Databricks Certified Data Engineer Associate Practice Test 46
Question 450
At Education access provider, the student registration records workflow depends on student_registration_records_east. Engineers report that student_registration_records_east notebook hardcodes a development catalog and writes there during production runs; the evidence is that job run settings differ from values embedded in the notebook code. They require that the same notebook must respect runtime environment configuration. The failure and requirements have been diagnosed; the team must select the lasting pipeline or governance approach. Which platform or PySpark choice best fits the stated semantics?
- Identify job parameter keys and where student_registration_records_east notebook resolves the catalog
- Edit the source notebook by hand every time the job changes environment at Education access provider
- Monitor unresolved parameters and wrong-environment writes for student_registration_records_east
- Pass task parameters through supported notebook widgets or job parameters
Explanation
Correct Answer
D:Pass task parameters through supported notebook widgets or job parameters is the intended durable approach for student_registration_records_east: it addresses the verified problem (student_registration_records_east notebook hardcodes a development catalog and writes there during production runs) while preserving the required behavior (the same notebook must respect runtime environment configuration). A diagnostic or monitoring step alone would not create this target-state behavior.
Incorrect Answers
A:Identify job parameter keys and where student_registration_records_east notebook resolves the catalog could clarify the original fault, but the available evidence already establishes its scope; it is not the target approach now requested. The student_registration_records_east workflow still requires that the same notebook must respect runtime environment configuration.
B:Manual code edits are not reproducible parameterization. The proposed action (Edit the source notebook by hand every time the job changes environment at Education access provider) does not meet the requirement that the same notebook must respect runtime environment configuration, nor does it constitute the target approach.
C:Monitor unresolved parameters and wrong-environment writes for student_registration_records_east would help detect future recurrence, but metrics alone do not deliver the target approach. The student_registration_records_east requirement is that the same notebook must respect runtime environment configuration.
Question 451
At Financial audit partnership, the control testing evidence workflow depends on control_testing_evidence_coastal. Engineers report that the control_testing_evidence_coastal import stores files in personal workspace paths inaccessible to scheduled service principals; the evidence is that a job run fails to read a path that works under one engineer's user session. They require that source files must be reachable through governed identity and stable cloud storage. The first acceptance run passed. The current task is to detect future regressions and changes over time. Which ongoing alert or metric is most relevant?
- Run the same load under the production identity and verify access
- Monitor missing-volume grants and inaccessible source paths for control_testing_evidence_coastal
- Embed a personal access token and home-directory file path in production code at Financial audit partnership
- Land files in a permitted external or managed Unity Catalog volume
Explanation
Correct Answer
B:Monitor missing-volume grants and inaccessible source paths for control_testing_evidence_coastal creates recurring visibility into the failure mode (the control_testing_evidence_coastal import stores files in personal workspace paths inaccessible to scheduled service principals). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while source files must be reachable through governed identity and stable cloud storage.
Incorrect Answers
A:Run the same load under the production identity and verify access is a one-time acceptance check. It does not supply continuing operational detection for control_testing_evidence_coastal; a passing test cannot substitute for the specific task now required.
C:Personal paths and identities do not provide durable service access. The proposed action (Embed a personal access token and home-directory file path in production code at Financial audit partnership) does not meet the requirement that source files must be reachable through governed identity and stable cloud storage, nor does it constitute continuing operational detection.
D:Land files in a permitted external or managed Unity Catalog volume is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the control_testing_evidence_coastal scenario, the observed evidence is that a job run fails to read a path that works under one engineer's user session; the requirement remains: source files must be reachable through governed identity and stable cloud storage.
Question 452
A data engineer at Agricultural credit union is responsible for farm-loan transaction history. The executor OOM issue is that farm_loan_transaction_history_highland transformation intermittently fails with executor out-of-memory. The supporting evidence is that Spark UI shows large skewed partitions and executor lost errors. The engineer must ensure that the job must process full input safely without excluding valid rows. 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?
- Pilot repartitioning or right-sizing against the failing data window
- Run the previously failing input and confirm completion with result parity
- Filter out the largest partition without business approval at Agricultural credit union
- Inspect task partition sizes, execution plan and memory overhead for farm_loan_transaction_history_highland
Explanation
Correct Answer
B:Run the previously failing input and confirm completion with result parity directly tests the behavior that should change after the correction. With the observed evidence (Spark UI shows large skewed partitions and executor lost errors), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the job must process full input safely without excluding valid rows.
Incorrect Answers
A:Pilot repartitioning or right-sizing against the failing data window 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 Spark UI shows large skewed partitions and executor lost errors.
C:Dropping data to avoid oom violates completeness. The proposed action (Filter out the largest partition without business approval at Agricultural credit union) does not meet the requirement that the job must process full input safely without excluding valid rows, nor does it constitute the post-change acceptance test.
D:Inspect task partition sizes, execution plan and memory overhead for farm_loan_transaction_history_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 farm_loan_transaction_history_highland workflow still requires that the job must process full input safely without excluding valid rows.
Question 453
At Consumer finance platform, the scheduled job timezone workflow handles loan repayment events. The problem is that loan_repayment_events_island overnight export fires one hour early after daylight-saving changes. Evidence: run history shows schedule configured in a different timezone than business cutoff. Constraint: the export must complete relative to the local reporting calendar. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. Which test should pass before the new flow is accepted?
- Inspect schedule timezone, cron expression and daylight-saving policy for loan_repayment_events_island
- Verify triggers across DST transition dates against business calendar
- Change the job schedule in a test environment and review next fire times
- Assume all local timezones have the same UTC offset year-round at Consumer finance platform
Explanation
Correct Answer
B:Verify triggers across DST transition dates against business calendar directly tests the behavior that should change after the correction. With the observed evidence (run history shows schedule configured in a different timezone than business cutoff), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the export must complete relative to the local reporting calendar.
Incorrect Answers
A:Inspect schedule timezone, cron expression and daylight-saving policy for loan_repayment_events_island could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The loan_repayment_events_island workflow still requires that the export must complete relative to the local reporting calendar.
C:Change the job schedule in a test environment and review next fire times 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 run history shows schedule configured in a different timezone than business cutoff.
D:Timezones with dst can shift relative to utc. The proposed action (Assume all local timezones have the same UTC offset year-round at Consumer finance platform) does not meet the requirement that the export must complete relative to the local reporting calendar, nor does it constitute the post-change acceptance test.
Question 454
A data engineer at Community energy cooperative is responsible for smart meter readings. The Git branch review issue is that developers edit smart_meter_readings_urban production notebooks directly and bypass code review. The supporting evidence is that workspace Git history shows changes without a pull request. The engineer must ensure that releases need traceable approval and a recoverable commit. The first acceptance run passed. The current task is to detect future regressions and changes over time. What repeatable measure detects this failure after go-live?
- Copy arbitrary notebook cells into production without a commit at Community energy cooperative
- Verify deployed code hash matches the approved merged commit
- Develop in a feature branch with a reviewed pull request before merging
- Monitor direct main-branch pushes and unreviewed notebook changes for smart_meter_readings_urban
Explanation
Correct Answer
D:Monitor direct main-branch pushes and unreviewed notebook changes for smart_meter_readings_urban creates recurring visibility into the failure mode (developers edit smart_meter_readings_urban production notebooks directly and bypass code review). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while releases need traceable approval and a recoverable commit.
Incorrect Answers
A:Untracked copies cannot reliably reproduce the approved source. The proposed action (Copy arbitrary notebook cells into production without a commit at Community energy cooperative) does not meet the requirement that releases need traceable approval and a recoverable commit, nor does it constitute continuing operational detection.
B:Verify deployed code hash matches the approved merged commit is a one-time acceptance check. It does not supply continuing operational detection for smart_meter_readings_urban; a passing test cannot substitute for the specific task now required.
C:Develop in a feature branch with a reviewed pull request before merging is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the smart_meter_readings_urban scenario, the observed evidence is that workspace Git history shows changes without a pull request; the requirement remains: releases need traceable approval and a recoverable commit.
Question 455
Consider the inventory_adjustments_island workload at Retail pharmacy network: inventory_adjustments_island high-frequency triggers create overlapping job runs that overwrite the same gold partition. Inspection found that run history shows two active instances of an identical pipeline. The governed outcome must ensure that concurrent processing must respect destination write semantics. The new approach is deployed. The current task is to prove correct output and authorized behavior, not just successful installation. How should the team verify the original fault has been addressed?
- Send overlapping triggers and confirm bounded jobs and consistent output
- Pilot concurrency limits and deterministic write keys
- Raise maximum concurrent runs without coordinating shared output writes at Retail pharmacy network
- Inspect overlap, idempotency and safe concurrency limit for inventory_adjustments_island
Explanation
Correct Answer
A:Send overlapping triggers and confirm bounded jobs and consistent output directly tests the behavior that should change following the correction. With the observed evidence (run history shows two active instances of an identical pipeline), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that concurrent processing must respect destination write semantics.
Incorrect Answers
B:Pilot concurrency limits and deterministic write keys 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 run history shows two active instances of an identical pipeline. This matters here because consider the inventory_adjustments_island workload at Retail pharmacy network: inventory_adjustments_island….
C:Overlapping unsafe writers can corrupt business results or cause failures. The proposed action (Raise maximum concurrent runs without coordinating shared output writes at Retail pharmacy network) does not meet the requirement that concurrent processing must respect destination write semantics, nor does it constitute the post-change acceptance test.
D:Inspect overlap, idempotency and safe concurrency limit for inventory_adjustments_island could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The inventory_adjustments_island workflow still requires that concurrent processing must respect destination write semantics.
Question 456
The pipeline_flow_metrics_north pipeline at Public water district has this failure: pipeline_flow_metrics_north pipeline configuration exists only in one engineer's workspace UI. The team observed that releasing to test requires manual reconstruction of tasks. Business requirement: the same versioned workload definitions must deploy to multiple targets. The team has not selected a remedy. It first needs evidence that distinguishes the actual dependency or data fault. What should the engineer inspect to establish the failure mechanism?
- Recreate every task manually with different values in each environment at Public water district
- Inventory job, pipeline and permissions resources needed for pipeline_flow_metrics_north
- Deploy the versioned bundle to test then prod with approval and target-specific config
- Package supported jobs and pipelines as Declarative Automation Bundle resources
Explanation
Correct Answer
B:Inventory job, pipeline and permissions resources needed for pipeline_flow_metrics_north directly investigates the evidence (releasing to test requires manual reconstruction of tasks) and distinguishes possible causes of pipeline_flow_metrics_north pipeline configuration exists only in one engineer's workspace UI. It establishes what must be corrected without assuming a fix before verifying the stated business requirement: the same versioned workload definitions must deploy to multiple targets.
Incorrect Answers
A:Manual recreation invites hidden differences and unreproducible releases. The proposed action (Recreate every task manually with different values in each environment at Public water district) does not meet the requirement that the same versioned workload definitions must deploy to multiple targets, nor does it constitute the required pre-change investigation.
C:Deploy the versioned bundle to test then prod with approval and target-particular config 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 releasing to test requires manual reconstruction of tasks.
D:Package supported jobs and pipelines as Declarative Automation Bundle resources is a plausible lasting design once chosen, but it does not perform the required pre-change investigation at this stage. In the pipeline_flow_metrics_north scenario, the observed evidence is that releasing to test requires manual reconstruction of tasks; the requirement remains: the same versioned workload definitions must deploy to multiple targets.
Question 457
At Municipal waste service, the cluster startup failure workflow handles collection telemetry. The problem is that collection_telemetry_coastal job fails before any Spark task begins. Evidence: cluster event log shows an unavailable instance type in the selected region. Constraint: the diagnostic must distinguish compute provisioning failure from ETL code defects. 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?
- Start a fresh cluster then execute one representative task successfully
- Rewrite successful SQL transformations without investigating provisioning at Municipal waste service
- Monitor provisioning failures, retries and startup wait time for collection_telemetry_coastal
- Select a supported compute configuration or serverless option that meets the job constraints
Explanation
Correct Answer
C:Monitor provisioning failures, retries and startup wait time for collection_telemetry_coastal creates recurring visibility into the failure mode (collection_telemetry_coastal job fails before any Spark task begins). Unlike a single successful test, the measure can reveal drift, lag, or new failures after later source and deployment changes while the diagnostic must distinguish compute provisioning failure from ETL code defects.
Incorrect Answers
A:Start a fresh cluster then execute one representative task successfully is a one-time acceptance check. It does not supply continuing operational detection for collection_telemetry_coastal; a passing test cannot substitute for the specific task now required.
B:Query changes cannot fix unavailable compute capacity. The proposed action (Rewrite successful SQL transformations without investigating provisioning at Municipal waste service) does not meet the requirement that the diagnostic must distinguish compute provisioning failure from ETL code defects, nor does it constitute continuing operational detection.
D:Select a supported compute configuration or serverless option that meets the job constraints is a plausible lasting design once chosen, but it does not perform continuing operational detection at this stage. In the collection_telemetry_coastal scenario, the observed evidence is that cluster event log shows an unavailable instance type in the selected region; the requirement remains: the diagnostic must distinguish compute provisioning failure from ETL code defects.
Question 458
At Research clinical trial group, the consent-related data changes workflow depends on consent_related_data_changes_west. Engineers report that consent_related_data_changes_west dataset is shared between clouds and network charges surprise the data provider; the evidence is that billing shows recipient reads create cross-cloud data transfer. They require that sharing must meet cost and policy expectations. 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?
- Design an approved sharing pattern accounting for network egress and access controls
- Pilot a small cross-cloud share and review billing before expansion
- Assume cross-cloud data transfer is always free because sharing is read-only at Research clinical trial group
- Compare actual transfer bytes and charges against the forecast
Explanation
Correct Answer
B:Pilot a small cross-cloud share and review billing before expansion provides a bounded way to introduce the approved solution into consent_related_data_changes_west and detect an early mismatch. The existing signal is billing shows recipient reads create cross-cloud data transfer; a staged change protects the service requirement (sharing must meet cost and policy expectations) and makes rollback practical.
Incorrect Answers
A:Design an approved sharing pattern accounting for network egress and access controls is a plausible lasting design once chosen, but it does not perform the controlled implementation step at this stage. In the consent_related_data_changes_west scenario, the observed evidence is that billing shows recipient reads create cross-cloud data transfer; the requirement remains: sharing must meet cost and policy expectations.
C:Read-only sharing can still incur network charges. The proposed action (Assume cross-cloud data transfer is always free because sharing is read-only at Research clinical trial group) does not meet the requirement that sharing must meet cost and policy expectations, nor does it constitute the controlled implementation step.
D:Compare actual transfer bytes and charges against the forecast is a one-time acceptance check. It does not supply the controlled implementation step for consent_related_data_changes_west; a passing test cannot substitute for the specific task now required.
Question 459
The dispatch_and_delivery_status_south pipeline at Food delivery franchise has this failure: dispatch_and_delivery_status_south managed table has manual OPTIMIZE jobs colliding with platform-managed maintenance. The team observed that table maintenance history shows overlapping compaction attempts. Business requirement: the maintenance policy must avoid redundant cost and scheduling conflict. 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?
- Manually VACUUM all data files before retention safeguards are checked at Food delivery franchise
- Compare file counts, query results and maintenance cost across a full cycle
- Inspect table eligibility, predictive optimization configuration and maintenance history for dispatch_and_delivery_status_south
- Disable the overlapping manual maintenance after verifying managed policy
Explanation
Correct Answer
B:Compare file counts, query results and maintenance cost across a full cycle directly tests the behavior that should change after the correction. With the observed evidence (table maintenance history shows overlapping compaction attempts), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that the maintenance policy must avoid redundant cost and scheduling conflict.
Incorrect Answers
A:Unguarded vacuum can remove files needed for recovery. The proposed action (Manually VACUUM all data files before retention safeguards are checked at Food delivery franchise) does not meet the requirement that the maintenance policy must avoid redundant cost and scheduling conflict, nor does it constitute the post-change acceptance test.
C:Inspect table eligibility, predictive optimization configuration and maintenance history for dispatch_and_delivery_status_south 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_south workflow still requires that the maintenance policy must avoid redundant cost and scheduling conflict.
D:Disable the overlapping manual maintenance after verifying managed policy 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 table maintenance history shows overlapping compaction attempts.
Question 460
At Online apparel cooperative, the customer order changes workflow depends on customer_order_changes_west. Engineers report that customer_order_changes_west test run overwrites production tables because both deployment targets share one catalog; the evidence is that resolved bundle targets point to the same UC prefix. They require that development tests must not mutate production data. 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?
- Deploy a nonproduction copy with unique resource namespace and service identity
- Run destructive test inputs and verify production table remains unchanged
- Compare target resolution, workspace URL and catalog bindings for customer_order_changes_west
- Use identical production destinations and hope developers avoid dangerous input at Online apparel cooperative
Explanation
Correct Answer
B:Run destructive test inputs and verify production table remains unchanged directly tests the behavior that should change after the correction. With the observed evidence (resolved bundle targets point to the same UC prefix), the acceptance result must demonstrate actual data or permission correctness, while retaining the requirement that development tests must not mutate production data.
Incorrect Answers
A:Deploy a nonproduction copy with unique resource namespace and service identity 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 resolved bundle targets point to the same UC prefix.
C:Compare target resolution, workspace URL and catalog bindings for customer_order_changes_west could clarify the original fault, but the available evidence already establishes its scope; it is not the post-change acceptance test now requested. The customer_order_changes_west workflow still requires that development tests must not mutate production data.
D:Shared output targets defeat environment isolation. The proposed action (Use identical production destinations and hope developers avoid dangerous input at Online apparel cooperative) does not meet the requirement that development tests must not mutate production data, nor does it constitute the post-change acceptance test.