Multiple Expression Pipeline

How can we apply multiple calculated column expressions in a single projection pass using selectExpr()?

Advanced⏱ 3 Minutes⭐ 820 XP

🤔 THE QUESTION

How can we apply multiple calculated column expressions in a single projection pass using selectExpr()?

💡 WHAT IS IT?

selectExpr() accepts SQL expression strings to calculate mathematical operations, string conversions, and casts in a single Catalyst query plan node.

🎯 WHAT IS IT USED FOR?

High-throughput batch transformations where chaining multiple withColumn calls would build deep lineage trees.

💻 EXAMPLE

df_transformed = df.selectExpr("user_id", "upper(user_name) AS user_name", "price * quantity AS total_amount", "cast(created_at AS date) AS event_date")

🎯 Mission Objectives

Practice typing production-grade PySpark code for Multiple Expression Pipeline.

✓ selectExpr() batch execution
✓ SQL string expressions
✓ Catalyst query plan optimization

🚀 Start Mission

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