The correct answer is stale statistics causing the optimizer to underestimate cardinality. When statistics are outdated, the query optimizer in Azure SQL Database miscalculates the number of rows a join will process, leading it to favor a nested loops join—which performs well with small row counts—over a hash join, which is more efficient for larger datasets. This regression from hash to nested loops is a classic sign of cardinality underestimation, as the optimizer mistakenly believes it can process rows quickly with nested loops, only to suffer from excessive iterations. On the DP-300 exam, this scenario tests your understanding of how Query Store reveals plan regressions and your ability to distinguish stale statistics from other common causes like parameter sniffing or missing indexes. A common trap is confusing parameter sniffing, which typically causes plan changes based on initial parameter values, not a consistent shift from hash to nested loops. Memory tip: think “stale stats slow loops”—when statistics are stale, the optimizer loops into trouble.
DP-300 Practice Question: Monitor, configure, and optimize database resources
This DP-300 practice question tests your understanding of monitor, configure, and optimize database resources. 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 performance issue on an Azure SQL Database. Query Store shows a significant increase in query duration for a specific query. The execution plan has changed from a hash join to a nested loops join. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Stale statistics caused the optimizer to underestimate cardinality
Option B is correct because a plan regression often occurs when statistics are stale, causing the optimizer to choose a suboptimal plan. Option A is wrong because parameter sniffing can cause plan changes but usually the plan is based on initial parameter values, not all parameters. Option C is wrong because missing indexes would cause scans, not a change from hash to nested loops. Option D is wrong because forced parameterization might stabilize plans but does not cause this change.
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.
✗
Parameter sniffing caused the optimizer to choose a plan for atypical parameter values
Why it's wrong here
Could cause a different plan but less likely than stale stats.
✗
An index was dropped, forcing a table scan
Why it's wrong here
Would cause scan, not nested loops join.
✗
Forced parameterization was enabled
Why it's wrong here
Would not typically change join type.
✓
Stale statistics caused the optimizer to underestimate cardinality
Why this is correct
Leads to nested loops instead of hash join due to underestimation.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-300 question in full detail.
Identify which DP-300 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Monitor, configure, and optimize database resources — This question tests Monitor, configure, and optimize database resources — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Stale statistics caused the optimizer to underestimate cardinality — Option B is correct because a plan regression often occurs when statistics are stale, causing the optimizer to choose a suboptimal plan. Option A is wrong because parameter sniffing can cause plan changes but usually the plan is based on initial parameter values, not all parameters. Option C is wrong because missing indexes would cause scans, not a change from hash to nested loops. Option D is wrong because forced parameterization might stabilize plans but does not cause this change.
What should I do if I get this DP-300 question wrong?
Identify which DP-300 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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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