DP-300 Practice Question: Monitor, configure, and optimize database resources
Exhibit
Refer to the exhibit. The following KQL query is used to analyze performance metrics for an Azure SQL Database: AzureDiagnostics | where ResourceProvider == "MICROSOFT.SQL" | where Category == "QueryStoreRuntimeStatistics" | summarize avg_duration = avg(duration_s) by query_hash, DatabaseName | where avg_duration > 1000 | order by avg_duration desc
The query returns a list of query hashes with high average duration. You need to identify which queries are most likely causing CPU pressure. What additional metric should you include?
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
✓
Include avg_cpu_time to measure CPU usage.
Avg_cpu_time directly measures CPU usage per query, helping correlate high duration with CPU pressure. Option A is incorrect because wait_stats show wait types (e.g., blocking), not CPU consumption. Option B is incorrect because execution count alone does not indicate CPU usage; a query could run frequently but use little CPU. Option C is incorrect because avg_logical_reads measure I/O, not CPU pressure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Include wait_stats to see blocking.
Why it's wrong here
Wait stats are for concurrency, not CPU.
- ✗
Include count_executions to see frequency.
Why it's wrong here
Frequency doesn't show CPU cost per execution.
- ✗
Include avg_logical_reads to see I/O consumption.
Why it's wrong here
Logical reads are I/O, not CPU.
- ✓
Include avg_cpu_time to measure CPU usage.
Why this is correct
CPU time directly measures CPU consumption.
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