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 Flinks 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 Flinks 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 Flinks key concepts including checkpoint mechanism, map state, list state and value state Learn Flinks 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.

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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 Flinks 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 Flinks 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 Flinks key concepts including checkpoint mechanism, map state, list state and value state

Learn Flinks 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

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5 stars: 13 votes

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