Live Coding: Building Stateful and Scalable Reactive Streams...
summary
Live-codes a working pipeline that reads partitioned Kafka quotes, groups by symbol, and computes 10‑second windows (max 10 substreams) to emit max/min and percent change alerts. Uses Akka Streams statefulMapConcat, mapAsync to ask sharded actors, and a Source.queue to push actor-generated alerts back into the stream. Shows per-symbol cluster sharding so each company has one actor, commits Kafka offsets after ack, and demos threshold alerts running end-to-end.
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chapters (14)
- 0:00Intro
- 0:25Agenda
- 1:22M1 Finance
- 1:36Backend Services
- 1:50Stateful vs Stateless
- 3:18Akka Streams
- 5:09Akka Cluster Sharding
- 6:06Use Case
- 7:05Models
- 7:39Mapkincat
- 18:43Sharded Actor
- 20:19Bounded Source Queue
- 22:04Map Async
- 27:39Kafka Cluster Sharding
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