From the course: Apache Flink: Real-Time Data Engineering
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Related prerequisite courses - Flink Tutorial
From the course: Apache Flink: Real-Time Data Engineering
Related prerequisite courses
- [Instructor] This course only focuses on the stream processing aspects of Apache Flink. The topics covered in this course include using KeyBy for partitioning streams, windowing for aggregations, splitting and merging streams, event time processing, stateful processing, and streaming sources and sinks. The prerequisites for this course are covered in my other course about batch mode data engineering in Apache Flink. I highly recommend that students are familiar with the following prerequisites in order to learn from this course effectively. Students must be familiar with how to set up a standalone Flink instance as well as a base Flink project in an IDE. Familiarity with Flink architecture will help understand how data gets processed in Flink. We use a number of basic operations, like map and reduce, in this course, but do not cover those functionality in detail. It would be an added benefit to know about batch…
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