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