This object provides extension methods to create Java Streams that operate on Scala collections (sequentially or in parallel). For more information on Java streams, consult the documentation (https://docs.oracle.com/javase/8/docs/api/java/util/stream/package-summary.html).
When writing Java code, use the explicit conversion methods defined in javaapi.StreamConverters instead.
asJavaParStream convert a collection to a Java Stream:
scala> import scala.jdk.StreamConverters._ scala> val s = (1 to 10).toList.asJavaSeqStream s: java.util.stream.IntStream = java.util.stream.IntPipeline$Head@7b1e5e55 scala> s.map(_ * 2).filter(_ > 5).toScala(List) res1: List[Int] = List(6, 8, 10, 12, 14, 16, 18, 20)
Note: using parallel streams in the Scala REPL causes deadlocks, see
https://github.com/scala/bug/issues/9076. As a workaround, use
scala> def isPrime(n: Int): Boolean = !(2 +: (3 to Math.sqrt(n).toInt by 2) exists (n % _ == 0)) isPrime: (n: Int)Boolean scala> (10000 to 1000000).asJavaParStream.filter(isPrime).toScala(Vector) res6: scala.collection.immutable.Vector[Int] = Vector(10007, 10009, 10037, 10039, ...
A Java Stream provides operations on a sequence of elements. Streams are created from Spliterators, which are similar to Iterators with the additional capability to partition off some of their elements. This partitioning, if supported by the Spliterator, is used for parallelizing Stream operations.
asJavaSeqStream extension method is available on any Scala collection. The
asJavaParStream extension method can only be invoked on collections where the return type of
stepper method is marked with the
scala.collection.Stepper.EfficientSplit marker trait. This trait is added to steppers that
support partitioning, and therefore efficient parallel processing.
The following extension methods are available:
asJavaPrimitiveStream method converts a
Stream[Int] to an
IntStream. It is the dual
boxed method defined on primitive streams (e.g.,
IntStream.boxed is a
toScala extension methods on Java streams collects the result of a stream pipeline into a
Scala collection, for example
stream.toScala(Vector). Note that
transformation operations on streams are lazy (also called "intermediate"), terminal operations
toScala trigger the evaluation.
Collecting a parallel stream to a collection can be performed in parallel. This is beneficial if
the target collection supports efficient merging of the segments that are built in parallel.
To support this use case, the Scala standard library provides the Accumulator collection.
This collection supports efficient parallel construction, and it has specialized subtypes for
Double so that primitive Java streams can be collected to a Scala collection
without boxing the elements.