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PYSPARK โ€ข LESSON 95

Multi-Table Relational Joins

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

Intermediateโฑ 3 Minutesโญ 480 XP
๐Ÿค” THE QUESTION

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

๐Ÿ’ก WHAT IS IT?

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

๐ŸŽฏ WHAT IS IT USED FOR?

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

๐Ÿ’ป EXAMPLE
analytics_df = orders \
    .join(customers, "customer_id", "inner") \
    .join(products, "product_id", "inner")

๐ŸŽฏ Mission Objectives

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

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