Data processing with Kafka Streams and Spring Framework. Dmitriy Sergeev. Java Fest 2020 Online

on YouTube ↗51m

" summary

A demo building a real-time app that uses Kafka Streams together with Spring to process Raspberry Pi weather-sensor data. It explains Kafka Streams concepts (time semantics, windows, aggregations, processing graphs/topologies) and why time handling can cause difficult debugging, and also covers deployment considerations for Kafka Streams applications using Spring Cloud abstractions.

AI-written summary · about

" chapters (16)

1. 0:00Introduction
2. 1:16Why Kafka named Kafka
3. 3:03Kafka Streams overview
4. 8:23Kafka Streams architecture
5. 10:08Kafka Streams with Spring
6. 11:53Spring Cloud Stream
7. 13:17Live coding start
8. 16:46Windowed averages
9. 22:32Stateful vs stateless
10. 23:57State storage recovery
11. 27:37Windowed aggregations
12. 31:37App demo launch
13. 35:29Time in Kafka Streams
14. 37:41Offline data issues
15. 42:50Deployment nuances
16. 44:16Useful links

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