Quick Answer
The answer is Rows scanned and CPU time. Rows scanned directly reveals whether a secondary index is selective enough; if the query still scans a large number of rows despite using an index, the index is poorly chosen or the query retrieves too much data, causing excessive I/O and latency. CPU time indicates expensive operations like sorting, joining, or complex filtering that slow performance even when an index is used. On the Google Professional Cloud Database Engineer exam, this tests your ability to distinguish between index-related inefficiency and computational overhead—a common trap is focusing only on latency or execution count, which are less direct. Remember the mnemonic “Scan and Spin”: Rows scanned tells you how much data is touched, CPU time tells you how hard the engine works to process it. Together, they pinpoint whether the bottleneck is data volume or processing cost.
This PCDE practice question tests your understanding of monitor and optimize database performance. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
You are troubleshooting a slow-performing query on Cloud Spanner. The query scans a large table with a secondary index. Which TWO metrics from the Query Insights dashboard would most directly indicate the source of the performance issue?
CPU time
High CPU time indicates the query is computationally expensive.
Rows scanned
High rows scanned suggests the query is reading too many rows, possibly due to missing filters.
Storage utilization
Why wrong: Storage utilization is a capacity metric.
Commit latency
Why wrong: Commit latency applies to write transactions, not read queries.
Lock wait time
Why wrong: Lock wait time is for write contention, not read queries.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
CPU time
CPU time (A) is correct because high CPU usage indicates that the query is performing expensive operations like sorting, joining, or complex filtering, which can slow performance even if the index is used. Rows scanned (B) is correct because scanning a large number of rows, even with a secondary index, suggests the index is not selective enough or the query is retrieving many rows, leading to excessive I/O and latency. Both metrics directly point to query execution inefficiency.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
CPU time
Why this is correct
High CPU time indicates the query is computationally expensive.
Related concept
Read the scenario before looking for a memorised answer.
Rows scanned
Why this is correct
High rows scanned suggests the query is reading too many rows, possibly due to missing filters.
Related concept
Read the scenario before looking for a memorised answer.
Storage utilization
Why it's wrong here
Storage utilization is a capacity metric.
Commit latency
Why it's wrong here
Commit latency applies to write transactions, not read queries.
Lock wait time
Why it's wrong here
Lock wait time is for write contention, not read queries.
Common exam traps
Google Cloud often tests the distinction between metrics that indicate query execution inefficiency (CPU time, rows scanned) versus metrics related to storage or write contention, leading candidates to mistakenly select storage utilization or lock wait time for a read-only query performance issue.
Detailed technical explanation
Under the hood, Cloud Spanner's Query Insights tracks CPU time as the sum of CPU seconds consumed across all nodes for query execution, which correlates directly with computational cost. Rows scanned reflects the number of rows read from storage before filtering; a high value often indicates a full index scan or a non-selective index, which can be mitigated by using a covering index or rewriting the query to push filters. In real-world scenarios, a query scanning millions of rows but returning only a few rows is a classic sign of poor index design or missing filters.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
Monitor and optimize database performance — This question tests Monitor and optimize database performance — Read the scenario before looking for a memorised answer..
The correct answer is: CPU time — CPU time (A) is correct because high CPU usage indicates that the query is performing expensive operations like sorting, joining, or complex filtering, which can slow performance even if the index is used. Rows scanned (B) is correct because scanning a large number of rows, even with a secondary index, suggests the index is not selective enough or the query is retrieving many rows, leading to excessive I/O and latency. Both metrics directly point to query execution inefficiency.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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