Apache Kafka - Real-time Stream Processing (Master Class) - KTable Aggregation using Aggregate()

The video tutorial explains the use of K tables for aggregation in Kafka streams, focusing on handling update streams. It covers the transition from K stream to K table aggregation, emphasizing the need for updates when employee data changes. The tutorial details the grouping and aggregation process in K tables, highlighting the differences from K streams. It introduces the adder and subtractor aggregators, explaining their roles in managing updates. The video concludes with executing the solution and observing the results, suggesting the use of a state store query server for better insights.

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