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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Databricks Lakehouse Platform	24%	- Delta Lake - Unity Catalog - Lakehouse Architecture - Data Management
Topic 2: Data Modeling and Storage	20%	- Storage Optimization - File Formats - Data Modeling
Topic 3: Monitoring and Troubleshooting	16%	- Monitoring - Performance Optimization - Troubleshooting
Topic 4: Data Processing	28%	- ETL Pipelines - Structured Streaming - Data Transformation - Spark SQL
Topic 5: Data Quality and Governance	12%	- Data Quality - Data Lineage - Governance

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q173-Q178):

NEW QUESTION # 173
What statement is true regarding the retention of job run history?

A. It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3
B. It is retained for 60 days, during which you can export notebook run results to HTML
C. It is retained until you export or delete job run logs
D. It is retained for 60 days, after which logs are archived
E. It is retained for 90 days or until the run-id is re-used through custom run configuration

Answer: B

Explanation:
https://docs.databricks.com/en/workflows/jobs/monitor-job-runs.html

NEW QUESTION # 174
A junior data engineer has manually configured a series of jobs using the Databricks Jobs UI.
Upon reviewing their work, the engineer realizes that they are listed as the "Owner" for each job.
They attempt to transfer "Owner" privileges to the "DevOps" group, but cannot successfully accomplish this task.
Which statement explains what is preventing this privilege transfer?

A. Databricks jobs must have exactly one owner; "Owner" privileges cannot be assigned to a group.
B. Other than the default "admins" group, only individual users can be granted privileges on jobs.
C. The creator of a Databricks job will always have "Owner" privileges; this configuration cannot be changed.
D. Only workspace administrators can grant "Owner" privileges to a group.
E. A user can only transfer job ownership to a group if they are also a member of that group.

Answer: A

Explanation:
A job cannot have more than one owner. A job cannot have a group as an owner.

NEW QUESTION # 175
While reviewing a query's execution in the Databricks Query Profiler, a data engineer observes that the Top Operators panel shows a Sort operator with high Time Spent and Memory Peak metrics. The Spark UI also reports frequent data spilling. How should the data engineer address this issue?

A. Repartition the DataFrame to a single partition before sorting.
B. Switch to a broadcast join to reduce memory usage.
C. Convert the sort operation to a filter operation.
D. Increase the number of shuffle partitions to better distribute data.

Answer: D

Explanation:
Increasing the number of shuffle partitions distributes the data across more tasks, reducing per- task memory pressure during the sort operation. This helps mitigate spilling by lowering memory peak usage per task and improves overall sort performance in large-scale distributed queries.

NEW QUESTION # 176
The DevOps team has configured a production workload as a collection of notebooks scheduled to run daily using the Jobs Ul. A new data engineering hire is onboarding to the team and has requested access to one of these notebooks to review the production logic. What are the maximum notebook permissions that can be granted to the user without allowing accidental changes to production code or data?

A. Can manage
B. Can edit
C. Can Read
D. Can run

Answer: C

Explanation:
Granting a user 'Can Read' permissions on a notebook within Databricks allows them to view the notebook's content without the ability to execute or edit it. This level of permission ensures that the new team member can review the production logic for learning or auditing purposes without the risk of altering the notebook's code or affecting production data and workflows. This approach aligns with best practices for maintaining security and integrity in production environments, where strict access controls are essential to prevent unintended modifications.

NEW QUESTION # 177
A Delta Lake table was created with the below query:

Consider the following query:
DROP TABLE prod.sales_by_store
If this statement is executed by a workspace admin, which result will occur?

A. The table will be removed from the catalog but the data will remain in storage.
B. Data will be marked as deleted but still recoverable with Time Travel.
C. Nothing will occur until a COMMIT command is executed.
D. The table will be removed from the catalog and the data will be deleted.
E. An error will occur because Delta Lake prevents the deletion of production data.

Answer: D

Explanation:
When a table is dropped in Delta Lake, the table is removed from the catalog and the data is deleted. This is because Delta Lake is a transactional storage layer that provides ACID guarantees. When a table is dropped, the transaction log is updated to reflect the deletion of the table and the data is deleted from the underlying storage.

NEW QUESTION # 178
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