Apache Flink with Scala 3
Apache Flink with Scala 3, available at $54.99, has an average rating of 5, with 39 lectures, based on 13 reviews, and has 88 subscribers.
You will learn about Learn Flink's basic and advanced concepts and architecture each followed by hands-on exercises in Scala 3 Learn how Flink handles stream processing, distributed and stateful computation Learn to handle event time processing using Flink's watermarks mechanism and window operation Learn to integrate Flink version 1.17 with Kafka and Kubernetes using Scala 3 Learn to write stateful applications using Flink's key concepts including checkpoint mechanism, map state, list state and value state Learn Flink's deployment modes and deploy your own Flink application on Kubernetes This course is ideal for individuals who are Developers who want write production ready Flink applications or want to learn about distributed real-time data streaming systems, or trying to troubleshoot Flink deployment on Kubernetes It is particularly useful for Developers who want write production ready Flink applications or want to learn about distributed real-time data streaming systems, or trying to troubleshoot Flink deployment on Kubernetes.
Enroll now: Apache Flink with Scala 3
Summary
Title: Apache Flink with Scala 3
Price: $54.99
Average Rating: 5
Number of Lectures: 39
Number of Published Lectures: 39
Number of Curriculum Items: 39
Number of Published Curriculum Objects: 39
Original Price: $84.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn Flink's basic and advanced concepts and architecture each followed by hands-on exercises in Scala 3
- Learn how Flink handles stream processing, distributed and stateful computation
- Learn to handle event time processing using Flink's watermarks mechanism and window operation
- Learn to integrate Flink version 1.17 with Kafka and Kubernetes using Scala 3
- Learn to write stateful applications using Flink's key concepts including checkpoint mechanism, map state, list state and value state
- Learn Flink's deployment modes and deploy your own Flink application on Kubernetes
Who Should Attend
- Developers who want write production ready Flink applications or want to learn about distributed real-time data streaming systems, or trying to troubleshoot Flink deployment on Kubernetes
Target Audiences
- Developers who want write production ready Flink applications or want to learn about distributed real-time data streaming systems, or trying to troubleshoot Flink deployment on Kubernetes
As the latest Flink course in Scala 3 released in 2024, it covers Flink’s basic and advanced concepts each followed by hands-on exercises. This course cuts through all the complexities of integrating the very recent Flink version 1.17 with Scala 3 and Kubernetes. Starting with version 1.15 of Flink, Scala support was removed to make it easier to integrate with multiple versions of Scala, including Scala 3. This course includes step by step video demonstrations on how to resolve the problem of classpath collision when deploying Flink applications in Scala 3 on Kubernetes.
Concretely, here’s what you will learn to either ace your next Flink interview or be ready to write your production level Flink application:
1. Flink and Streaming Fundamentals
You’ll understand how Flink handles stream processing, distributed and stateful computation; You’ll learn Flink’s architecture including Flink cluster’s components; You’ll know how to deploy and manage the lifecycle of a Flink application.
2. Flink Data Pipeline
You’ll understand different levels of abstraction for developing streaming applications; You’ll be able to process big data in real time any way you want to by mastering fundamental Flink concepts including: data ingestion, efficient data transformation, controlling your applications with lower level APIs, producing output streams to data sinks.
3. Integration with Apache Kafka
You’ll learn configuration of Kafka Source and Kafka Sink; You’ll master how to set up Kafka dependencies in built.sbt and how to integrate Kafka with Flink as a data source or data sink.
4. Time Handling, Watermarks and Windows
You’ll be able to handle event time processing using Flink’s watermarks mechanism and window operation including tumbling window, sliding window and global window.
5. Fault Tolerant
You’ll be able to write stateful applications using Flink’s key concepts including checkpoint mechanism, map state, list state and value state.
6. Integration with Kubernetes
You’ll learn Flink’s deployment modes and deploy your own Flink application on Kubernetes by following along the video demonstration of every deployment step and deployment configurations.
What you’ll get from this course:
You will get 30+ total Flink video lessons with slides and illustrative diagrams plus access to Github Repo with all the code in the course;
You can practice by writing more than 20 Flink applications for common use cases and following along the hands-on video lessons;
You will quickly master the configurations of all the dependencies and steps to deploy Flink 1.17 applications on Kubernetes by following the video demonstration;
You will learn transferrable principles of big data streaming and distributed systems that you can apply on other streaming systems.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Prerequisites
Lecture 2: Introduction
Lecture 3: Why Flink
Lecture 4: Flink Cluster and Life Cycle
Chapter 2: Anatomy of a Flink Pipeline
Lecture 1: Flink Pipeline
Lecture 2: Data Source
Lecture 3: Hands-on: Data Source Part One
Lecture 4: Hands-on: Data Source Part Two
Lecture 5: Hands-on: Data Source Part Three
Lecture 6: Kafka Source
Lecture 7: Data Transformation
Lecture 8: Hands-on: Data Transformation
Lecture 9: Low Level APIs
Lecture 10: Hands-on: Low Level APIs Part One
Lecture 11: Hands-on: Low Level APIs Part Two
Lecture 12: Data Transformation II: Handling Multiple Streams
Lecture 13: Hands-on: Handling Multiple Streams
Lecture 14: Side Output
Lecture 15: Hands-on: Side Output
Lecture 16: Output
Lecture 17: Hands-on: Integration with Kafka
Chapter 3: Advanced Flink Concepts
Lecture 1: Introduction to Timely Streaming
Lecture 2: Windows I: Window Assigners
Lecture 3: Hands-on: Handling events with Processing Time
Lecture 4: Hands-on: Handling events with Event Time
Lecture 5: Windows II: Window Lifecycle
Lecture 6: Windows III: Window Functions
Lecture 7: Hands-on: Tumbling Window
Lecture 8: Hands-on: Sliding Window
Lecture 9: Hands-on: Global Window
Lecture 10: Handling Time with Multiple Streams
Lecture 11: Hands-on: Window Join
Lecture 12: Stateful Streaming
Lecture 13: State Types
Lecture 14: Hands-on: Value State
Lecture 15: Hands-on: List State
Lecture 16: Checkpoints
Lecture 17: Hands-on: Checkpoint
Chapter 4: Flink Application Deployment
Lecture 1: Deployment on Kubernetes
Instructors
-
Maggie Cao
Data Engineer & Instructor
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 0 votes
- 5 stars: 13 votes
Frequently Asked Questions
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