Notes on Kafka Stream
less on analystics, more on apps and services that process data streams
most valuable streaming apps is closer to async microservice => implement core functions rather than computing analytics
goal: use mainstream application programming model for asynch services
no cluster manager, just a library
load balancing: same protocol that Kafka provides for normal consumers
KStream and KTable can be converted back and forth
How to do windowed operations on streams if events can arrive out of order => represnet count so far for the window. continously update as new data arrives and allow downstream receiver to decide when it is complete
assigns ts to every data record=> event time or processing time possible