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PYSPARK โ€ข LESSON 82

Multi-Column Group Counts

How do we group orders across multiple dimensions (country and status) to analyze fulfillment?

Intermediateโฑ 2 Minutesโญ 390 XP
๐Ÿค” THE QUESTION

How do we group orders across multiple dimensions (country and status) to analyze fulfillment?

๐Ÿ’ก WHAT IS IT?

Passing multiple column names into groupBy() to partition data into multi-dimensional buckets.

๐ŸŽฏ WHAT IS IT USED FOR?

Cross-dimensional fulfillment tracking, international order monitoring, and cohort breakdown.

๐Ÿ’ป EXAMPLE
df.groupBy("country", "status").count().show()

๐ŸŽฏ Mission Objectives

Practice typing production-grade PySpark code for Multi-Column Group Counts.

  • โœ“ Group across multiple dimensions
  • โœ“ Compute multi-dimensional counts
  • โœ“ Inspect fulfillment matrix