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RAN-DBDEA-00041
Ranvier · DBDEA

Exam DBDEA Topics: transformation Difficulty: medium

A marketing engineer needs every combination of customer segment (40 rows) and promo code (5,000 rows) for a campaign evaluation job, and writes: ```python result = segments.crossJoin(promos) ``` The job will score every resulting pair once per night. What does this produce, and what should the engineer keep in mind?

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  1. A. A 200,000-row Cartesian product (40 x 5,000) — fine here, but cross joins grow as rows-times-rows
  2. B. 5,040 rows — crossJoin stacks both DataFrames the same way a union does
  3. C. An error, because cross joins require setting spark.sql.crossJoin.enabled to true first
  4. D. Only the rows where a segment value also appears in the promos DataFrame — crossJoin applies an implicit equality filter
Reveal answer

Correct answer: A 200,000-row Cartesian product (40 x 5,000) — fine here, but cross joins grow as rows-times-rows

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

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Official Answer (A): A 200,000-row Cartesian product (40 x 5,000) — fine here, but cross joins grow as rows-times-rows

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