Microsoft DP-800 Practice Test 44
Question 430
At Brookfield Labs, a DMV suggests a large covering index for a busy write table. The observed constraint is: A single recommendation ignores write/storage cost. Which recurring metrics identify BOTH usage of the proposed index and the additional **storage footprint** it creates, rather than measuring only its effect on write latency?
- Monitor index usage and storage overhead
- Monitor Query Store regressed queries
- Monitor index seek usage and write cost
- Monitor version-store usage and long transactions
Explanation
Correct Answer
A:
A single recommendation ignores write/storage cost. Monitor index usage and storage overhead.
Incorrect Answers
B:
“Monitor Query Store regressed queries” concerns Query Store captures a new high-cost plan; the reported problem instead is A single recommendation ignores write/storage cost. Monitor index usage and storage overhead.
C:
Index-seek counts and write cost can reveal performance trade-offs, but the question specifically requires measurement of accumulated index storage overhead together with actual usage. The usage/storage pair in A covers both named metrics.
D:
“Monitor version-store usage and long transactions” concerns Concurrent updates produce inconsistent intermediate totals; the reported problem instead is A single recommendation ignores write/storage cost. Monitor index usage and storage overhead.
Question 431
A database engineer at Cascade Manufacturing is investigating this case: Queries scan millions of rows after a skewed data load. The relevant finding is: Outdated statistics misestimate filtered cardinality. What initial check best narrows the technical cause without altering business data?
- Inspect actual plans, existing overlapping indexes and workloads
- Compare plans, duration and deployment timestamp
- Compare statistics age and actual-versus-estimated rows
- Inspect index key order and WHERE/JOIN predicate patterns
Explanation
Correct Answer
C:
Outdated statistics misestimate filtered cardinality. Compare statistics age and actual-versus-estimated rows.
Incorrect Answers
A:
“Inspect actual plans, existing overlapping indexes and workloads” concerns A single recommendation ignores write/storage cost; the reported problem instead is Outdated statistics misestimate filtered cardinality. Compare statistics age and actual-versus-estimated rows.
B:
“Compare plans, duration and deployment timestamp” concerns Query Store captures a new high-cost plan; the reported problem instead is Outdated statistics misestimate filtered cardinality. Compare statistics age and actual-versus-estimated rows.
D:
“Inspect index key order and WHERE/JOIN predicate patterns” concerns Existing index begins with a rarely filtered column; the reported problem instead is Outdated statistics misestimate filtered cardinality. Compare statistics age and actual-versus-estimated rows.
Question 432
Clearwater Utilities is responsible for an Azure SQL or Microsoft SQL workload. Queries scan millions of rows after a skewed data load. Operational evidence: Outdated statistics misestimate filtered cardinality. Which proposed change is the most suitable response to the observed constraint?
- Use appropriate plan-stability or parameter-sensitivity strategy based on supported engine
- Correct indexing/statistics or use an approved plan correction mechanism
- Improve batching and supported rowgroup maintenance strategy
- Update appropriate statistics or adjust stats maintenance process
Explanation
Correct Answer
D:
Outdated statistics misestimate filtered cardinality. Update appropriate statistics or adjust stats maintenance process.
Incorrect Answers
A:
“Use appropriate plan-stability or parameter-sensitivity strategy based on supported engine” concerns The cached query plan favors one selectivity pattern; the reported problem instead is Outdated statistics misestimate filtered cardinality. Update appropriate statistics or adjust stats maintenance process.
B:
“Correct indexing/statistics or use an approved plan correction mechanism” concerns Query Store captures a new high-cost plan; the reported problem instead is Outdated statistics misestimate filtered cardinality. Update appropriate statistics or adjust stats maintenance process.
C:
“Improve batching and supported rowgroup maintenance strategy” concerns Columnstore contains many small delta rowgroups; the reported problem instead is Outdated statistics misestimate filtered cardinality. Update appropriate statistics or adjust stats maintenance process.
Question 433
At Cedarbridge Health, queries scan millions of rows after a skewed data load. The observed constraint is: Outdated statistics misestimate filtered cardinality. What isolated pilot would provide the strongest evidence before rollout?
- Replay representative sort with captured plans
- Replay affected query with prior and candidate plan on snapshot
- Load skewed fixture and compare query plans before/after stats refresh
- Bulk-load comparable test batches and run aggregates
Explanation
Correct Answer
C:
Outdated statistics misestimate filtered cardinality. Load skewed fixture and compare query plans before/after stats refresh.
Incorrect Answers
A:
“Replay representative sort with captured plans” concerns Actual plan warns of spill and high memory grant; the reported problem instead is Outdated statistics misestimate filtered cardinality. Load skewed fixture and compare query plans before/after stats refresh.
B:
“Replay affected query with prior and candidate plan on snapshot” concerns Query Store captures a new high-cost plan; the reported problem instead is Outdated statistics misestimate filtered cardinality. Load skewed fixture and compare query plans before/after stats refresh.
D:
“Bulk-load comparable test batches and run aggregates” concerns Columnstore contains many small delta rowgroups; the reported problem instead is Outdated statistics misestimate filtered cardinality. Load skewed fixture and compare query plans before/after stats refresh.
Question 434
A database engineer at Ashwood Solutions is investigating this case: Queries scan millions of rows after a skewed data load. The relevant finding is: Outdated statistics misestimate filtered cardinality. Which acceptance result most directly demonstrates the requirement has been satisfied?
- Compressed rowgroups and scan efficiency improve
- Invariant preserved and expected one transaction eventually succeeds
- Plan uses efficient seeks without excessive key lookups
- Cardinality estimates and plan selection improve appropriately
Explanation
Correct Answer
D:
Outdated statistics misestimate filtered cardinality. Cardinality estimates and plan selection improve appropriately.
Incorrect Answers
A:
“Compressed rowgroups and scan efficiency improve” concerns Columnstore contains many small delta rowgroups; the reported problem instead is Outdated statistics misestimate filtered cardinality. Cardinality estimates and plan selection improve appropriately.
B:
“Invariant preserved and expected one transaction eventually succeeds” concerns App treats concurrency conflict as permanent failure; the reported problem instead is Outdated statistics misestimate filtered cardinality. Cardinality estimates and plan selection improve appropriately.
C:
“Plan uses efficient seeks without excessive key lookups” concerns Existing index begins with a rarely filtered column; the reported problem instead is Outdated statistics misestimate filtered cardinality. Cardinality estimates and plan selection improve appropriately.
Question 435
Seabrook University is responsible for an Azure SQL or Microsoft SQL workload. Queries scan millions of rows after a skewed data load. Operational evidence: Outdated statistics misestimate filtered cardinality. What operational condition would provide the earliest useful regression warning?
- Monitor index seek usage and write cost
- Monitor plan forcing and parameter regression
- Monitor index usage and storage overhead
- Monitor stats modification counts and plan churn
Explanation
Correct Answer
D:
Outdated statistics misestimate filtered cardinality. Monitor stats modification counts and plan churn.
Incorrect Answers
A:
“Monitor index seek usage and write cost” concerns Existing index begins with a rarely filtered column; the reported problem instead is Outdated statistics misestimate filtered cardinality. Monitor stats modification counts and plan churn.
B:
“Monitor plan forcing and parameter regression” concerns The cached query plan favors one selectivity pattern; the reported problem instead is Outdated statistics misestimate filtered cardinality. Monitor stats modification counts and plan churn.
C:
“Monitor index usage and storage overhead” concerns A single recommendation ignores write/storage cost; the reported problem instead is Outdated statistics misestimate filtered cardinality. Monitor stats modification counts and plan churn.
Question 436
At Atlas Publishing, a highly selective lookup repeatedly scans a large customers table. The observed constraint is: Existing index begins with a rarely filtered column. What initial check best narrows the technical cause without altering business data?
- Inspect index key order and WHERE/JOIN predicate patterns
- Inspect isolation and row-version conflict errors
- Inspect actual plans, existing overlapping indexes and workloads
- Collect deadlock XML and lock acquisition order
Explanation
Correct Answer
A:
Existing index begins with a rarely filtered column. Inspect index key order and WHERE/JOIN predicate patterns.
Incorrect Answers
B:
“Inspect isolation and row-version conflict errors” concerns App treats concurrency conflict as permanent failure; the reported problem instead is Existing index begins with a rarely filtered column. Inspect index key order and WHERE/JOIN predicate patterns.
C:
“Inspect actual plans, existing overlapping indexes and workloads” concerns A single recommendation ignores write/storage cost; the reported problem instead is Existing index begins with a rarely filtered column. Inspect index key order and WHERE/JOIN predicate patterns.
D:
“Collect deadlock XML and lock acquisition order” concerns Deadlock graphs repeatedly identify the same pair of statements; the reported problem instead is Existing index begins with a rarely filtered column. Inspect index key order and WHERE/JOIN predicate patterns.
Question 437
A database engineer at Mountainview Realty is investigating this case: A highly selective lookup repeatedly scans a large customers table. The relevant finding is: Existing index begins with a rarely filtered column. Which proposed change is the most suitable response to the observed constraint?
- Evaluate consolidated indexes against read/write impact instead of blindly applying DMV hint
- Update appropriate statistics or adjust stats maintenance process
- Create or revise composite index key order for dominant filters
- Fix cardinality/index design or query shape before increasing resources
Explanation
Correct Answer
C:
Existing index begins with a rarely filtered column. Create or revise composite index key order for dominant filters.
Incorrect Answers
A:
“Evaluate consolidated indexes against read/write impact instead of blindly applying DMV hint” concerns A single recommendation ignores write/storage cost; the reported problem instead is Existing index begins with a rarely filtered column. Create or revise composite index key order for dominant filters.
B:
“Update appropriate statistics or adjust stats maintenance process” concerns Outdated statistics misestimate filtered cardinality; the reported problem instead is Existing index begins with a rarely filtered column. Create or revise composite index key order for dominant filters.
D:
“Fix cardinality/index design or query shape before increasing resources” concerns Actual plan warns of spill and high memory grant; the reported problem instead is Existing index begins with a rarely filtered column. Create or revise composite index key order for dominant filters.
Question 438
Willow Creek Finance is responsible for an Azure SQL or Microsoft SQL workload. A highly selective lookup repeatedly scans a large customers table. Operational evidence: Existing index begins with a rarely filtered column. What isolated pilot would provide the strongest evidence before rollout?
- Benchmark lookups before/after on representative dataset
- Benchmark candidate and baseline indexes under mixed reads/writes
- Replay representative sort with captured plans
- Benchmark small and large tenant parameter sets in test SQL
Explanation
Correct Answer
A:
Existing index begins with a rarely filtered column. Benchmark lookups before/after on representative dataset.
Incorrect Answers
B:
“Benchmark candidate and baseline indexes under mixed reads/writes” concerns A single recommendation ignores write/storage cost; the reported problem instead is Existing index begins with a rarely filtered column. Benchmark lookups before/after on representative dataset.
C:
“Replay representative sort with captured plans” concerns Actual plan warns of spill and high memory grant; the reported problem instead is Existing index begins with a rarely filtered column. Benchmark lookups before/after on representative dataset.
D:
“Benchmark small and large tenant parameter sets in test SQL” concerns The cached query plan favors one selectivity pattern; the reported problem instead is Existing index begins with a rarely filtered column. Benchmark lookups before/after on representative dataset.
Question 439
At Granite Ridge Technology, a highly selective lookup repeatedly scans a large customers table. The observed constraint is: Existing index begins with a rarely filtered column. Which acceptance result most directly demonstrates the requirement has been satisfied?
- Query performance returns without incorrect forced assumptions
- Plan uses efficient seeks without excessive key lookups
- End-to-end workload improves after considering maintenance costs
- Cardinality estimates and plan selection improve appropriately
Explanation
Correct Answer
B:
Existing index begins with a rarely filtered column. Plan uses efficient seeks without excessive key lookups.
Incorrect Answers
A:
“Query performance returns without incorrect forced assumptions” concerns Query Store captures a new high-cost plan; the reported problem instead is Existing index begins with a rarely filtered column. Plan uses efficient seeks without excessive key lookups.
C:
“End-to-end workload improves after considering maintenance costs” concerns A single recommendation ignores write/storage cost; the reported problem instead is Existing index begins with a rarely filtered column. Plan uses efficient seeks without excessive key lookups.
D:
“Cardinality estimates and plan selection improve appropriately” concerns Outdated statistics misestimate filtered cardinality; the reported problem instead is Existing index begins with a rarely filtered column. Plan uses efficient seeks without excessive key lookups.
Question 440
A database engineer at Pinecrest Operations is investigating this case: A highly selective lookup repeatedly scans a large customers table. The relevant finding is: Existing index begins with a rarely filtered column. What operational condition would provide the earliest useful regression warning?
- Monitor index seek usage and write cost
- Track index usage and storage overhead
- Monitor version-store usage and long transactions
- Monitor Query Store regressed queries
Explanation
Correct Answer
A:
Existing index begins with a rarely filtered column. Monitor index seek usage and write cost.
Incorrect Answers
B:
“Track index usage and storage overhead” addresses the missing index dmv caution situation—a single recommendation ignores write/storage cost. The observed failure is: Existing index begins with a rarely filtered column. Monitor index seek usage and write cost.
C:
“Monitor version-store usage and long transactions” concerns Concurrent updates produce inconsistent intermediate totals; the reported problem instead is Existing index begins with a rarely filtered column. Monitor index seek usage and write cost.
D:
“Monitor Query Store regressed queries” concerns Query Store captures a new high-cost plan; the reported problem instead is Existing index begins with a rarely filtered column. Monitor index seek usage and write cost.