The answer is the query using EXISTS with UNNEST. This is the most efficient BigQuery array membership check because EXISTS leverages short-circuit evaluation, stopping the scan of each row’s array as soon as a match for product_id 'ABC' is found, avoiding unnecessary row multiplication that would occur with a CROSS JOIN UNNEST. On the Google Professional Cloud Database Engineer exam, this pattern tests your understanding of correlated subqueries and array unnesting performance—a common trap is choosing a CROSS JOIN that multiplies rows and then filters, which is less efficient for large datasets. A useful memory tip: think of EXISTS as a “needle in a haystack” search—it stops the moment the needle is found, while a JOIN would lay out every piece of hay first.
PCDE Practice Question: Define data structures and implement SQL for Business Intelligence
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 company uses BigQuery with a table 'orders' that has a column 'items' of type ARRAY<STRUCT<product_id STRING, quantity INT64>>. An analyst needs to find orders that contain a specific product, 'ABC'. Which query is most efficient?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
SELECT * FROM orders WHERE EXISTS (SELECT 1 FROM UNNEST(items) WHERE product_id = 'ABC')
Option A is correct because it uses a correlated subquery with `UNNEST` and `EXISTS`, which stops scanning as soon as a matching product_id is found within each row's array. This is the most efficient pattern for checking array membership in BigQuery, as it avoids unnecessary row multiplication and leverages short-circuit evaluation.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
SELECT * FROM orders WHERE EXISTS (SELECT 1 FROM UNNEST(items) WHERE product_id = 'ABC')
Why this is correct
EXISTS with UNNEST is the standard pattern for array membership.
Related concept
Read the scenario before looking for a memorised answer.
✗
SELECT * FROM orders WHERE ARRAY_LENGTH(items) > 0
Why it's wrong here
This only checks if the array is non-empty, not product existence.
✗
SELECT * FROM orders WHERE 'ABC' IN UNNEST(items)
Why it's wrong here
IN UNNEST does not work; IN expects a subquery or list.
✗
SELECT o.*, item FROM orders o, UNNEST(items) item WHERE item.product_id = 'ABC'
Why it's wrong here
This returns a row per item, potentially duplicating orders if multiple items match.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that `IN UNNEST` works directly with struct arrays, when in fact it requires a scalar field extraction, and that `CROSS JOIN UNNEST` is always the correct way to filter array contents, ignoring the performance penalty of row multiplication.
Detailed technical explanation
How to think about this question
Under the hood, BigQuery's `EXISTS` with `UNNEST` uses a semi-join pattern that can leverage columnar storage and predicate pushdown, scanning only the necessary struct fields. In contrast, `CROSS JOIN UNNEST` materializes all array elements into rows, which can significantly increase intermediate data volume and query cost, especially when arrays are large or the table has many rows. This distinction is critical in data warehouse environments where minimizing data shuffle and slot usage directly impacts query performance and billing.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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..
What is the correct answer to this question?
The correct answer is: SELECT * FROM orders WHERE EXISTS (SELECT 1 FROM UNNEST(items) WHERE product_id = 'ABC') — Option A is correct because it uses a correlated subquery with `UNNEST` and `EXISTS`, which stops scanning as soon as a matching product_id is found within each row's array. This is the most efficient pattern for checking array membership in BigQuery, as it avoids unnecessary row multiplication and leverages short-circuit evaluation.
What should I do if I get this PCDE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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