Translated from Java (https://github.com/apache/kafka/blob/trunk/streams/examples/src/main/java/org/apache/kafka/streams/examples/wordcount/WordCountDemo.java) with help from IntelliJ :-)

build.sbt

name := "kafka-wordcount"

version := "1.0"

scalaVersion := "2.12.1"

libraryDependencies += "org.apache.kafka" % "kafka-streams" % "0.10.2.0"

WordCountDemo.scala

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements. See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */


import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.Serdes
import org.apache.kafka.streams.KafkaStreams
import org.apache.kafka.streams.KeyValue
import org.apache.kafka.streams.StreamsConfig
import org.apache.kafka.streams.kstream.KStreamBuilder
import org.apache.kafka.streams.kstream.KStream
import org.apache.kafka.streams.kstream.KTable
import java.util.{Locale, Properties}

/**
  * Demonstrates, using the high-level KStream DSL, how to implement the WordCount program
  * that computes a simple word occurrence histogram from an input text.
  *
  * In this example, the input stream reads from a topic named "streams-file-input", where the values of messages
  * represent lines of text; and the histogram output is written to topic "streams-wordcount-output" where each record
  * is an updated count of a single word.
  *
  * Before running this example you must create the input topic and the output topic (e.g. via
  * bin/kafka-topics.sh --create ...), and write some data to the input topic (e.g. via
  * bin/kafka-console-producer.sh). Otherwise you won't see any data arriving in the output topic.
  */
object WordCountDemoScala {

  def main(args: Array[String]): Unit = {
    val props = new Properties
    props.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams-wordcount")
    props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092")
    props.put(StreamsConfig.KEY_SERDE_CLASS_CONFIG, Serdes.String.getClass.getName)
    props.put(StreamsConfig.VALUE_SERDE_CLASS_CONFIG, Serdes.String.getClass.getName)

    // setting offset reset to earliest so that we can re-run the demo code with the same pre-loaded data
    // Note: To re-run the demo, you need to use the offset reset tool:
    // https://cwiki.apache.org/confluence/display/KAFKA/Kafka+Streams+Application+Reset+Tool
    props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

    import scala.collection.JavaConverters._

    val builder = new KStreamBuilder
    val source: KStream[String, String] = builder.stream("streams-file-input")
    val counts: KTable[String, java.lang.Long] = source.
      flatMapValues[String] { _.toLowerCase(Locale.getDefault).split(" ").toList.asJava }.
      map[String, String] { (key, value) => new KeyValue(value, value) }.
      groupByKey.count("Counts")

    // need to override value serde to Long type
    counts.to(Serdes.String, Serdes.Long, "streams-wordcount-output")

    val streams = new KafkaStreams(builder, props)
    streams.start()
    // usually the stream application would be running forever,
    // in this example we just let it run for some time and stop since the input data is finite.
    Thread.sleep(5000L)
    streams.close()
  }
}

See http://scastie.org/30490

Cool, thanks, Adriaan... this helped me see how I wasn't providing the map types that I assumed could be inferred..
Cheers,
Robert