Terminologies in Apache Spark | Data Engineering, Spark & Databricks Course

Описание: Welcome to the chapter of our comprehensive course on Data Engineering, Spark, and Databricks! In this video, Terminologies in Apache Spark

📌 What You’ll Learn:
Timestamps:
00:00 Introduction
00:10 Cluster
00:38 Spark Driver
01:04 Worker node
01:27 Executors
01:54 Cores
02:16 Slots
02:40 On-heap memory
03:08 off-heap memory
03:40 Partations
04:16 Spark Application
04:43 Spark Jobs
05:14 Stages
05:40 Tasks
06:00 DAG (Directed Acyclic Graph)
06:41 Transformation
07:29 Action
08:09 Thanks

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🌟 Why This Course?
Big Data is at the core of digital transformation, and understanding its fundamentals is crucial for anyone looking to build a career in data engineering. In this course, we'll break down complex concepts into easy-to-understand lessons, accompanied by practical examples and hands-on exercises.

🔧 Tools and Technologies:
Throughout this course, we'll dive deep into tools like Apache Spark and Databricks, which are essential for processing and analyzing Big Data. You'll learn how to set up your environment, write efficient Spark jobs, and leverage Databricks for seamless data engineering workflows.

🎯 Who Should Watch This?
1. Aspiring Data Engineers
2. Software Developers and Engineers
3. Data Analysts interested in Big Data
4. IT Professionals transitioning to Big Data roles
5. Students and enthusiasts eager to learn about Big Data

📅 What’s Next?
Stay tuned for the upcoming chapters History of Big Data

🔗 Useful Links:
Skillsharp https://www.youtube.com/ @SkillSharp

🤝 Get Involved:
★ Like this video if you found it helpful!
★ Comment below with your questions or topics you’d like to see covered in future chapters.
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