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Apache Flink Course Overview

Apache Flink Course Overview

The Apache Flink course offers comprehensive training for learners aiming to master stream processing and Real-time Data Analytics. It is designed to help participants gain a solid foundation in Apache Flink, equipping them with the skills needed to build scalable stream processing applications.

Module 1: Introduction to Stream Processing and Apache Flink introduces the basics of stream processing, its importance, and how Apache Flink fits into this landscape.

Module 2: Runtime Architecture delves into the internal workings of Flink, including its Distributed Architecture and Task Execution.

Module 3: Foundations of the DataStream API focuses on the core API for stream processing in Flink, teaching learners how to define and execute data flows.

Module 4: Data Pipelines and Stateful Stream Processing covers how to build data pipelines and manage state in a distributed environment.

Module 5: Event Time and Watermarks introduces Event Time Processing and the use of watermarks for handling out-of-order events.

Module 6: Process Functions, Side Outputs, and Timers explores advanced functions, side outputs for splitting streams, and using timers.

Module 7: Windows and Streaming Analytics provides knowledge on windowing functions for temporal data analysis.

Module 8: State Backends explains the configuration and use of different state backends for state management.

Module 9: Fault Tolerance covers Flink’s Fault Tolerance Mechanisms and Checkpointing.

Module 10: Connector Ecosystem reviews the connectors available for integration with various data sources and sinks.

Module 11: Application Evolution: Rescaling, Upgrades, State Migration discusses strategies for maintaining and evolving Flink applications over time.

Module 12: Intro to Flink SQL and the Table API introduces SQL and Table API for unified stream and batch processing.

Module 13: Use Cases and Application Patterns provides insights into practical applications and patterns for Flink.

Module 14: Testing offers guidance on testing Flink applications to ensure reliability and correctness.

By the end of the course, participants can aim for an Apache Flink certification, proving their expertise in the field. This Apache Flink course is beneficial for data engineers, data scientists, and developers interested in real-time data processing and analytics.
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Free Pre-requisite Training

Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.

Assessments (Qubits)

Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.

Post Training Reports

Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.

Class Recordings

Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.

Free Lab Extensions

Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.

Free Revision Classes

Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

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Target Audience for Apache Flink

The Apache Flink course by Koenig Solutions is designed for professionals dealing with high-volume data processing and real-time analytics.


  • Data Engineers
  • Data Architects
  • Software Engineers working with Big Data
  • System Administrators managing data streams
  • IT Professionals seeking to learn stream processing
  • Technical Leads overseeing data processing teams
  • Data Scientists interested in real-time data analysis
  • DevOps Engineers involved in deploying and managing data-intensive applications
  • Software Developers building scalable data-driven applications
  • Business Intelligence Professionals looking to expand their skillset into real-time analytics
  • Technical Project Managers responsible for data processing projects
  • Database Administrators looking to integrate Flink into their data systems


Learning Objectives - What you will Learn in this Apache Flink?

  1. The Apache Flink course offers a comprehensive understanding of stream processing, Flink's architecture, and hands-on skills for building scalable streaming applications.

  2. Learning Objectives and Outcomes:

  • Gain a strong foundation in the principles of stream processing and how Apache Flink facilitates real-time data processing.
  • Understand the runtime architecture of Apache Flink, including task distribution and checkpointing mechanisms.
  • Master the DataStream API to implement robust data processing pipelines and manage stateful stream processing efficiently.
  • Develop proficiency in handling event time processing, generating watermarks, and understanding their significance in event-driven applications.
  • Utilize process functions, side outputs, and timers to create complex event processing patterns.
  • Learn to implement windows and apply streaming analytics for timely insights from data streams.
  • Explore different state backends in Flink and their roles in state management and application performance.
  • Comprehend the fault tolerance mechanisms in Flink, such as checkpoints and savepoints, for ensuring consistent state in the event of failures.
  • Delve into the connector ecosystem, understanding how to integrate Flink with various external systems for data input and output.
  • Acquire the skills to manage application evolution, including rescaling, upgrades, and state migration within streaming jobs.
  • Get introduced to Flink SQL and the Table API for convenient and expressive stream and batch processing queries.
  • Understand common use cases and application patterns, preparing for real-world Flink deployment scenarios.
  • Learn testing strategies for Flink applications to ensure correctness and performance of streaming pipelines.

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