Real-Time Data Analysis with Apache Kafka

on YouTube ↗55m

" summary

A practical walkthrough of Kafka Streams showing a Java word-count example that uses flatMap → groupBy → count, writes results to a topic, and builds a KTable-backed state stored locally in RocksDB with two internal topics. Covers Kafka Streams features: exactly-once delivery semantics, partition-count requirements for joins, scaling limits tied to partition count, runtime thread-per-instance behavior (avoid colocating with brokers), integration via Kafka Connect, and a comparison with Spark Streaming and Flink.

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" chapters (9)

1. 0:00Kafka intro
2. 6:02Kafka basics & benefits
3. 13:24Kafka Streams processing
4. 27:35Kafka Streams code
5. 35:17Scaling Kafka Streams
6. 41:57Kafka Streams vs alternatives
7. 48:37Kafka in IoT
8. 50:22Kafka monitoring
9. 54:19Summary & Q&A

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