Udemy - Apache Kafka Series - Kafka Streams for Data Processing
Apache Kafka Series

Udemy – Apache Kafka Series – Kafka Streams for Data Processing


Apache Kafka Series – Kafka Streams for Data Processing is the name of a new course in the Apache Kafka series of training courses in which the Kafka streams data processing library is taught. Kafka streams is the easiest way to write your program on Kafka platform:

  • The easiest way to move data using high-level DSL
  • Good support Exactly Once semantics
  • Expand and increase the capacity of Kafka Streams without even a cluster
  • Perform aggregation, integration, and any operation you can think of using just a few lines of code
  • Build applications on the Kafka platform for fault tolerance, capacity and flexibility

The instructor of this course is Stephane Maarek, one of the Kafka specialists and the author of high-level Kafka education courses in Udemy, which has had more than 40,000 students with more than 12,000 feedbacks. He shares all his Kafka knowledge and tries to explain all the concepts and provide practical and theoretical dimensions to the students.
This course is based on java 8 and includes an example in Scala. Since Kafka streams is based on Java, it is not suitable for any other language.

Each section is either theoretical or practical:

  • In practice, you will be challenged by writing your own Kafka streams program. The solution is fully explained and you will learn tips for the best use of Kafka streams.
  • In the theory section you will learn about all the available APIs, their libraries and some interesting concepts like Exactly Once Semantics.

This is the first and only Kafka streams training course available on the Internet, take this course and become a Kafka expert.

Overview of the Apache Kafka Series – Kafka Streams for Data Processing:

  • Kafka streams – First look: Start Kafka and run your first Kafka streams program (wordcount)
  • End-to-End Kafka streams program: Write the wordcount program code, bring its dependencies, build and package your program and learn how to increase its capacity. This is a complete end to end example.
  • Simple KStream and KTable operators: All stateless operators available for KStream API and KTable
  • Practical Practice – Favorite Color: Practice your newly learned skills by writing your own Kafka stream program (Favorite Color) that will challenge you. This includes a scala version.
  • Advanced KStream and KTable Operators: All stateful operators available for KStream API and KTable
  • Theory – Exactly Once Semantics: Learn what Exactly Once Semantics (EOS) is and how Kafka 0.11 provides it and how to enable them on Kafka streams.
  • Exactly Once – Practice Exercise – Bank Balance: Apply the new knowledge you have learned by writing your own Kafka streams program, Exactly Once, to calculate bank balances for your customers.
  • Testing Kafka streams: Learn how to test WordCount with Kafka Streams v1.1.0.

Learn Kafka, the most popular data processing library, right now. Kafka is getting ahead to become an essential skill and this course will help you to succeed quickly using the Kafka Streams API. The job market needs more people with the new skills you have acquired.

Course features:

  • Write your own Kafka Streams application using java 8.
  • Increase the capacity of the Kafka Streams program
  • Build and package the program
  • Set Kafka Streams to use Exactly Once Semantics
  • Scheduling with Kafka Streams High Level DSL
  • Write tests for Kafka Streams Topology

Specifications of the Apache Kafka Series – Kafka Streams for Data Processing 2020/12:

Language: English
Duration: 4h 50m
Number of Courses: 76
Level: Medium
Instructor: Stephane Maarek
File Format: mp4

Course topics on 2020/12:

Kafka Streams for Data Processing

Course prerequisites:

Good knowledge of Apache Kafka

A recent computer (Windows / Linux / Mac OS X) with 4GB of RAM

Good knowledge of Java 8 Programming Language

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Download Part 1 – 2 GB
Download Part 2 – 2 GB
Download Section 3 – 2 GB
Download section 4 – 57 MB
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