Udemy – Stream processing frameworks for big data: the internals 2022-6
Udemy – Stream processing frameworks for big data: the internals 2022-6 Downloadly IRSpace

Stream processing frameworks for big data: the internals. This course provides a comprehensive review and comparison of stream processing frameworks for big data to help you choose the right tool for your projects. If you need stream processing for your next project or are planning to become a data engineer, this course will help you make an informed choice or start the learning process by providing detailed explanations and comparisons of four leading frameworks—Flink, Kafka Streams, Spark Streaming, and Structured Streaming. You will learn about the features, differences, APIs, and programming languages of these frameworks. Topics such as latency performance, throughput, scalability, elasticity, fault tolerance, state management, and deployment are explored in detail. The course focuses on the theoretical aspects and internals of the frameworks and provides an overview of the research findings of the instructor, Giselle, including benchmarking and analyzing these tools against the mentioned criteria.
What you will learn
- Features and built-in functionality of Flink, Spark Streaming, Structured Streaming, and Kafka Streams.
- How to choose the right stream processing framework for a specific use case.
- The current state of distributed stream processing.
- Resources for equivalent implementations across all frameworks.
- This is not a programming course; it is a course to understand how these systems work.
This course is suitable for people who:
- Anyone who needs information to choose the right framework for a use case.
- Anyone who wants to gain a solid and in-depth knowledge of the differences and features of these frameworks.
- Anyone who wants to have a deep understanding of stream processing in general.
Course details Stream processing frameworks for big data: the internals
- Publisher: Udemy
- Instructor: Giselle van Dongen
- Training level: Beginner to advanced
- Training duration: 3 hours and 9 minutes
- Number of lessons: 42
Course syllabus in 2022/8
Prerequisites for the Stream processing frameworks for big data: the internals course
- Preferably a notion of distributed systems (eg Spark batch API) but not required.
Course images
Sample course video
Installation Guide
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Subtitles: None
Quality: 720p
Download link
File(s) password: www.downloadly.ir
File size
307 MB