Exam Bundle

That observation is a valid indicator for “The planner initially picks a shuffle join but one input becomes broadcast-eligible after filtering” when using Allow AQE to adapt supported join strategy at runtime. The scenario instead tests “A batch runtime plan changes but analysts worry results are inconsistent”; the relevant result is Both optimized and baseline execution return equivalent final records.

That observation is a valid indicator for “Executors are overwhelmed by excessive task count from tiny shuffle partitions” when using Tune/adopt AQE coalescing and advisory partition settings. The scenario instead tests “A batch runtime plan changes but analysts worry results are inconsistent”; the relevant result is Both optimized and baseline execution return equivalent final records.

That observation is a valid indicator for “Shuffle partitions are badly sized at runtime due to variable daily input” when using Enable supported Adaptive Query Execution partition coalescing. The scenario instead tests “A batch runtime plan changes but analysts worry results are inconsistent”; the relevant result is Both optimized and baseline execution return equivalent final records.

Downsize after benchmarking query durations and concurrency is appropriate when “A workload is stable and an oversized warehouse wastes resources”; it would be verified by Measured SLO remains satisfied with lower billing usage. It does not directly satisfy “Peak interactive workload queues queries despite low individual query duration,” whose relevant acceptance evidence is Query queue time falls during measured peak load.

This action solves a different issue: “An idle development SQL warehouse keeps running and accumulating avoidable cost.” Its normal signal is The warehouse stops after its configured inactivity period. Here the requested behavior is “Peak interactive workload queues queries despite low individual query duration,” so that signal is not sufficient.

This action solves a different issue: “A dashboard has frequent small queries and startup delay dominates response time.” Its normal signal is Dashboard p95 latency includes acceptable startup behavior. Here the requested behavior is “Peak interactive workload queues queries despite low individual query duration,” so that signal is not sufficient.

That observation is a valid indicator for “A workload is stable and an oversized warehouse wastes resources” when using Downsize after benchmarking query durations and concurrency. The scenario instead tests “Peak interactive workload queues queries despite low individual query duration”; the relevant result is Query queue time falls during measured peak load.

The warehouse stops after its configured inactivity period would demonstrate the separate action Enable reasonable auto-stop and serverless eligibility, which addresses “An idle development SQL warehouse keeps running and accumulating avoidable cost.” It does not verify the requirement “Peak interactive workload queues queries despite low individual query duration” following Scale up or out eligible SQL warehouse capacity to match concurrency.

Dashboard p95 latency includes acceptable startup behavior pertains to a different control (Use an appropriately sized always-ready or short-autostop SQL warehouse for the SLO) and a different need (A dashboard has frequent small queries and startup delay dominates response time). It cannot establish that Scale up or out eligible SQL warehouse capacity to match concurrency met the stated goal.

This action solves a different issue: “A dashboard has frequent small queries and startup delay dominates response time.” Its normal signal is Dashboard p95 latency includes acceptable startup behavior. Here the requested behavior is “An idle development SQL warehouse keeps running and accumulating avoidable cost,” so that signal is not sufficient.

Scale up or out eligible SQL warehouse capacity to match concurrency is appropriate when “Peak interactive workload queues queries despite low individual query duration”; it would be verified by Query queue time falls during measured peak load. It does not directly satisfy “An idle development SQL warehouse keeps running and accumulating avoidable cost,” whose relevant acceptance evidence is The warehouse stops after its configured inactivity period.

Downsize after benchmarking query durations and concurrency is appropriate when “A workload is stable and an oversized warehouse wastes resources”; it would be verified by Measured SLO remains satisfied with lower billing usage. It does not directly satisfy “An idle development SQL warehouse keeps running and accumulating avoidable cost,” whose relevant acceptance evidence is The warehouse stops after its configured inactivity period.

Query queue time falls during measured peak load would demonstrate the separate action Scale up or out eligible SQL warehouse capacity to match concurrency, which addresses “Peak interactive workload queues queries despite low individual query duration.” It does not verify the requirement “An idle development SQL warehouse keeps running and accumulating avoidable cost” following Enable reasonable auto-stop and serverless eligibility.

That observation is a valid indicator for “A scheduled heavy ETL job competes for slots with interactive BI users” when using Separate ETL compute from user-facing SQL workload capacity. The scenario instead tests “An idle development SQL warehouse keeps running and accumulating avoidable cost”; the relevant result is The warehouse stops after its configured inactivity period.

Dashboard p95 latency includes acceptable startup behavior would demonstrate the separate action Use an appropriately sized always-ready or short-autostop SQL warehouse for the SLO, which addresses “A dashboard has frequent small queries and startup delay dominates response time.” It does not verify the requirement “An idle development SQL warehouse keeps running and accumulating avoidable cost” following Enable reasonable auto-stop and serverless eligibility.

Enable reasonable auto-stop and serverless eligibility is appropriate when “An idle development SQL warehouse keeps running and accumulating avoidable cost”; it would be verified by The warehouse stops after its configured inactivity period. It does not directly satisfy “A dashboard has frequent small queries and startup delay dominates response time,” whose relevant acceptance evidence is Dashboard p95 latency includes acceptable startup behavior.

Downsize after benchmarking query durations and concurrency belongs to the separate case “A workload is stable and an oversized warehouse wastes resources,” where Measured SLO remains satisfied with lower billing usage would be expected. That differs from the condition in this stem: “A dashboard has frequent small queries and startup delay dominates response time.”

The alternative Separate ETL compute from user-facing SQL workload capacity has a distinct purpose—A scheduled heavy ETL job competes for slots with interactive BI users. It would not establish the required outcome (A dashboard has frequent small queries and startup delay dominates response time); the necessary verification concerns Dashboard p95 latency includes acceptable startup behavior.

Query queue time falls during measured peak load would demonstrate the separate action Scale up or out eligible SQL warehouse capacity to match concurrency, which addresses “Peak interactive workload queues queries despite low individual query duration.” It does not verify the requirement “A dashboard has frequent small queries and startup delay dominates response time” following Use an appropriately sized always-ready or short-autostop SQL warehouse for the SLO.

That observation is a valid indicator for “A scheduled heavy ETL job competes for slots with interactive BI users” when using Separate ETL compute from user-facing SQL workload capacity. The scenario instead tests “A dashboard has frequent small queries and startup delay dominates response time”; the relevant result is Dashboard p95 latency includes acceptable startup behavior.

This signal belongs to the adjacent case “A workload is stable and an oversized warehouse wastes resources,” whose remedy is Downsize after benchmarking query durations and concurrency. The observed result for the present requirement is Dashboard p95 latency includes acceptable startup behavior.

Downsize after benchmarking query durations and concurrency is appropriate when “A workload is stable and an oversized warehouse wastes resources”; it would be verified by Measured SLO remains satisfied with lower billing usage. It does not directly satisfy “A scheduled heavy ETL job competes for slots with interactive BI users,” whose relevant acceptance evidence is BI query queue time improves while ETL completes independently.

Enable reasonable auto-stop and serverless eligibility is appropriate when “An idle development SQL warehouse keeps running and accumulating avoidable cost”; it would be verified by The warehouse stops after its configured inactivity period. It does not directly satisfy “A scheduled heavy ETL job competes for slots with interactive BI users,” whose relevant acceptance evidence is BI query queue time improves while ETL completes independently.

This action solves a different issue: “A dashboard has frequent small queries and startup delay dominates response time.” Its normal signal is Dashboard p95 latency includes acceptable startup behavior. Here the requested behavior is “A scheduled heavy ETL job competes for slots with interactive BI users,” so that signal is not sufficient.

That observation is a valid indicator for “A workload is stable and an oversized warehouse wastes resources” when using Downsize after benchmarking query durations and concurrency. The scenario instead tests “A scheduled heavy ETL job competes for slots with interactive BI users”; the relevant result is BI query queue time improves while ETL completes independently.

That observation is a valid indicator for “A dashboard has frequent small queries and startup delay dominates response time” when using Use an appropriately sized always-ready or short-autostop SQL warehouse for the SLO. The scenario instead tests “A scheduled heavy ETL job competes for slots with interactive BI users”; the relevant result is BI query queue time improves while ETL completes independently.

The warehouse stops after its configured inactivity period pertains to a different control (Enable reasonable auto-stop and serverless eligibility) and a different need (An idle development SQL warehouse keeps running and accumulating avoidable cost). It cannot establish that Separate ETL compute from user-facing SQL workload capacity met the stated goal.

Use an appropriately sized always-ready or short-autostop SQL warehouse for the SLO is appropriate when “A dashboard has frequent small queries and startup delay dominates response time”; it would be verified by Dashboard p95 latency includes acceptable startup behavior. It does not directly satisfy “A workload is stable and an oversized warehouse wastes resources,” whose relevant acceptance evidence is Measured SLO remains satisfied with lower billing usage.

The alternative Scale up or out eligible SQL warehouse capacity to match concurrency has a distinct purpose—Peak interactive workload queues queries despite low individual query duration. It would not establish the required outcome (A workload is stable and an oversized warehouse wastes resources); the necessary verification concerns Measured SLO remains satisfied with lower billing usage.

This action solves a different issue: “An idle development SQL warehouse keeps running and accumulating avoidable cost.” Its normal signal is The warehouse stops after its configured inactivity period. Here the requested behavior is “A workload is stable and an oversized warehouse wastes resources,” so that signal is not sufficient.

This signal belongs to the adjacent case “A dashboard has frequent small queries and startup delay dominates response time,” whose remedy is Use an appropriately sized always-ready or short-autostop SQL warehouse for the SLO. The observed result for the present requirement is Measured SLO remains satisfied with lower billing usage.

BI query queue time improves while ETL completes independently would demonstrate the separate action Separate ETL compute from user-facing SQL workload capacity, which addresses “A scheduled heavy ETL job competes for slots with interactive BI users.” It does not verify the requirement “A workload is stable and an oversized warehouse wastes resources” following Downsize after benchmarking query durations and concurrency.

That observation is a valid indicator for “Peak interactive workload queues queries despite low individual query duration” when using Scale up or out eligible SQL warehouse capacity to match concurrency. The scenario instead tests “A workload is stable and an oversized warehouse wastes resources”; the relevant result is Measured SLO remains satisfied with lower billing usage.