSize = 10 val elementsToProcess = 5 val queue = Source .queue[Int](bufferSize) .throttle(elementsToProcess, 3.second) .map(x => x * x) .toMat(Sink.foreach(x => println(s"completed $x")))(Keep.left) .run() val source = Source(1 to 10) source .map(x => { queue.offer(x).map { case QueueOfferResult.Enqueued => println(s"enqueued $x") case QueueOfferResult.Dropped => println(s"dropped $x") case QueueOfferResult.Failure(ex) => println(s"Offer failed ${ex.getMessage}") case QueueOfferResult.QueueClosed => println("Source Queue closed") } }) .runWith(Sink.ignore)
- Java
-
source
int bufferSize = 10; int elementsToProcess = 5; BoundedSourceQueue<Integer> sourceQueue = Source.<Integer>queue(bufferSize) .throttle(elementsToProcess, Duration.ofSeconds(3)) .map(x -> x * x) .to(Sink.foreach(x -> System.out.println("got: " + x))) .run(system); Source<Integer, NotUsed> source = Source.from(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)); source.map(x -> sourceQueue.offer(x)).runWith(Sink.ignore(), system);
Reactive Streams semantics
emits when there is demand and the queue contains elements
completes when downstream completes