Disambiguating Column Names with Aliases

How do we disambiguate identical column names (like created_at and id) between joined DataFrames?

Advanced⏱ 2 Minutes⭐ 550 XP

🤔 THE QUESTION

How do we disambiguate identical column names (like created_at and id) between joined DataFrames?

💡 WHAT IS IT?

Applying alias('l') and alias('r') to DataFrames before joining and referencing fields via col('l.field').

🎯 WHAT IS IT USED FOR?

Preventing AnalysisException column ambiguity errors during complex multi-table warehouse queries.

💻 EXAMPLE

from pyspark.sql.functions import col

df = df_left.alias("l").join(
    df_right.alias("r"),
    col("l.id") == col("r.id"),
    "inner"
).select(col("l.id"), col("l.created_at"), col("r.status"))

🎯 Mission Objectives

Practice typing production-grade PySpark code for Disambiguating Column Names with Aliases.

✓ Alias left and right DataFrames
✓ Disambiguate column references with prefixes
✓ Select clean unambiguous schema

🚀 Start Mission

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