The answer is to run VACUUM ANALYZE, as this command refreshes table statistics that the PostgreSQL query planner uses to decide between index scans and sequential scans. When statistics become stale, the planner may underestimate the selectivity of index conditions, leading to inefficient sequential scans that increase query latency—exactly the problem described in the scenario. On the Google Professional Cloud Developer exam, this concept tests your understanding of Cloud SQL for PostgreSQL maintenance operations and how they directly impact query performance in read-heavy reporting environments. A common trap is to focus only on indexing or read replica configuration while neglecting the underlying statistics that drive index usage. Remember that VACUUM ANALYZE is a two-in-one tool: VACUUM reclaims storage and prevents transaction ID wraparound, while ANALYZE updates the planner’s data distribution estimates. A useful memory tip is “VACUUM for space, ANALYZE for pace”—the latter directly improves query speed by enabling smarter index scans.
PCD Building and testing applications Practice Question
This PCD practice question tests your understanding of building and testing applications. 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 Cloud SQL for PostgreSQL instance is experiencing high query latency. The database has a high number of read replicas and is used for reporting. The team has identified that index scans are not being used effectively. Which THREE actions should they take to improve query performance?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Analyze table statistics using VACUUM ANALYZE.
Option A is correct because `VACUUM ANALYZE` updates table statistics that the PostgreSQL query planner relies on to choose efficient index scans. Stale statistics can cause the planner to underestimate the selectivity of index conditions, leading to sequential scans instead of index scans, which increases latency. Regular analysis ensures the planner has accurate data distribution information to optimize query execution plans.
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.
✓
Analyze table statistics using VACUUM ANALYZE.
Why this is correct
Updating statistics helps the query planner choose index scans over sequential scans.
Related concept
Read the scenario before looking for a memorised answer.
✓
Increase the number of CPUs on the primary instance.
Why this is correct
More CPUs can help if queries are CPU-bound due to poor indexing.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable automatic storage increase.
Why it's wrong here
Storage increase handles capacity, not performance or index usage.
✓
Use pg_stat_statements to identify slow queries.
Why this is correct
This extension helps pinpoint queries that are not using indexes.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create additional read replicas.
Why it's wrong here
Read replicas offload read traffic but do not improve index usage on the primary.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between symptom mitigation (adding replicas or CPUs) and root-cause resolution (updating statistics), leading candidates to choose resource scaling options instead of the correct maintenance operation.
Detailed technical explanation
How to think about this question
PostgreSQL's query planner uses statistics stored in `pg_statistic` (collected by `ANALYZE`) to estimate the cost of index scans versus sequential scans. When statistics are outdated, the planner may incorrectly assume that a sequential scan is cheaper, especially on large tables with skewed data distributions. The `pg_stat_statements` extension (Option D) helps identify which queries are slow, but the corrective action to improve index usage is to refresh statistics with `ANALYZE` or `VACUUM ANALYZE`.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Building and testing applications — This question tests Building and testing applications — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Analyze table statistics using VACUUM ANALYZE. — Option A is correct because `VACUUM ANALYZE` updates table statistics that the PostgreSQL query planner relies on to choose efficient index scans. Stale statistics can cause the planner to underestimate the selectivity of index conditions, leading to sequential scans instead of index scans, which increases latency. Regular analysis ensures the planner has accurate data distribution information to optimize query execution plans.
What should I do if I get this PCD 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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