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A data engineering team wants to limit cloud costs by stopping compute after job tasks finish, rather than keeping an all-purpose cluster active every night.
Which acceptance result most directly demonstrates that the intended solution works?
Job compute resources can be provisioned for a run and released afterward, reducing unnecessary idle costs.
The clean job run resolves its dependencies without requiring an interactive cluster setup. That finding does not establish that compute is deallocated after task completion and billed usage matches the workload window.
A failing validation result prevents publication and activates the intended failure path. That finding does not establish that compute is deallocated after task completion and billed usage matches the workload window.
The consumer task never starts before its producer has completed successfully. That finding does not establish that compute is deallocated after task completion and billed usage matches the workload window.
A notebook succeeds in an interactive session but its scheduled job fails because it relied on an undeclared package installed only on the author's cluster.
Which implementation decision best addresses this requirement?
Production job environments must include all libraries rather than inheriting accidental state from a developer cluster. The selected implementation is the one directly aligned with the constraints in the scenario.
Task keys are identifiers used by the orchestrator to build an unambiguous DAG.
Starting a job before its required data arrives creates avoidable idle time and retry noise.
Trigger selection must match the upstream change mechanism that exists in the real pipeline.
A notebook succeeds in an interactive session but its scheduled job fails because it relied on an undeclared package installed only on the author's cluster.
Which acceptance result most directly demonstrates that the intended solution works?
Production job environments must include all libraries rather than inheriting accidental state from a developer cluster.
The validated graph has unique task identifiers and all depends_on references resolve. That finding does not establish that the clean job run resolves its dependencies without requiring an interactive cluster setup.
Execution begins after the required source update and the dashboard meets its freshness target. That finding does not establish that the clean job run resolves its dependencies without requiring an interactive cluster setup.
A table commit starts the job without creating a synthetic storage file. That finding does not establish that the clean job run resolves its dependencies without requiring an interactive cluster setup.
Two task definitions use the same task key in a job configuration and the deployed DAG behaves unpredictably.
Which implementation decision best addresses this requirement?
Task keys are identifiers used by the orchestrator to build an unambiguous DAG. The selected implementation is the one directly aligned with the constraints in the scenario.
Control-flow decisions should depend on explicit upstream task results rather than manually editing task states.
Ad hoc replay is a separate operational action from modifying an automated recurring trigger.
Job-completion dependencies model cross-job sequencing more directly than arbitrary timer offsets.
Two task definitions use the same task key in a job configuration and the deployed DAG behaves unpredictably.
Which acceptance result most directly demonstrates that the intended solution works?
Task keys are identifiers used by the orchestrator to build an unambiguous DAG.
A failing validation result prevents publication and activates the intended failure path. That finding does not establish that the validated graph has unique task identifiers and all depends_on references resolve.
One replay processes the requested partition and future scheduled runs retain their normal calendar. That finding does not establish that the validated graph has unique task identifiers and all depends_on references resolve.
Downstream execution starts after the intended predecessor completes successfully. That finding does not establish that the validated graph has unique task identifiers and all depends_on references resolve.
A finance job should publish a Gold table only after a source-validation notebook writes a boolean pass/fail result.
Which implementation decision best addresses this requirement?
Control-flow decisions should depend on explicit upstream task results rather than manually editing task states. The selected implementation is the one directly aligned with the constraints in the scenario.
Starting a job before its required data arrives creates avoidable idle time and retry noise.
A DAG documents resource dependencies and prevents tasks from running before their inputs are ready.
DAG status inspection exposes upstream blockers more directly than just looking at total elapsed time.
A finance job should publish a Gold table only after a source-validation notebook writes a boolean pass/fail result.
Which acceptance result most directly demonstrates that the intended solution works?
Control-flow decisions should depend on explicit upstream task results rather than manually editing task states.
Execution begins after the required source update and the dashboard meets its freshness target. That finding does not establish that a failing validation result prevents publication and activates the intended failure path.
The consumer task never starts before its producer has completed successfully. That finding does not establish that a failing validation result prevents publication and activates the intended failure path.
The blocked task's dependency is identified and the reason for waiting is visible. That finding does not establish that a failing validation result prevents publication and activates the intended failure path.
A schedule-based pipeline is expected to meet a 06:00 dashboard deadline but routinely spends two hours waiting for upstream tables to appear.
Which implementation decision best addresses this requirement?
Starting a job before its required data arrives creates avoidable idle time and retry noise. The selected implementation is the one directly aligned with the constraints in the scenario.
Ad hoc replay is a separate operational action from modifying an automated recurring trigger.
Trigger selection must match the upstream change mechanism that exists in the real pipeline.
Runtime configuration separates environment routing from transformation logic.
A schedule-based pipeline is expected to meet a 06:00 dashboard deadline but routinely spends two hours waiting for upstream tables to appear.
Which acceptance result most directly demonstrates that the intended solution works?
Starting a job before its required data arrives creates avoidable idle time and retry noise.
One replay processes the requested partition and future scheduled runs retain their normal calendar. That finding does not establish that execution begins after the required source update and the dashboard meets its freshness target.
A table commit starts the job without creating a synthetic storage file. That finding does not establish that execution begins after the required source update and the dashboard meets its freshness target.
A staging run writes only to staging tables and production uses its authorized catalog. That finding does not establish that execution begins after the required source update and the dashboard meets its freshness target.
A jobs administrator needs a one-time replay of yesterday's failed data partition without permanently changing the production cron schedule.
Which implementation decision best addresses this requirement?
Ad hoc replay is a separate operational action from modifying an automated recurring trigger. The selected implementation is the one directly aligned with the constraints in the scenario.
A DAG documents resource dependencies and prevents tasks from running before their inputs are ready.
Job-completion dependencies model cross-job sequencing more directly than arbitrary timer offsets.
Time-spaced retries avoid magnifying transient saturation and preserve a finite failure policy.
A jobs administrator needs a one-time replay of yesterday's failed data partition without permanently changing the production cron schedule.
Which acceptance result most directly demonstrates that the intended solution works?
Ad hoc replay is a separate operational action from modifying an automated recurring trigger.
The consumer task never starts before its producer has completed successfully. That finding does not establish that one replay processes the requested partition and future scheduled runs retain their normal calendar.
Downstream execution starts after the intended predecessor completes successfully. That finding does not establish that one replay processes the requested partition and future scheduled runs retain their normal calendar.
The log shows delayed retries and eventual successful completion when the source recovers. That finding does not establish that one replay processes the requested partition and future scheduled runs retain their normal calendar.
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