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PYSPARK • LESSON 213

Range & Threshold Boundary Validation

How can we validate that sensor readings and monetary values fall within realistic physical boundaries?

Advanced3 Minutes820 XP
🤔 THE QUESTION

How can we validate that sensor readings and monetary values fall within realistic physical boundaries?

💡 WHAT IS IT?

The between() condition verifies that numeric values satisfy strict lower and upper business bounds.

🎯 WHAT IS IT USED FOR?

Filtering corrupted IoT temperature readings, invalid discount percentages, or negative ages.

💻 EXAMPLE
df_clean_range = df.filter(col("temperature").between(-50, 150) & col("discount_pct").between(0.0, 1.0))

🎯 Mission Objectives

Practice typing production-grade PySpark code for Range & Threshold Boundary Validation.

  • between() validation
  • Boundary enforcement
  • Outlier rejection