リファレンス
Scala API
How to Create Akka Streams of Any Shape Using the Graph DSL
Comparing Kafka Streams, Akka Streams and Spark Streaming: what to use when
https://blog.rockthejvm.com/kafka,-akka,-spark/
Akka Streams is best for high-performance systems, when you want to bake Akka Streams into your application. It has an extremely powerful API, but unless you know what you’re doing, it might be easy to shoot yourself (accidentally or not).
Kafka on the other hand works best as an external high performance message bus for your applications, so if you want microservices to read and write to and from a common event store, you might be best with Kafka. However, its Java-style API is cumbersome, but I understand it might be a matter of code cleanliness and taste.
Finally, Spark Streaming is without a doubt best for big data computation. Spark has always been good at that and here we also removed data bounds. However, at the moment of this recording, Spark Streaming is bad for actual application logic and low-latency, so you might want to use it as a data aggregator to gather insights from your data.
Materialized Values in Akka Streams
Log-streamサンプルコード
変更（修正）箇所リスト（リモートのサンプルのコード変更が一部混在）
SDKバージョンが古いため、最新バージョン変更に伴うコード修正