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

Databricks Certified Data Engineer Professional Sample Questions:

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

2. A data engineer is attempting to execute the following PySpark code:
df = spark.read.table("sales")
result = df.groupBy("region").agg(sum("revenue"))
However, upon inspecting the execution plan and profiling the Spark job, they observe excessive data shuffling during the aggregation phase.
Which technique should be applied to reduce shuffling during the groupBy aggregation operation?

A) Use broadcast join.
B) Caching the DataFrame df.
C) Use coalesce() after the aggregation.
D) Repartition by region before aggregation.

3. A developer has successfully configured their credentials for Databricks Repos and cloned a remote Git repository. They do not have privileges to make changes to the main branch, which is the only branch currently visible in their workspace. Which approach allows this user to share their code updates without the risk of overwriting the work of their teammates?

A) Use repos to create a fork of the remote repository commit all changes and make a pull request on the source repository
B) Use Repos to merge all differences and make a pull request back to the remote repository.
C) Use Repos to create a new branch commit all changes and push changes to the remote Git repertory.
D) Use repos to merge all difference and make a pull request back to the remote repository.
E) Use Repos to pull changes from the remote Git repository; commit and push changes to a branch that appeared as changes were pulled.

4. The data architect has decided that once data has been ingested from external sources into the Databricks Lakehouse, table access controls will be leveraged to manage permissions for all production tables and views.
The following logic was executed to grant privileges for interactive queries on a production database to the core engineering group.
GRANT USAGE ON DATABASE prod TO eng;
GRANT SELECT ON DATABASE prod TO eng;
Assuming these are the only privileges that have been granted to the eng group and that these users are not workspace administrators, which statement describes their privileges?

A) Group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database.
B) Group members have full permissions on the prod database and can also assign permissions to other users or groups.
C) Group members are able to query and modify all tables and views in the prod database, but cannot create new tables or views.
D) Group members are able to list all tables in the prod database but are not able to see the results of any queries on those tables.
E) Group members are able to create, query, and modify all tables and views in the prod database, but cannot define custom functions.

5. The data engineer team is configuring environment for development testing, and production before beginning migration on a new data pipeline. The team requires extensive testing on both the code and data resulting from code execution, and the team want to develop and test against similar production data as possible.
A junior data engineer suggests that production data can be mounted to the development testing environments, allowing pre production code to execute against production data. Because all users have Admin privileges in the development environment, the junior data engineer has offered to configure permissions and mount this data for the team.
Which statement captures best practices for this situation?

A) Because delta Lake versions all data and supports time travel, it is not possible for user error or malicious actors to permanently delete production data, as such it is generally safe to mount production data anywhere.
B) All developer, testing and production code and data should exist in a single unified workspace; creating separate environments for testing and development further reduces risks.
C) In environments where interactive code will be executed, production data should only be accessible with read permissions; creating isolated databases for each environment further reduces risks.
D) Because access to production data will always be verified using passthrough credentials it is safe to mount data to any Databricks development environment.

Solutions: