From Functional to Reactive Programming

on YouTube ↗01h 04m

" summary

Argues that reactive = functional++: start with functional composition and lazy streams, then add back pressure and three channels (data, error, complete). Shows Java examples (streams vs Flowable/Reactive Streams), using emit/subscribe, observeOn(Schedulers.io), and backpressure strategies drop or buffer to handle faster producers. Points to real systems — Excel, Google Docs, Kafka, AWS Lambda — and cites a customer case of ~70 million users in 48 hours to justify elasticity and message‑driven design.

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" chapters (15)

1. 0:00Introduction to Reactivity
2. 1:00Functional Programming Roots
3. 5:53Revisiting Paradigm Shifts
4. 11:17Lists vs. Streams
5. 15:20Understanding Lazy Evaluation
6. 22:10Efficiency and Deadlines
7. 26:28What is Reactive Programming?
8. 28:46Real-world Reactive Examples
9. 31:43Moving Beyond CRUD
10. 36:20Pillars of Reactive Systems
11. 42:50Resilience in Applications
12. 49:03Implementing Reactive Streams
13. 51:10Java Streams vs. Reactive
14. 52:30Handling Errors and Backpressure
15. 56:57Conclusion and Summary

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