- A
Use the LIKE operator with wildcards for pattern matching.
Why wrong: LIKE with wildcards is inefficient and not a full-text search solution.
- B
Store article content in a Cloud Storage bucket and query metadata.
Why wrong: This is external to Cloud SQL and not a schema design choice.
- C
Normalize content into a separate table and use joins.
Why wrong: Normalization does not enable full-text search.
- D
Use Cloud SQL's built-in full-text search feature.
Cloud SQL for MySQL supports full-text search via FULLTEXT indexes and MATCH AGAINST queries.
- E
Add a FULLTEXT index on the content column.
A FULLTEXT index enables efficient text search queries.
Question 782 of 1,000
Full-Text Search in Cloud SQL MySQL: Schema Design Choices
This PCDE practice question tests your understanding of design and implement database schemas. 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.
Your team is designing a schema for Cloud SQL (MySQL) for a content management system. You need to implement full-text search on article content. Which TWO schema design choices are appropriate? (Choose two.)
Quick Answer
The answer is to add a FULLTEXT index on the content column and to use MySQL’s built-in full-text search feature. These two choices are appropriate because a FULLTEXT index is specifically designed for efficient word-based searching within large text fields, enabling MySQL’s internal full-text search engine to rank results by relevance, while the built-in feature provides the query syntax—like MATCH...AGAINST—to leverage that index. On the Google Professional Cloud Database Engineer exam, this question tests your understanding of schema design for Cloud SQL MySQL, particularly the distinction between search-optimized indexing and inefficient alternatives like LIKE clauses or external storage. A common trap is confusing normalization or external services with in-database full-text capabilities. Remember the memory tip: “FULLTEXT for full-text” — if you need to search words inside a column, the index name tells you the tool.
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
✓
Use Cloud SQL's built-in full-text search feature.
Cloud SQL for MySQL provides built-in full-text search capabilities that allow efficient searching of text data. Adding a FULLTEXT index on the content column enables the use of MATCH...AGAINST queries, which are optimized for natural language search and are far more performant than LIKE operations. This is the correct approach because it leverages the database engine's native indexing and search algorithms.
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.
- ✗
Use the LIKE operator with wildcards for pattern matching.
Why it's wrong here
LIKE with wildcards is inefficient and not a full-text search solution.
- ✗
Store article content in a Cloud Storage bucket and query metadata.
Why it's wrong here
This is external to Cloud SQL and not a schema design choice.
- ✗
Normalize content into a separate table and use joins.
Why it's wrong here
Normalization does not enable full-text search.
- ✓
Use Cloud SQL's built-in full-text search feature.
Why this is correct
Cloud SQL for MySQL supports full-text search via FULLTEXT indexes and MATCH AGAINST queries.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Add a FULLTEXT index on the content column.
Why this is correct
A FULLTEXT index enables efficient text search queries.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common pitfall in Cloud SQL for MySQL is relying on LIKE with wildcards for text search, which cannot use FULLTEXT indexes and leads to full table scans. Cloud SQL supports FULLTEXT indexes and MATCH...AGAINST queries for efficient full-text search.
Detailed technical explanation
How to think about this question
A FULLTEXT index in MySQL creates an inverted index of words in the text column, enabling fast token-based searches using MATCH...AGAINST in natural language or boolean mode. Under the hood, MySQL uses a built-in parser to tokenize text, filter stopwords, and store word positions, allowing relevance ranking. In a real-world CMS with millions of articles, using FULLTEXT indexes can reduce query time from seconds to milliseconds compared to LIKE '%term%' scans.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this PCDE question test?
Design and implement database schemas — This question tests Design and implement database schemas — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Cloud SQL's built-in full-text search feature. — Cloud SQL for MySQL provides built-in full-text search capabilities that allow efficient searching of text data. Adding a FULLTEXT index on the content column enables the use of MATCH...AGAINST queries, which are optimized for natural language search and are far more performant than LIKE operations. This is the correct approach because it leverages the database engine's native indexing and search algorithms.
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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Last reviewed: Jul 4, 2026
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