- A
High write workloads can lead to frequent cache invalidation, reducing its effectiveness.
Every table modification invalidates cached queries for that table, making cache less useful for write-heavy workloads.
- B
The query cache can become fragmented and require periodic defragmentation.
Fragmentation reduces cache efficiency and can be mitigated by adjusting cache size or resetting.
- C
Query cache uses disk storage for cached results.
Why wrong: The query cache is stored in memory, not on disk.
- D
The query cache is deprecated and removed in MySQL 8.0+, so it should not be relied upon for new deployments.
MySQL 8.0 removed the query cache, so alternative caching strategies must be used.
- E
Prepared statements always bypass the query cache.
Why wrong: Prepared statements can use the query cache if they are identical binary representations.
Quick Answer
The answer is that the query cache is deprecated and removed in MySQL 8.0+, so it should not be relied upon for new Cloud SQL deployments. This is correct because high write workloads cause frequent table updates, which invalidate cached query results, forcing the cache to be repopulated and adding overhead that degrades performance rather than improving it. On the Google Professional Cloud Database Engineer exam, this tests your awareness of MySQL version-specific deprecations and the pitfalls of relying on legacy features in managed services like Cloud SQL. A common trap is assuming query caching is always beneficial, but the exam emphasizes that modern MySQL versions and Cloud SQL’s architecture favor alternative optimizations like read replicas or InnoDB buffer pool tuning. Remember the memory tip: “Write-heavy workloads wreck the cache—if it’s deprecated, don’t deploy it.”
PCDE Monitor and optimize database performance Practice Question
This PCDE practice question tests your understanding of monitor and optimize database performance. 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.
Which THREE factors should you consider when configuring Cloud SQL for MySQL query caching to optimize performance?
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
High write workloads can lead to frequent cache invalidation, reducing its effectiveness.
Option A is correct because in Cloud SQL for MySQL, high write workloads cause frequent updates to tables, which invalidates the query cache entries for those tables. This means the cache must be repopulated often, reducing the hit rate and potentially adding overhead from cache maintenance, making it less effective for performance optimization.
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.
- ✓
High write workloads can lead to frequent cache invalidation, reducing its effectiveness.
Why this is correct
Every table modification invalidates cached queries for that table, making cache less useful for write-heavy workloads.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
The query cache can become fragmented and require periodic defragmentation.
Why this is correct
Fragmentation reduces cache efficiency and can be mitigated by adjusting cache size or resetting.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Query cache uses disk storage for cached results.
Why it's wrong here
The query cache is stored in memory, not on disk.
- ✓
The query cache is deprecated and removed in MySQL 8.0+, so it should not be relied upon for new deployments.
Why this is correct
MySQL 8.0 removed the query cache, so alternative caching strategies must be used.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Prepared statements always bypass the query cache.
Why it's wrong here
Prepared statements can use the query cache if they are identical binary representations.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that the query cache uses disk storage, when in fact it uses memory, and that prepared statements always bypass the cache, which is not universally true across all MySQL configurations.
Detailed technical explanation
How to think about this question
The MySQL query cache works by storing the exact text of a SELECT query and its result set in memory; any modification (INSERT, UPDATE, DELETE) to the underlying table invalidates all cached queries referencing that table. In Cloud SQL, the query cache is a shared resource across connections, and its size is controlled by the 'query_cache_size' parameter, which must be carefully tuned to avoid memory pressure. For high-write workloads, the overhead of constant invalidation can actually degrade performance, which is why MySQL 8.0+ deprecated and removed the feature entirely.
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
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PCDE question test?
Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: High write workloads can lead to frequent cache invalidation, reducing its effectiveness. — Option A is correct because in Cloud SQL for MySQL, high write workloads cause frequent updates to tables, which invalidates the query cache entries for those tables. This means the cache must be repopulated often, reducing the hit rate and potentially adding overhead from cache maintenance, making it less effective for performance optimization.
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: Jun 30, 2026
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.
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