Introduction - Joins & Window Functions
"Master Apache Spark and Big Data Engineering from first principles."
What You'll Master
Relational Join Types
Differentiating and executing Inner, Outer, and advanced Left Semi/Left Anti joins using Spark DSL.
Physical Join Strategies
The physical execution mechanics of Sort-Merge Joins, Shuffle Hash Joins, and high-performance Broadcast Hash Joins.
Window Analytics
Creating partition-level window specifications, and calculating running totals, row rankings, and lead/lag values.
Hands-on Windowing Workbook
Applying join strategy selection and window function analytics to real query-tuning scenarios.
Learning Path & Course Syllabus
The physical execution mechanics of Sort-Merge Joins, Shuffle Hash Joins, and high-performance Broadcast Hash Joins.
Differentiating and executing relational join types (Inner, Outer, and advanced Left Semi/Left Anti joins) using Spark DSL.
Creating partition-level analytical window specifications, calculating running totals, row rankings, and lead/lag values.
A hands-on workbook applying join strategies and window function analytics to real query-tuning scenarios.
Scenario questions covering join type selection, physical join strategy tradeoffs, and window function internals.
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 |