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

Databricks Certified Data Engineer Professional Sample Questions:

Question 1

Which REST API call can be used to review the notebooks configured to run as tasks in a multi- task job?

A. /jobs/get
B. /jobs/list
C. /jobs/runs/get
D. /jobs/runs/list
E. /jobs/runs/get-output

Question 2

The data governance team is reviewing code used for deleting records for compliance with GDPR. They note the following logic is used to delete records from the Delta Lake table named users.

Assuming that user_id is a unique identifying key and that delete_requests contains all users that have requested deletion, which statement describes whether successfully executing the above logic guarantees that the records to be deleted are no longer accessible and why?

A. Yes; the Delta cache immediately updates to reflect the latest data files recorded to disk.
B. No; the Delta Lake delete command only provides ACID guarantees when combined with the merge into command.
C. Yes; Delta Lake ACID guarantees provide assurance that the delete command succeeded fully and permanently purged these records.
D. No; files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files.
E. No; the Delta cache may return records from previous versions of the table until the cluster is restarted.

Question 3

A data engineer is working on a Databricks notebook that requires several third-party Python libraries. Some of these are available on PyPI, while others are custom-developed and stored as local.wheel (.whl) and source (.tar.gz) files in an S3 bucket. The goal is to ensure all dependencies are installed and correctly available across multiple jobs running on any automated cluster in a Unity Catalog-enabled workspace. The engineer needs to install the required dependencies in a way that ensures a consistent environment setup across interactive notebooks and jobs and complies with workspace security policies (no internet access). Which approach should the engineer use to install and manage these dependencies while also ensuring reproducibility and compliance?

A. Use an init script on the cluster to install all dependencies using pip, referencing the local file system.
B. Install all dependencies manually in the driver node of an interactive cluster, then export the environment and reimport on job clusters using %conda.
C. Use %pip install in every notebook and job to install packages directly from PyPl and custom S3 paths.
D. Create a Python wheel file for the entire project, upload it to the Databricks Workspace Files or Volumes, and install it using a Cluster Library or pip install in a requirements.txt declared within a Databricks Asset Bundle.

Question 4

A junior data engineer on your team has implemented the following code block.

The view new_events contains a batch of records with the same schema as the events Delta table. The event_id field serves as a unique key for this table.
When this query is executed, what will happen with new records that have the same event_id as an existing record?

A. They are inserted.
B. They are merged.
C. They are deleted.
D. They are updated.
E. They are ignored.

Question 5

Which statement describes the correct use of pyspark.sql.functions.broadcast?

A. It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.
B. It marks a column as small enough to store in memory on all executors, allowing a broadcast join.
C. It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.
D. It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.
E. It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.

Solutions: