Implement a Kafka Streams punctuator on stream time to emit periodic aggregation results without relying on wall-clock time

Steps

1. In a Transformer or Processor implementation, obtain a ProcessorContext and call context.schedule(Duration.ofSeconds(30), PunctuationType.STREAM_TIME, timestamp -> { ... }) inside init()
2. Inside the punctuator lambda, iterate the local state store using store.all() or store.range(), emit aggregated records via context.forward(), and optionally clear processed entries
3. Use PunctuationType.STREAM_TIME to fire only when records advance stream time, ensuring the punctuator is deterministic and replays correctly during reprocessing
4. Use PunctuationType.WALL_CLOCK_TIME only for side effects that should fire regardless of data flow (e.g., health checks), not for data emission, because it breaks determinism
5. Register the transformer in the topology with builder.addProcessor() and connect it to the relevant state store via connectProcessorAndStateStores()