This video will show you how to use Spring Cloud Stream + Kafka to aggregate min, max based on windowed-event-time in the fast ways (real-time). As long as data arrives in your data ingestion platform, it will be aggregated immediately, even with the late arriving records. It will help us to resolve 4 common problem with typical batch processing: real-time, accuracy with late arriving records, scalability/no performance issues with db query, alerts.
- Youtube Part1: https://youtu.be/cP9yaMc_Bm0
- Youtube Part2: https://youtu.be/U8HLKvMR4lk
- Kafka: https://kafka.apache.org/
- Spring Cloud Stream: https://cloud.spring.io/spring-cloud-stream/
- Github Link: mem-aggregator
This video will show you how to do data analytics using Spring Cloud Stream + Kafka. As long as data arrives in your data ingestion platform, it will be analyzed immediately, even with the late arriving records. It will help us to resolve 4 common problem with typical batch processing: real-time, accuracy with late arriving records, scalability/no performance issues with db query, alerts.
- Youtube: https://youtu.be/wJAHvCnkt1A
- Kafka: https://kafka.apache.org/
- Spring Cloud Stream: https://cloud.spring.io/spring-cloud-stream/
- MongoDB: https://www.mongodb.com/
- Github Link: mem-analytics
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