Quick Answer
The answer is a one-to-many relationship between the tables being joined. When you join a table on the “one” side of a relationship to a table on the “many” side, each matching row from the “many” side creates a separate row in the result set, effectively duplicating the data from the “one” side. This happens because SQL JOINs produce a Cartesian product of all matching row pairs, so if one customer has five orders, the customer’s row repeats five times. On the Google Professional Cloud Database Engineer exam, this concept tests your understanding of relational database design and query behavior; a common trap is assuming duplicate rows always indicate bad data or a faulty JOIN condition, when in fact the root cause is often a missing DISTINCT or an unintended one-to-many expansion. To remember this, think: “One row on the left, many on the right—duplicates are by design, not by mistake.” Always check your table relationships before adding DISTINCT or GROUP BY.
This PCDE practice question tests your understanding of define data structures and implement sql for business intelligence. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A SQL query with multiple JOINs is returning duplicate rows. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Using INNER JOIN instead of LEFT JOIN.
Why wrong: Both can produce duplicates with one-to-many relationships.
There is a one-to-many relationship between tables.
One-to-many joins multiply rows from the one side.
Missing ORDER BY clause.
Why wrong: ORDER BY only sorts rows.
Using UNION instead of UNION ALL.
Why wrong: UNION removes duplicates, UNION ALL keeps them.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
There is a one-to-many relationship between tables.
When a SQL query with multiple JOINs returns duplicate rows, the most likely cause is a one-to-many relationship between the tables being joined. Each matching row in the 'many' side of the join multiplies the rows from the 'one' side, producing duplicates. This is a fundamental behavior of JOIN operations in SQL, where the result set is the Cartesian product of matching rows across the joined tables.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Using INNER JOIN instead of LEFT JOIN.
Why it's wrong here
Both can produce duplicates with one-to-many relationships.
There is a one-to-many relationship between tables.
Why this is correct
One-to-many joins multiply rows from the one side.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Missing ORDER BY clause.
Why it's wrong here
ORDER BY only sorts rows.
Using UNION instead of UNION ALL.
Why it's wrong here
UNION removes duplicates, UNION ALL keeps them.
Common exam traps
Google Cloud often tests the misconception that duplicate rows are caused by the type of JOIN (e.g., INNER vs LEFT) or by missing sorting, rather than understanding that duplicates arise from the cardinality of the relationship between the joined tables.
Detailed technical explanation
Under the hood, a JOIN performs a row-wise multiplication: for each row in the left table, every matching row in the right table is appended, creating a new row in the result set. In a one-to-many relationship, the 'many' side can have multiple rows with the same foreign key, causing each left row to appear multiple times. A real-world scenario is joining an Orders table (one) to an OrderItems table (many): each order with multiple items will produce duplicate order rows unless aggregated or deduplicated.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Define data structures and implement SQL for Business Intelligence — This question tests Define data structures and implement SQL for Business Intelligence — Read the scenario before looking for a memorised answer..
The correct answer is: There is a one-to-many relationship between tables. — When a SQL query with multiple JOINs returns duplicate rows, the most likely cause is a one-to-many relationship between the tables being joined. Each matching row in the 'many' side of the join multiplies the rows from the 'one' side, producing duplicates. This is a fundamental behavior of JOIN operations in SQL, where the result set is the Cartesian product of matching rows across the joined tables.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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