Databricks Certified Data Engineer Associate Practice Test 48
Question 470
Consider the shipment_manifests_west workload at Coastal freight alliance: shipment_manifests_west access exception uses a DENY policy without verifying feature support and scope. Inspection found that review finds the target resource is outside the supported ABAC deny-policy securable types. The governed outcome must ensure that authorization must use supported policy semantics without assuming beta behavior. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. Which staged rollout best preserves the existing workload?
- Use supported UC grants and only supported ABAC deny policies where available
- Pilot the policy in a test catalog and confirm evaluation result
- Assume any DENY syntax universally applies to all Unity Catalog objects at Coastal freight alliance
- Test denied and permitted identities on the exact target object
Explanation
Correct Answer
B:Pilot the policy in a test catalog and confirm evaluation result provides a bounded way to introduce the approved solution into shipment_manifests_west and detect an early mismatch. The existing signal is review finds the target resource is outside the supported ABAC deny-policy securable types; a staged change protects the service requirement (authorization must use supported policy semantics without assuming beta behavior) and makes rollback practical.
Incorrect Answers
A:Use supported UC grants and only supported ABAC deny policies where available is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the shipment_manifests_west scenario, the observed evidence is that review finds the target resource is outside the supported ABAC deny-policy securable types; the requirement remains: authorization must use supported policy semantics without assuming beta behavior.
C:Beta deny policy semantics are not universal to every securable type. The proposed action (Assume any DENY syntax universally applies to all Unity Catalog objects at Coastal freight alliance) does not meet the requirement that authorization must use supported policy semantics without assuming beta behavior, nor does it constitute the controlled implementation step.
D:Test denied and permitted identities on the exact target object is a one-time acceptance check. It does not supply the controlled implementation step for shipment_manifests_west; a passing test cannot substitute for the specific task now required.
Question 471
Consider the match_session_events_urban workload at Cloud gaming cooperative: match_session_events_urban test run overwrites production tables because both deployment targets share one catalog. Inspection found that resolved bundle targets point to the same UC prefix. The governed outcome must ensure that development tests must not mutate production data. The first acceptance run passed. The current task is to detect future regressions and changes over time. Which continuing signal best reveals recurrence or drift?
- Use identical production destinations and hope developers avoid dangerous input at Cloud gaming cooperative
- Segregate dev/test/prod catalog settings using bundle target overrides
- Run destructive test inputs and verify production table remains unchanged
- Monitor cross-environment writes and unexpected permissions for match_session_events_urban
Explanation
Correct Answer
D:Monitor cross-environment writes and unexpected permissions for match_session_events_urban creates recurring visibility into the failure mode (match_session_events_urban test run overwrites production tables because both deployment targets share one catalog). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while development tests must not mutate production data.
Incorrect Answers
A:Shared output targets defeat environment isolation. The proposed action (Use identical production destinations and hope developers avoid dangerous input at Cloud gaming cooperative) does not meet the requirement that development tests must not mutate production data, nor does it constitute continuing operational detection.
B:Segregate dev/test/prod catalog settings using bundle target overrides is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the match_session_events_urban scenario, the observed evidence is that resolved bundle targets point to the same UC prefix; the requirement remains: development tests must not mutate production data.
C:Run destructive test inputs and verify production table remains unchanged is a one-time acceptance check. It does not supply continuing operational detection for match_session_events_urban; a passing test cannot substitute for the specific task now required.
Question 472
Consider the smart_meter_readings_delta workload at Community energy cooperative: smart_meter_readings_delta aggregation spends most time scheduling thousands of tiny shuffle tasks. Inspection found that Spark UI shows very low per-task data size and excessive scheduling overhead. The governed outcome must ensure that performance changes must be benchmarked against the same output. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which data-engineering approach resolves the documented weakness?
- Inspect shuffle output size, task duration and partition setting for smart_meter_readings_delta
- Increase shuffle partitions without measuring task size or skew at Community energy cooperative
- Tune spark.sql.shuffle.partitions or AQE behavior based on measured shuffle workload
- Watch task count, spill and stage duration after tuning smart_meter_readings_delta
Explanation
Correct Answer
C:Tune spark.sql.shuffle.partitions or AQE behavior based on measured shuffle workload is the intended durable approach for smart_meter_readings_delta: it addresses the verified problem (smart_meter_readings_delta aggregation spends most time scheduling thousands of tiny shuffle tasks) while preserving the required behavior (performance changes must be benchmarked against the same output). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Inspect shuffle output size, task duration and partition setting for smart_meter_readings_delta could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The smart_meter_readings_delta workflow still requires that performance changes must be benchmarked against the same output.
B:Arbitrary partition expansion can increase overhead. The proposed action (Increase shuffle partitions without measuring task size or skew at Community energy cooperative) does not meet the requirement that performance changes must be benchmarked against the same output, nor does it constitute the target approach.
D:Watch task count, spill and stage duration after tuning smart_meter_readings_delta would help detect future recurrence, but metrics alone do not deliver the target approach. The smart_meter_readings_delta requirement is that performance changes must be benchmarked against the same output.
Question 473
A data engineer at Local government portal is responsible for citizen service applications. The derived column withColumn issue is that citizen_service_applications_west needs a normalized discount amount but the pipeline overwrites the source field. The supporting evidence is that code review shows an arithmetic expression replacing original gross_sales. The engineer must ensure that auditors require gross and net amounts independently. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which durable Databricks control best addresses the requirement?
- Monitor negative net amounts and source-to-derived reconciliation for citizen_service_applications_west
- Use withColumn to add a derived net amount while keeping gross_sales unchanged
- Inspect expression dependencies and column lineage for citizen_service_applications_west
- Overwrite the only gross amount and discard source values at Local government portal
Explanation
Correct Answer
B:Use withColumn to add a derived net amount while keeping gross_sales unchanged is the intended durable approach for citizen_service_applications_west: it addresses the verified problem (citizen_service_applications_west needs a normalized discount amount but the pipeline overwrites the source field) while preserving the required behavior (auditors require gross and net amounts independently). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Monitor negative net amounts and source-to-derived reconciliation for citizen_service_applications_west would help detect future recurrence, but metrics alone do not deliver the target approach. The citizen_service_applications_west requirement is that auditors require gross and net amounts independently.
C:Inspect expression dependencies and column lineage for citizen_service_applications_west could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The citizen_service_applications_west workflow still requires that auditors require gross and net amounts independently.
D:Overwriting original financial evidence breaks reconciliation. The proposed action (Overwrite the only gross amount and discard source values at Local government portal) does not meet the requirement that auditors require gross and net amounts independently, nor does it constitute the target approach.
Question 474
Consider the smart_meter_readings_metro workload at Community energy cooperative: BI users query smart_meter_readings_metro through engineering notebook compute with unpredictable startup and permissions. Inspection found that query history shows short read-only dashboards competing with development Spark sessions. The governed outcome must ensure that analysts need governed SQL concurrency and stable refresh latency. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which evidence-gathering action should precede an architectural change?
- Migrate one dashboard and verify warehouse permissions and query plans
- Grant BI users unrestricted notebook cluster administration at Community energy cooperative
- Classify smart_meter_readings_metro query mix, concurrency and compute isolation requirements
- Serve the BI workload on an appropriately sized SQL warehouse with Unity Catalog access
Explanation
Correct Answer
C:Classify smart_meter_readings_metro query mix, concurrency and compute isolation requirements directly investigates the evidence (query history shows short read-only dashboards competing with development Spark sessions) and distinguishes possible causes of BI users query smart_meter_readings_metro through engineering notebook compute with unpredictable startup and permissions. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: analysts need governed SQL concurrency and stable refresh latency.
Incorrect Answers
A:Migrate one dashboard and verify warehouse permissions and query plans may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the required pre-change investigation, especially given the evidence that query history shows short read-only dashboards competing with development Spark sessions. This matters here because consider the smart_meter_readings_metro workload at Community energy cooperative: BI users query….
B:Broad compute administration is not necessary to query governed bi data. The proposed action (Grant BI users unrestricted notebook cluster administration at Community energy cooperative) does not meet the requirement that analysts need governed SQL concurrency and stable refresh latency, nor does it constitute the required pre-change investigation.
D:Serve the BI workload on an appropriately sized SQL warehouse with Unity Catalog access is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the smart_meter_readings_metro scenario, the observed evidence is that query history shows short read-only dashboards competing with development Spark sessions; the requirement remains: analysts need governed SQL concurrency and stable refresh latency.
Question 475
At Multinational parts distributor, the Spark SQL NULL semantics workflow handles warehouse movement logs. The problem is that warehouse_movement_logs_north SQL filter misses transactions where the nullable flag was never populated. Evidence: the predicate uses flag = NULL and always yields unknown. Constraint: the analysis must distinguish missing from explicitly false flag values. The first acceptance run passed. The current task is to detect future regressions and changes over time. Which monitoring approach will detect newly emerging defects?
- Monitor unknown-flag rate and predicate regression for warehouse_movement_logs_north
- Use IS NULL for missing flags and IS NOT NULL for populated fields
- Test null, false and true rows against the intended filter
- Use flag = NULL and assume it matches missing values at Multinational parts distributor
Explanation
Correct Answer
A:Monitor unknown-flag rate and predicate regression for warehouse_movement_logs_north creates recurring visibility into the failure mode (warehouse_movement_logs_north SQL filter misses transactions where the nullable flag was never populated). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the analysis must distinguish missing from explicitly false flag values.
Incorrect Answers
B:Use IS NULL for missing flags and IS NOT NULL for populated fields is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the warehouse_movement_logs_north scenario, the observed evidence is that the predicate uses flag = NULL and always yields unknown; the requirement remains: the analysis must distinguish missing from explicitly false flag values.
C:Test null, false and true rows against the intended filter is a one-time acceptance check. It does not supply continuing operational detection for warehouse_movement_logs_north; a passing test cannot substitute for the specific task now required.
D:Sql equality against null is not true. The proposed action (Use flag = NULL and assume it matches missing values at Multinational parts distributor) does not meet the requirement that the analysis must distinguish missing from explicitly false flag values, nor does it constitute continuing operational detection.
Question 476
A data engineer at Independent cinema group is responsible for ticket transactions. The job conditional branching issue is that ticket_transactions_coastal quality validation flags an empty input but the pipeline always publishes gold. The supporting evidence is that the job DAG lacks an if/else decision based on validation outcome. The engineer must ensure that empty invalid batches must skip publication while still reporting status. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. What evidence establishes that correct output is maintained?
- Always run publish regardless of validator outcome at Independent cinema group
- Deploy a condition and branch tasks using an output from the validator
- Test valid and invalid input and verify only the intended branch executes
- Identify the condition output and branch decisions required for ticket_transactions_coastal
Explanation
Correct Answer
C:Test valid and invalid input and verify only the intended branch executes directly tests the behavior that should change after the correction. With the observed evidence (the job DAG lacks an if/else decision based on validation outcome), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that empty invalid batches must skip publication while still reporting status.
Incorrect Answers
A:Unconditional publication violates the quality gate. The proposed action (Always run publish regardless of validator outcome at Independent cinema group) does not meet the requirement that empty invalid batches must skip publication while still reporting status, nor does it constitute the post-change acceptance test.
B:Deploy a condition and branch tasks using an output from the validator may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the post-change acceptance test, especially given the evidence that the job DAG lacks an if/else decision based on validation outcome.
D:Identify the condition output and branch decisions required for ticket_transactions_coastal could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The ticket_transactions_coastal workflow still requires that empty invalid batches must skip publication while still reporting status.
Question 477
At Food delivery franchise, the dispatch and delivery status workflow depends on dispatch_and_delivery_status_highland. Engineers report that dispatch_and_delivery_status_highland sort aggregation spills gigabytes of intermediates to disk; the evidence is that stage metrics show spilled bytes and GC pressure on executors. They require that the job should improve without losing aggregation accuracy. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. Which post-change acceptance check is strongest?
- Verify output and decreased spill plus completion time
- Trial an adjusted executor configuration on identical data volume
- Disable logs and assume spilled data was never written at Food delivery franchise
- Compare per-task memory, partition sizes and spill metrics for dispatch_and_delivery_status_highland
Explanation
Correct Answer
A:Verify output and decreased spill plus completion time directly tests the behavior that should change after the correction. With the observed evidence (stage metrics show spilled bytes and GC pressure on executors), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the job should improve without losing aggregation accuracy.
Incorrect Answers
B:Trial an adjusted executor configuration on identical data volume may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the post-change acceptance test, especially given the evidence that stage metrics show spilled bytes and GC pressure on executors.
C:Missing telemetry cannot correct memory pressure. The proposed action (Disable logs and assume spilled data was never written at Food delivery franchise) does not meet the requirement that the job should improve without losing aggregation accuracy, nor does it constitute the post-change acceptance test.
D:Compare per-task memory, partition sizes and spill metrics for dispatch_and_delivery_status_highland could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The dispatch_and_delivery_status_highland workflow still requires that the job should improve without losing aggregation accuracy.
Question 478
The sampling_field_notes_metro pipeline at Environmental inspection office has this failure: the sampling_field_notes_metro import creates a single malformed column because input format settings are wrong. The team observed that source inspection shows UTF-8 CSV with an explicit header and quoted delimiters. Business requirement: all source columns must map to the intended typed Delta fields. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. What test most directly proves the requirement is satisfied?
- Test the file format on a small sample, then run the governed target load
- Inspect sample files and COPY INTO format options for sampling_field_notes_metro
- Load comma-separated records with JSON parsing and suppress all errors at Environmental inspection office
- Compare parsed field count, null patterns and source record counts
Explanation
Correct Answer
D:Compare parsed field count, null patterns and source record counts directly tests the behavior that should change after the correction. With the observed evidence (source inspection shows UTF-8 CSV with an explicit header and quoted delimiters), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that all source columns must map to the intended typed Delta fields.
Incorrect Answers
A:Test the file format on a small sample, then run the governed target load may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the post-change acceptance test, especially given the evidence that source inspection shows UTF-8 CSV with an explicit header and quoted delimiters.
B:Inspect sample files and COPY INTO format options for sampling_field_notes_metro could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The sampling_field_notes_metro workflow still requires that all source columns must map to the intended typed Delta fields.
C:The parser would misread the source schema rather than fix its mapping. The proposed action (Load comma-separated records with JSON parsing and suppress all errors at Environmental inspection office) does not meet the requirement that all source columns must map to the intended typed Delta fields, nor does it constitute the post-change acceptance test.
Question 479
At Municipal waste service, the collection telemetry workflow depends on collection_telemetry_island. Engineers report that a streaming file reader for collection_telemetry_island reprocesses historical data after every job restart; the evidence is that the streaming query creates a new checkpoint directory on each run. They require that a restart must resume discovered files instead of replaying all existing input. The target approach is approved. The current task is to introduce it safely with bounded scope and rollback. Which controlled implementation step is appropriate now?
- Delete checkpoint state as part of each successful load at Municipal waste service
- Deploy the stream with a durable checkpoint and restart the same logical query
- Configure cloudFiles with a stable checkpoint path for the collection_telemetry_island stream
- Restart after a micro-batch and confirm no duplicate file ingestion
Explanation
Correct Answer
B:Deploy the stream with a durable checkpoint and restart the same logical query provides a bounded way to introduce the approved solution into collection_telemetry_island and detect an early mismatch. The existing signal is the streaming query creates a new checkpoint directory on each run; a staged change protects the service requirement (a restart must resume discovered files instead of replaying all existing input) and makes rollback practical.
Incorrect Answers
A:Deleting checkpoint progress can cause full replay. The proposed action (Delete checkpoint state as part of each successful load at Municipal waste service) does not meet the requirement that a restart must resume discovered files instead of replaying all existing input, nor does it constitute the controlled implementation step.
C:Configure cloudFiles with a stable checkpoint path for the collection_telemetry_island stream is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the collection_telemetry_island scenario, the observed evidence is that the streaming query creates a new checkpoint directory on each run; the requirement remains: a restart must resume discovered files instead of replaying all existing input.
D:Restart after a micro-batch and confirm no duplicate file ingestion is a one-time acceptance check. It does not supply the controlled implementation step for collection_telemetry_island; a passing test cannot substitute for the specific task now required.
Question 480
Consider the sampling_field_notes_north workload at Environmental inspection office: sampling_field_notes_north reporting team plans to drop a UC-managed table but needs its data files retained. Inspection found that table ownership review shows storage lifecycle controlled by Unity Catalog. The governed outcome must ensure that a cleanup must not accidentally delete retained source data. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. Which evidence-gathering action should precede an architectural change?
- Move to approved external storage only through a supported governed migration
- Assume managed and external tables always have identical drop semantics at Environmental inspection office
- Choose managed or external table lifecycle deliberately for the retention requirement
- Inspect table type, location and intended retention before dropping sampling_field_notes_north
Explanation
Correct Answer
D:Inspect table type, location and intended retention before dropping sampling_field_notes_north directly investigates the evidence (table ownership review shows storage lifecycle controlled by Unity Catalog) and distinguishes possible causes of sampling_field_notes_north reporting team plans to drop a UC-managed table but needs its data files retained. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: a cleanup must not accidentally delete retained source data.
Incorrect Answers
A:Move to approved external storage only through a supported governed migration may introduce a correction, but the question does not ask for installation or migration. A rollout alone cannot replace the required pre-change investigation, especially given the evidence that table ownership review shows storage lifecycle controlled by Unity Catalog.
B:Uc table type affects ownership and managed data lifecycle. The proposed action (Assume managed and external tables always have identical drop semantics at Environmental inspection office) does not meet the requirement that a cleanup must not accidentally delete retained source data, nor does it constitute the required pre-change investigation.
C:Choose managed or external table lifecycle deliberately for the retention requirement is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the sampling_field_notes_north scenario, the observed evidence is that table ownership review shows storage lifecycle controlled by Unity Catalog; the requirement remains: a cleanup must not accidentally delete retained source data.