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Data Engineering Path  ·  PySpark

Introduction - Lakehouse Architecture & Production Best Practices

Level Intermediate to Advanced
Estimated Time ~2.5 Hours
Curriculum 6 Lessons
Course Mission

"Master Apache Spark and Big Data Engineering from first principles."


What You'll Master

Delta Lake & ACID

Implementing ACID transactions, schema enforcement, and DML operations (UPDATE, DELETE, MERGE) on top of object storage.

Delta Time Travel

How the Delta transaction log records actions, enabling version history and time-stamped rollbacks with versionAsOf.

Production Guidelines

Designing Bronze-Silver-Gold Medallion architectures, managing Spark UI monitoring, log4j errors, and cluster configs.

Capstone Hands-on Workbook

Applying Delta Lake ACID guarantees, time travel, and production best practices to a capstone scenario.


Learning Path & Course Syllabus

What is Delta Lake? Implementing ACID transactions, schema enforcement, and DML operations (UPDATE, DELETE, MERGE).

Designing Bronze-Silver-Gold Medallion architectures, managing Spark UI monitoring, log4j errors, and cluster configs.

How the Delta transaction log records actions, enabling version history and time-stamped rollbacks with versionAsOf.

A capstone workbook applying Delta Lake ACID guarantees, time travel, and production best practices.

Scenario questions covering Delta transaction guarantees, time travel semantics, and Medallion architecture design.


What's Included in This Module

Component Coverage Details
Core Topics Driver & Executor Architecture, Cluster Managers, Datasets
Practical Exercises Interactive Hands-on Labs & Spark Tasks
Assessments 1 Practical Assignment + 1 System Design Interview Quiz
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