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Exam Code: DP-800

Exam Name: Developing AI-Enabled Database Solutions

Certification Provider: Microsoft

Corresponding Certification: Microsoft Certified: SQL AI Developer Associate

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Microsoft DP-800 Practice Test 45

Question 440

A database has stable plans but waits show CPU and IO saturation at the current service tier. Which result would provide the strongest acceptance evidence?

  1. Peak load tests meet resource, latency, and cost limits after the chosen adjustment.
  2. A stale write is detected and retried or rejected rather than silently overwriting new data.
  3. Concurrent reports avoid dirty data while meeting tested read/write throughput goals.
  4. Only authorized auditors can view or alter audit records and retention meets policy.

Explanation

Correct Answer

A:

Capacity selection should reflect measured demand, not only the number of users. The observation “Peak load tests meet resource, latency, and cost limits after the chosen adjustment” directly confirms the chosen action worked for this situation: A database has stable plans but waits show CPU and IO saturation at the current service tier.

Incorrect Answers

B:

Optimistic concurrency compares version tokens to prevent lost updates without holding long locks. This observation would not establish that the required result occurred for A database has stable plans but waits show CPU and IO saturation at the current service tier. The confirming test is: Peak load tests meet resource, latency, and cost limits after the chosen adjustment.

C:

READ UNCOMMITTED or NOLOCK may read uncommitted changes; row versioning can improve concurrency without dirty reads. This observation would not establish that the required result occurred for A database has stable plans but waits show CPU and IO saturation at the current service tier. The confirming test is: Peak load tests meet resource, latency, and cost limits after the chosen adjustment.

D:

Audit credibility depends on destination protection and retention, not just enabling the event stream. This observation would not establish that the required result occurred for A database has stable plans but waits show CPU and IO saturation at the current service tier. The confirming test is: Peak load tests meet resource, latency, and cost limits after the chosen adjustment.

Question 441

A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. What should the database team change FIRST for this workload?

  1. Profile latch waits and evaluate suitable index/table design or supported last-page contention mitigation.
  2. Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.
  3. Add a unique stable tie-breaker to ordering and consider keyset pagination for mutable streams.
  4. Route appropriate Azure Monitor diagnostic logs into Log Analytics with approved retention.

Explanation

Correct Answer

B:

Statistics guide cardinality estimation; stale distributions can cause inefficient joins and memory grants. For the described situation—A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong—the targeted fix is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints. A successful test should show: Estimated and actual row counts become more consistent and query latency improves.

Incorrect Answers

A:

Page-level hot spots can constrain concurrency beyond disk capacity; fixes require evidence of actual latch waits. But that technique does not solve the stated problem—A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. The needed intervention is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.

C:

Stable ordering is essential for pagination; OFFSET without a unique key can duplicate or omit records. But that technique does not solve the stated problem—A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. The needed intervention is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.

D:

Log Analytics provides centralized queryable telemetry; metrics dashboards alone do not store every event. But that technique does not solve the stated problem—A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. The needed intervention is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.

Question 442

A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. Which acceptance check should accompany the remediation?

  1. A controlled test triggers the intended alert with enough context for response.
  2. Representative parameter values meet latency targets without breaking atypical cases.
  3. Oversized queries are denied or paged while ordinary client requests meet latency goals.
  4. Estimated and actual row counts become more consistent and query latency improves.

Explanation

Correct Answer

D:

Statistics guide cardinality estimation; stale distributions can cause inefficient joins and memory grants. The observation “Estimated and actual row counts become more consistent and query latency improves” directly confirms the chosen action worked for this situation: A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong.

Incorrect Answers

A:

Monitoring becomes operationally useful when routed to timely alerts rather than passive dashboards. This observation would not establish that the required result occurred for A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. The confirming test is: Estimated and actual row counts become more consistent and query latency improves.

B:

Query Store keeps plan/runtime history and can help isolate parameter-sensitive plan regressions. This observation would not establish that the required result occurred for A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. The confirming test is: Estimated and actual row counts become more consistent and query latency improves.

C:

GraphQL and REST query surfaces require limits to prevent accidental overfetch and resource exhaustion. This observation would not establish that the required result occurred for A query performs nested-loop lookups millions of times after a table cardinality estimate is wrong. The confirming test is: Estimated and actual row counts become more consistent and query latency improves.

Question 443

A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. Which implementation most directly satisfies the stated requirement?

  1. Use Query Store to compare plans and apply an appropriate vetted plan correction or hint.
  2. Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.
  3. Inspect actual execution plans and relevant Query Store runtime statistics before changing indexes.
  4. Add unit tests for data rules and integration tests using a representative test database.

Explanation

Correct Answer

B:

Statistics guide cardinality estimation; stale distributions can cause inefficient joins and memory grants. For the described situation—A complex join has stale statistics and the optimizer chooses an unsuitable join strategy—the targeted fix is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints. A successful test should show: Estimated and actual row counts become more consistent and query latency improves.

Incorrect Answers

A:

Query Store keeps plan/runtime history and can help isolate parameter-sensitive plan regressions. But that technique does not solve the stated problem—A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. The needed intervention is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.

C:

Execution plans show access paths and join strategies; blind indexing is not reliable diagnosis. But that technique does not solve the stated problem—A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. The needed intervention is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.

D:

Build validation checks syntax/schema dependencies; tests verify behavior and interactions. But that technique does not solve the stated problem—A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. The needed intervention is Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.

Question 444

A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. What measurement or test best demonstrates that the requirement is satisfied?

  1. The blocker and blocked session chain are identified with actionable wait evidence.
  2. A query plan uses the intended index range seek and returns identical date-filtered rows.
  3. Negative tests prove an assistant cannot issue unauthorized DDL or DML through the endpoint.
  4. Estimated and actual row counts become more consistent and query latency improves.

Explanation

Correct Answer

D:

Statistics guide cardinality estimation; stale distributions can cause inefficient joins and memory grants. The observation “Estimated and actual row counts become more consistent and query latency improves” directly confirms the chosen action worked for this situation: A complex join has stale statistics and the optimizer chooses an unsuitable join strategy.

Incorrect Answers

A:

DMVs expose current session/wait state; Query Store primarily provides historical query performance. This observation would not establish that the required result occurred for A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. The confirming test is: Estimated and actual row counts become more consistent and query latency improves.

B:

Applying functions to indexed columns often prevents efficient predicate seek pushdown. This observation would not establish that the required result occurred for A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. The confirming test is: Estimated and actual row counts become more consistent and query latency improves.

C:

MCP is an action gateway; server-side permissions and tool allowlists are necessary even with trusted prompts. This observation would not establish that the required result occurred for A complex join has stale statistics and the optimizer chooses an unsuitable join strategy. The confirming test is: Estimated and actual row counts become more consistent and query latency improves.

Question 445

A Sort operator repeatedly spills to tempdb and slows a large grouped query. What is the most defensible next technical action?

  1. Inspect execution-plan estimates and update relevant statistics before proposing disruptive hints.
  2. Project only required columns and measure a covering index or columnstore fit.
  3. Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.
  4. Restrict MCP tool surfaces to approved operations, read-only roles, and audited access.

Explanation

Correct Answer

C:

Tempdb spills indicate memory/workload mismatch and should be diagnosed from actual plans. For the described situation—A Sort operator repeatedly spills to tempdb and slows a large grouped query—the targeted fix is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans. A successful test should show: The spill disappears or decreases and the query meets latency targets without new regressions.

Incorrect Answers

A:

Statistics guide cardinality estimation; stale distributions can cause inefficient joins and memory grants. But that technique does not solve the stated problem—A Sort operator repeatedly spills to tempdb and slows a large grouped query. The needed intervention is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.

B:

Overfetching wastes IO and network capacity; targeted projection can allow lean index access. But that technique does not solve the stated problem—A Sort operator repeatedly spills to tempdb and slows a large grouped query. The needed intervention is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.

D:

MCP is an action gateway; server-side permissions and tool allowlists are necessary even with trusted prompts. But that technique does not solve the stated problem—A Sort operator repeatedly spills to tempdb and slows a large grouped query. The needed intervention is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.

Question 446

A Sort operator repeatedly spills to tempdb and slows a large grouped query. Which result distinguishes a successful implementation from a cosmetic change?

  1. The spill disappears or decreases and the query meets latency targets without new regressions.
  2. Repeated paging covers the intended rows in deterministic order under the documented consistency model.
  3. A stale write is detected and retried or rejected rather than silently overwriting new data.
  4. A staging migration retains record counts and transforms fields without data loss.

Explanation

Correct Answer

A:

Tempdb spills indicate memory/workload mismatch and should be diagnosed from actual plans. The observation “The spill disappears or decreases and the query meets latency targets without new regressions” directly confirms the chosen action worked for this situation: A Sort operator repeatedly spills to tempdb and slows a large grouped query.

Incorrect Answers

B:

Stable ordering is essential for pagination; OFFSET without a unique key can duplicate or omit records. This observation would not establish that the required result occurred for A Sort operator repeatedly spills to tempdb and slows a large grouped query. The confirming test is: The spill disappears or decreases and the query meets latency targets without new regressions.

C:

Optimistic concurrency compares version tokens to prevent lost updates without holding long locks. This observation would not establish that the required result occurred for A Sort operator repeatedly spills to tempdb and slows a large grouped query. The confirming test is: The spill disappears or decreases and the query meets latency targets without new regressions.

D:

Declarative deployment may generate destructive operations; data-loss protection and review are essential. This observation would not establish that the required result occurred for A Sort operator repeatedly spills to tempdb and slows a large grouped query. The confirming test is: The spill disappears or decreases and the query meets latency targets without new regressions.

Question 447

A query has insufficient memory grant for a wide ORDER BY on a large result set. Which solution is the most appropriate for the scenario?

  1. Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.
  2. Profile latch waits and evaluate suitable index/table design or supported last-page contention mitigation.
  3. Use SERIALIZABLE or appropriate locking for the invariant after load testing.
  4. Set the SQL project target platform correctly and validate compatibility before generating a deployment.

Explanation

Correct Answer

A:

Tempdb spills indicate memory/workload mismatch and should be diagnosed from actual plans. For the described situation—A query has insufficient memory grant for a wide ORDER BY on a large result set—the targeted fix is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans. A successful test should show: The spill disappears or decreases and the query meets latency targets without new regressions.

Incorrect Answers

B:

Page-level hot spots can constrain concurrency beyond disk capacity; fixes require evidence of actual latch waits. But that technique does not solve the stated problem—A query has insufficient memory grant for a wide ORDER BY on a large result set. The needed intervention is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.

C:

Serializable isolation prevents phantom/invariant anomalies with stronger locking and possible contention. But that technique does not solve the stated problem—A query has insufficient memory grant for a wide ORDER BY on a large result set. The needed intervention is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.

D:

Target platform models determine which schema features are valid in the destination SQL version. But that technique does not solve the stated problem—A query has insufficient memory grant for a wide ORDER BY on a large result set. The needed intervention is Inspect spills/memory grants and adjust query/indexing or capacity based on measured plans.

Question 448

A query has insufficient memory grant for a wide ORDER BY on a large result set. What should a technical reviewer verify before approving completion?

  1. Concurrent reports avoid dirty data while meeting tested read/write throughput goals.
  2. Blocked request durations fall while consistency requirements still hold.
  3. Red-team test payloads do not reveal internal secrets or disallowed columns.
  4. The spill disappears or decreases and the query meets latency targets without new regressions.

Explanation

Correct Answer

D:

Tempdb spills indicate memory/workload mismatch and should be diagnosed from actual plans. The observation “The spill disappears or decreases and the query meets latency targets without new regressions” directly confirms the chosen action worked for this situation: A query has insufficient memory grant for a wide ORDER BY on a large result set.

Incorrect Answers

A:

READ UNCOMMITTED or NOLOCK may read uncommitted changes; row versioning can improve concurrency without dirty reads. This observation would not establish that the required result occurred for A query has insufficient memory grant for a wide ORDER BY on a large result set. The confirming test is: The spill disappears or decreases and the query meets latency targets without new regressions.

B:

Long transactions prolong lock retention, and extra indexes alone cannot resolve idle open transactions. This observation would not establish that the required result occurred for A query has insufficient memory grant for a wide ORDER BY on a large result set. The confirming test is: The spill disappears or decreases and the query meets latency targets without new regressions.

C:

Securing GraphQL and REST requires response-field minimization in addition to connection authentication. This observation would not establish that the required result occurred for A query has insufficient memory grant for a wide ORDER BY on a large result set. The confirming test is: The spill disappears or decreases and the query meets latency targets without new regressions.

Question 449

A developer wants to know which active sessions are currently blocking a transaction. What should the SQL developer implement after verifying the conditions?

  1. Inspect current waits and blocking sessions via DMVs or supported monitoring tools.
  2. Inspect actual execution plans and relevant Query Store runtime statistics before changing indexes.
  3. Reduce transaction scope, choose suitable indexes/isolation, and keep external calls outside transactions.
  4. Route appropriate Azure Monitor diagnostic logs into Log Analytics with approved retention.

Explanation

Correct Answer

A:

DMVs expose current session/wait state; Query Store primarily provides historical query performance. For the described situation—A developer wants to know which active sessions are currently blocking a transaction—the targeted fix is Inspect current waits and blocking sessions via DMVs or supported monitoring tools. A successful test should show: The blocker and blocked session chain are identified with actionable wait evidence.

Incorrect Answers

B:

Execution plans show access paths and join strategies; blind indexing is not reliable diagnosis. But that technique does not solve the stated problem—A developer wants to know which active sessions are currently blocking a transaction. The needed intervention is Inspect current waits and blocking sessions via DMVs or supported monitoring tools.

C:

Long transactions prolong lock retention, and extra indexes alone cannot resolve idle open transactions. But that technique does not solve the stated problem—A developer wants to know which active sessions are currently blocking a transaction. The needed intervention is Inspect current waits and blocking sessions via DMVs or supported monitoring tools.

D:

Log Analytics provides centralized queryable telemetry; metrics dashboards alone do not store every event. But that technique does not solve the stated problem—A developer wants to know which active sessions are currently blocking a transaction. The needed intervention is Inspect current waits and blocking sessions via DMVs or supported monitoring tools.

Question 450

A developer wants to know which active sessions are currently blocking a transaction. Which verification finding is most specific to this scenario?

  1. Concurrent reports avoid dirty data while meeting tested read/write throughput goals.
  2. Load tests show reduced latch waits and consistent insert correctness.
  3. A replay of change tables reconstructs expected mutations including relevant old and new values.
  4. The blocker and blocked session chain are identified with actionable wait evidence.

Explanation

Correct Answer

D:

DMVs expose current session/wait state; Query Store primarily provides historical query performance. The observation “The blocker and blocked session chain are identified with actionable wait evidence” directly confirms the chosen action worked for this situation: A developer wants to know which active sessions are currently blocking a transaction.

Incorrect Answers

A:

READ UNCOMMITTED or NOLOCK may read uncommitted changes; row versioning can improve concurrency without dirty reads. This observation would not establish that the required result occurred for A developer wants to know which active sessions are currently blocking a transaction. The confirming test is: The blocker and blocked session chain are identified with actionable wait evidence.

B:

Page-level hot spots can constrain concurrency beyond disk capacity; fixes require evidence of actual latch waits. This observation would not establish that the required result occurred for A developer wants to know which active sessions are currently blocking a transaction. The confirming test is: The blocker and blocked session chain are identified with actionable wait evidence.

C:

CDC records change data for replay, unlike simple change tracking versions. This observation would not establish that the required result occurred for A developer wants to know which active sessions are currently blocking a transaction. The confirming test is: The blocker and blocked session chain are identified with actionable wait evidence.

Developing AI-Enabled Database Solutions (DP-800) Practice Tests