Apache Spark for Data Engineering - Hands-On with PySpark

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Apache Spark for Data Engineering - Hands-On with PySpark (Size: 3 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction & Course Overview
  1. Welcome to the Course.mp4 34.6 MB
  2 - Apache Spark Fundamentals
  10. Spark SQL.mp4 51.5 MB
  3 - Creating Your First DataFrame
  11. Creating a Spark Session.mp4 54.2 MB
  12. Reading Data with Spark.mp4 104.3 MB
  12. transactions.csv 4.2 KB
  13. Understanding Schemas and Data Types.mp4 145 MB
  14. Selecting and Filtering Data.mp4 96.9 MB
  15. Adding and Modifying Columns.mp4 91.9 MB
  16. Aggregations and GroupBy.mp4 164.8 MB
  17. Sorting and Handling Null Values.mp4 87.5 MB
  18. Joins in Spark DataFrames.mp4 84.4 MB
  19. Writing Data with Spark.mp4 175.6 MB
  20. Spark SQL in Practice.mp4 62.7 MB
  4 - Real-World Data Engineering Project
  21. Project Description.html 9 KB
  22. Project Overview & Business Context.mp4 78.4 MB
  23. Project Requirements & Pipeline Design.mp4 16 MB
  24. Centralized Configuration & Project Structure.mp4 170 MB
  25. Reading Raw Data with Explicit Schemas.mp4 82.9 MB
  26. Data Cleaning & Quality Rules.mp4 186.7 MB
  27. Logging & Data Quality Monitoring.mp4 107.7 MB
  28. Data Enrichment.mp4 123.1 MB
  29. Currency Conversion & Business Rules.mp4 130.8 MB
  30. Computing Business Metrics.mp4 100.2 MB
  31. Final Analytics & Production Readiness.mp4 77.4 MB
  32. Project Recap & Next Steps.mp4 33.5 MB
  5 - Spark Execution Model [Advanced]
  33. [OPTIONNAL] Local Setup.html 8.2 KB
  34. Lazy Evaluation Transformations vs Actions.mp4 141.1 MB
  35. From Code to Execution What Is a Spark Job.mp4 54.7 MB
  36. Tasks How Work Is Parallelized.mp4 72.4 MB
  37. Stages Explained Why Shuffles Change Everything.mp4 109.2 MB
  38. Narrow vs Wide Transformations in Apache Spark.mp4 64.4 MB
  6 - Wrap-Up & Career Path
  39. What You Can Confidently Do After This Course.mp4 44.1 MB
  6. What Is Apache Spark.mp4 44 MB
  7. Spark Architecture Explained.mp4 44 MB
  8. SparkSession & SparkContext.mp4 42.4 MB
  9. Spark APIs DataFrames.mp4 65.3 MB
  2. Spark vs Other Tools (Pandas, SQL, etc.).mp4 33.8 MB
  3. Working environment and Databricks.mp4 31.6 MB
  4. How to Ask Questions and Get Help.html 6.9 KB
  5. Summary & Next Steps.mp4 29.3 MB

Description


Apache Spark for Data Engineering — Hands-On with PySpark

https://WebToolTip.com

Published 2/2026
Created by Big Data Expertise
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 39 Lectures ( 3h 54m ) | Size: 3 GB

Go from beginner to building real Spark ETL pipelines using DataFrames and Spark SQL

What you'll learn
✓ Set up and work with an Apache Spark environment using PySpark to process real-world datasets.
✓ Read data from common formats such as CSV and Parquet
✓ Clean, transform and aggregate data using the Spark DataFrame API & Spark SQL
✓ Build a complete end-to-end Spark ETL pipeline
✓ Understand how Apache Spark works under the hood

Requirements
● Basic programming knowledge : You should be comfortable with basic programming concepts such as variables, functions, and loops (Python or any similar language).
● Basic Python or Scala familiarity (recommended, not mandatory) : Knowing Python or Scala basics will help you follow the examples, but Spark concepts apply to both languages.
● Basic SQL knowledge Understanding simple SQL queries (SELECT, WHERE, GROUP BY) is helpful but not required.
● A computer with internet access A standard laptop or desktop computer is enough. No special hardware is required.

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