The correct answer is SELECT address.city FROM table, which uses dot notation to directly access a STRUCT field, and JSON_EXTRACT(TO_JSON(address), '$.city'), which converts the STRUCT to a JSON string and then extracts the city field via JSONPath. Dot notation is the standard SQL syntax for navigating nested fields in BigQuery, allowing you to reference a STRUCT column followed by a period and the subfield name without any function calls. On the Google Professional Cloud Database Engineer exam, this tests your understanding of how BigQuery handles nested and repeated data, a common scenario when modeling complex schemas like customer addresses. A frequent trap is forgetting that JSON_EXTRACT requires the TO_JSON conversion first, or assuming dot notation only works with REPEATED fields. For a quick memory tip: think of dot notation as "drilling down" directly into the struct, while JSON_EXTRACT is like taking a photo of the struct and then reading the label on the photo.
PCDE Practice Question: Define data structures and implement SQL for Business Intelligence
This PCDE practice question tests your understanding of define data structures and implement sql for business intelligence. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A BigQuery dataset contains a table with a STRUCT column for customer address. The BI team needs to query the city field from the struct. Which two approaches are valid? (Select TWO).
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
SELECT JSON_EXTRACT(TO_JSON(address), '$.city') FROM table
Option B is correct because `JSON_EXTRACT(TO_JSON(address), '$.city')` converts the STRUCT to a JSON string and then extracts the `city` field using JSONPath syntax. Option C is correct because BigQuery allows direct field access on a STRUCT column using dot notation (`address.city`), which is the standard SQL syntax for nested fields.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
SELECT UNNEST(address) as city FROM table
Why it's wrong here
UNNEST is used to flatten arrays, not to access struct fields.
✓
SELECT JSON_EXTRACT(TO_JSON(address), '$.city') FROM table
Why this is correct
Converting the struct to JSON and extracting the city field is a valid but more verbose method.
Related concept
Read the scenario before looking for a memorised answer.
✓
SELECT address.city FROM table
Why this is correct
Dot notation is the standard way to access struct fields in BigQuery.
Related concept
Read the scenario before looking for a memorised answer.
✗
SELECT address['city'] FROM table
Why it's wrong here
Bracket notation is used for accessing array elements by index or for REPEATED fields, not for structs.
✗
SELECT address.city.standard FROM table
Why it's wrong here
This would require a nested field 'standard' inside city, which is not indicated.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between STRUCT and ARRAY types, and the trap here is that candidates confuse `UNNEST` (for ARRAYs) with dot notation (for STRUCTs), or mistakenly apply bracket syntax from other SQL dialects like PostgreSQL or MySQL.
Detailed technical explanation
How to think about this question
In BigQuery, STRUCTs are represented as RECORD types with named subfields, and dot notation is the native way to access them. The `JSON_EXTRACT` approach is useful when the STRUCT is deeply nested or when you need to pass the data to a JSON-processing function. Under the hood, BigQuery stores STRUCTs as repeated fields with a schema, and accessing subfields does not incur a full JSON serialization, making dot notation more performant than JSON extraction.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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 JSON_EXTRACT(TO_JSON(address), '$.city') FROM table — Option B is correct because `JSON_EXTRACT(TO_JSON(address), '$.city')` converts the STRUCT to a JSON string and then extracts the `city` field using JSONPath syntax. Option C is correct because BigQuery allows direct field access on a STRUCT column using dot notation (`address.city`), which is the standard SQL syntax for nested fields.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This PCDE 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 PCDE exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.