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PYSPARK • LESSON 95

Multi-Table Relational Joins

How do we chain multiple joins together to combine orders with customers and products in a single pipeline?

Intermediate3 Minutes480 XP
🤔 THE QUESTION

How do we chain multiple joins together to combine orders with customers and products in a single pipeline?

💡 WHAT IS IT?

Chaining sequential join() calls to link transactional facts with multiple dimension tables.

🎯 WHAT IS IT USED FOR?

Star-schema dimension lookups, sales analytics marts, and generating unified reporting datasets.

💻 EXAMPLE
analytics_df = orders \
    .join(customers, "customer_id", "inner") \
    .join(products, "product_id", "inner")

🎯 Mission Objectives

Practice typing production-grade PySpark code for Multi-Table Relational Joins.

  • Chain sequential joins across 3 tables
  • Connect orders with customers and products
  • Produce denormalized analytics dataset