Is there a way to name the inner mapValues() topic created as part of the count() operator in kafka-streams? - apache-kafka

Question

I'm, trying to name all processors of a simple word count kafka streams application, however, can't figure out how to name the inner topic created due to the mapValues() call inside the count() method, that's created as result of calling to stream(). This is the application code, followed by the topology description (showing only the second sub-topology):
def createTopology(builder: StreamsBuilder, config: Config): Topology = {
val consumed = Consumed
.as(inputTopic)
.withKeySerde(Serdes.stringSerde)
.withValueSerde(Serdes.stringSerde)
val produced = Produced
.as(outputTopic)
.withKeySerde(Serdes.stringSerde)
.withValueSerde(Serdes.longSerde)
val flatMapValuesProc = Named.as("flatMapValues")
val groupByProc = Grouped
.as("groupBy")
.withKeySerde(Serdes.stringSerde)
.withValueSerde(Serdes.stringSerde)
val textLines: KStream[String, String] = builder.stream[String, String](inputTopic)(consumed)
val wordCounts: KTable[String, Long] = textLines
.flatMapValues(textLine => textLine.toLowerCase.split("\\W+"), named = flatMapValuesProc)
.groupBy((_, word) => word)(grouped)
.count(Named.as("count"))(Materialized.as(storeName))
wordCounts
.toStream(Named.as("toStream"))
.to(outputTopic)(produced)
builder.build()
}
Looking at the count() method, it seems like it's not possible to name this operation, from the code. Is there another way to name this inner topic?
def count(named: Named)(implicit materialized: Materialized[K, Long, ByteArrayKeyValueStore]): KTable[K, Long] = {
...
new KTable(
javaCountTable.mapValues[Long](
((l: java.lang.Long) => Long2long(l)).asValueMapper,
Materialized.`with`[K, Long, ByteArrayKeyValueStore](tableImpl.keySerde(), Serdes.longSerde)
)
)
}