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RAN-DBDEA-00227
Ranvier · DBDEA

Exam DBDEA Topics: transformation Difficulty: hard

An analyst joins customers to loyalty_accounts on customer_id and is surprised to see that customers whose customer_id is NULL disappear from the output. The join call passes no join type: ```python customers.join(loyalty_accounts, "customer_id") ``` A teammate argues that switching to a left join will not help, because a NULL key never matches anything anyway. Which statement is correct?

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  1. A. NULL is treated as equal to NULL in the join, so those customers did match loyalty rows that also carry a NULL key
  2. B. A join whose key column contains NULL fails outright with an error, and those rows were rejected while all the other rows joined normally
  3. C. NULL never satisfies an equality comparison, so the default inner join drops those rows — a left join would keep them, padded with NULLs
  4. D. Spark converts NULL keys to empty strings before joining, so the customers survive in the output under a different value
Reveal answer

Correct answer: NULL never satisfies an equality comparison, so the default inner join drops those rows — a left join would keep them, padded with NULLs

Reference: https://docs.databricks.com/aws/en/pyspark/reference

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Official Answer (C): NULL never satisfies an equality comparison, so the default inner join drops those rows — a left join would keep them, padded with NULLs

⚓ Official Documentation Anchor: https://docs.databricks.com/aws/en/pyspark/reference
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