pekko/akka-docs/rst/scala/code/docs/stream/cookbook/RecipeReduceByKey.scala

76 lines
2.2 KiB
Scala
Raw Normal View History

2014-12-08 17:29:40 +01:00
package docs.stream.cookbook
import akka.NotUsed
import akka.stream.{ Graph, FlowShape, Inlet, Outlet, Attributes, OverflowStrategy }
2014-12-08 17:29:40 +01:00
import akka.stream.scaladsl._
import scala.concurrent.{ Await, Future }
import scala.concurrent.duration._
import akka.stream.stage.{ GraphStage, GraphStageLogic }
2014-12-08 17:29:40 +01:00
class RecipeReduceByKey extends RecipeSpec {
"Reduce by key recipe" must {
val MaximumDistinctWords = 1000
2014-12-08 17:29:40 +01:00
"work with simple word count" in {
def words = Source(List("hello", "world", "and", "hello", "universe", "akka") ++ List.fill(1000)("rocks!"))
//#word-count
val counts: Source[(String, Int), NotUsed] = words
// split the words into separate streams first
.groupBy(MaximumDistinctWords, identity)
2016-01-15 22:51:26 -05:00
//transform each element to pair with number of words in it
.map(_ -> 1)
// add counting logic to the streams
2016-01-15 22:51:26 -05:00
.reduce((l, r) => (l._1, l._2 + r._2))
// get a stream of word counts
.mergeSubstreams
2014-12-08 17:29:40 +01:00
//#word-count
Await.result(counts.limit(10).runWith(Sink.seq), 3.seconds).toSet should be(Set(
2014-12-08 17:29:40 +01:00
("hello", 2),
("world", 1),
("and", 1),
("universe", 1),
("akka", 1),
("rocks!", 1000)))
}
"work generalized" in {
def words = Source(List("hello", "world", "and", "hello", "universe", "akka") ++ List.fill(1000)("rocks!"))
//#reduce-by-key-general
def reduceByKey[In, K, Out](
maximumGroupSize: Int,
2014-12-08 17:29:40 +01:00
groupKey: (In) => K,
2016-01-15 22:51:26 -05:00
map: (In) => Out)(reduce: (Out, Out) => Out): Flow[In, (K, Out), NotUsed] = {
2014-12-08 17:29:40 +01:00
Flow[In]
2016-01-15 22:51:26 -05:00
.groupBy[K](maximumGroupSize, groupKey)
.map(e => groupKey(e) -> map(e))
.reduce((l, r) => l._1 -> reduce(l._2, r._2))
.mergeSubstreams
2014-12-08 17:29:40 +01:00
}
2016-01-15 22:51:26 -05:00
val wordCounts = words.via(
reduceByKey(MaximumDistinctWords,
groupKey = (word: String) => word,
map = (word: String) => 1)((left: Int, right: Int) => left + right))
2014-12-08 17:29:40 +01:00
//#reduce-by-key-general
Await.result(wordCounts.limit(10).runWith(Sink.seq), 3.seconds).toSet should be(Set(
2014-12-08 17:29:40 +01:00
("hello", 2),
("world", 1),
("and", 1),
("universe", 1),
("akka", 1),
("rocks!", 1000)))
}
}
}