Stream processing concepts
On This Lesson 4 topics
This lesson is planned. The outline below lists the topics it will cover. The full lesson has not been published yet.
In this lesson
describe enrichment and aggregation on streams.
Planned topics
- Stream processors apply stateful operations: joins, windows, aggregations.
- Event time versus processing time; late events need a policy.
- State stores are rebuilt from changelog topics, so recovery has a cost.
- Choose Kafka Streams for library-style, Flink for larger stateful jobs; verify before recording.
Draft outline details
Demonstration
a topology: stock changes joined with a product table, aggregated per warehouse in 1-minute windows, written to a topic.
Check your understanding
What is a late event?
Show answer
One arriving after its time window was processed.
Practice
Apply this lesson with the module's lab, exercises and quiz.
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