DP-300 Plan and implement data platform resources Practice Question
You are monitoring an Azure SQL Database and notice a pattern of high CPU usage during business hours. You need to identify the queries consuming the most CPU over the last 24 hours. Which dynamic management view should you query?
⚠ Common exam trap
Candidates often confuse sys.dm_exec_requests (current activity) with sys.dm_exec_query_stats (historical aggregated stats), leading them to choose Option A because they think 'requests' implies all recent queries, but it only shows currently running queries.
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
✓
sys.dm_exec_query_stats
sys.dm_exec_query_stats (Option C) is the correct DMV because it returns aggregate performance statistics for cached query plans, including total CPU time (total_worker_time), execution count, and last execution time. By querying this view and ordering by total_worker_time descending, you can identify the queries that have consumed the most CPU over the last 24 hours, directly addressing the pattern of high CPU usage during business hours.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
sys.dm_exec_requests
Why it's wrong here
Shows only currently running requests, not historical.
- ✗
sys.dm_exec_sessions
Why it's wrong here
Shows session info, not query CPU.
- ✓
sys.dm_exec_query_stats
Why this is correct
Provides aggregated CPU time for queries over time.
- ✗
sys.dm_os_performance_counters
Why it's wrong here
Shows performance counters, not query-level CPU.
Go deeper
Related to this question
Learn chapter
Overview of Azure Data Platform Options
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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