Join Semantics in Kafka Streams
With the recent adoption of the Confluent and Kafka Streams, organizations have experienced significantly improved system stability with real-time processing framework, as well as improved scalability and lower maintenance costs.
However, many organizations need to install separate processing clusters or similar special-purpose and expensive infrastructure to process the messages in the Kafka topics for various applications such as monitoring, log analytics etc. The most population solutions for this is Kafka Streams, it makes building stream processing services much simpler since it is cluster and framework free — it is just a library.
The focus of this session is:
Different join operators in Kafka Streams.
Exploring different options in Kafka Streams to join semantics, both with and without shared keys.
How to put Application Owner in control by leveraging simplified app-centric architecture.
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