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Data Analysis And PresentationhardMultiple ChoiceObjective-mapped

GCP-ADP Data Analysis And Presentation Practice Question

A BigQuery table has 10 billion rows. You notice a query performing a cross-join is timing out. What should you do?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Replace the cross-join with a specific JOIN condition.

Cross-joins on massive datasets are the leading cause of query failure; they should be avoided in favor of JOIN ON or other set-based operations.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Replace the cross-join with a specific JOIN condition.

    Why this is correct

    JOIN ON is significantly more efficient than a cross-join.

  • Use a wildcard table.

    Why it's wrong here

    Wildcard tables are for querying multiple tables, not fixing cartesian join issues.

  • Cache the results in BigQuery.

    Why it's wrong here

    Caching does not help a query that fails during the computation phase.

  • Increase the number of slots.

    Why it's wrong here

    Increasing slots cannot fix an inherently inefficient cartesian product.

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Google Cloud exam blueprint

This GCP-ADP practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCP-ADP exam.