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Wade Waldron

Wade Waldron

Staff Software Practice Lead

Anatomy of a Stream

Overview

A Flink datastream consists of multiple moving parts, including Sources, Sinks, and Operators. How these pieces fit together can be compared to a plumbing system where the water flowing through the plumbing is similar to the data flowing through the stream. This analogy can be especially useful when trying to understand the role of backpressure in the stream. This video will walk through the various components in a datastream using the plumbing analogy to help explain each stage.

Topics:

  • Sources
  • Sinks
  • Operators
  • Backpressure

Resources

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Total 21

  1. Apache Flink with Java - An Introduction
    2 min
  2. Datastream Programming
    4 min
  3. How to Start Flink and Get Setup (Exercise)
  4. The Flink Job Lifecycle
    6 min
  5. Running a Flink Job (Exercise)
  6. Anatomy of a Stream
    4 min
  7. Flink Data Sources
    5 min
  8. Creating a Flink Data Source (Exercise)
  9. Serializers & Deserializers
    5 min
  10. Deserializing Messages in Flink (Exercise)
  11. Transforming Data in Flink
    6 min
  12. Flink Data Transformations (Exercise)
  13. Flink Data Sinks
    4 min
  14. Creating a Flink Data Sink (Exercise)
  15. Creating Branching Data Streams in Flink
    7 min
  16. Merging Flink Data Streams (Exercise)
  17. Windowing and Watermarks in Flink
    7 min
  18. Aggregating Flink Data using Windowing (Exercise)
  19. Working with Keyed State in Flink
    5 min
  20. Managing State in Flink (Exercise)
  21. Closing Remarks
    2 min

Related Resources

Docs

Intro to the DataStream API

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