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Reliable Databricks-Certified-Professional-Data-Engineer Exam Prep & Examcollection Databricks-Certified-Professional-Data-Engineer Free Dumps

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By earning the Databricks Certified Professional Data Engineer certification, data professionals can demonstrate their expertise in using the Databricks platform to build and manage data solutions. Databricks Certified Professional Data Engineer Exam certification can help individuals advance their careers, as well as provide organizations with a way to identify and hire qualified data professionals who can help them achieve their data-driven goals.

Databricks Certified Professional Data Engineer (Databricks-Certified-Professional-Data-Engineer) certification exam is designed for professionals who want to demonstrate their expertise in using Databricks to manage big data and create data pipelines. Databricks Certified Professional Data Engineer Exam certification exam is ideal for data engineers, data architects, data scientists, and other professionals who work with big data and want to validate their skills in using Databricks to build data pipelines.

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The Databricks Databricks-Certified-Professional-Data-Engineer Exam covers a wide range of topics, including data architecture, data modeling, data integration, data processing, and data analytics. Databricks-Certified-Professional-Data-Engineer exam consists of both theoretical and practical components, which test the candidate's ability to apply their knowledge to real-world scenarios. The practical component requires candidates to complete a series of hands-on exercises using Databricks notebooks, which are used to build, test, and optimize data pipelines.

Databricks Certified Professional Data Engineer Exam Sample Questions (Q41-Q46):

NEW QUESTION # 41
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. No; files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files.
  • E. Yes; the Delta cache immediately updates to reflect the latest data files recorded to disk.

Answer: D

Explanation:
The code uses the DELETE FROM command to delete records from the users table that match a condition based on a join with another table called delete_requests, which contains all users that have requested deletion.
The DELETE FROM command deletes records from a Delta Lake table by creating a new version of the table that does not contain the deleted records. However, this does not guarantee that the records to be deleted are no longer accessible, because Delta Lake supports time travel, which allows querying previous versions of the table using a timestamp or version number. Therefore, files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files from physical storage.
Verified References: [Databricks Certified Data Engineer Professional], under "Delta Lake" section; Databricks Documentation, under "Delete from a table" section; Databricks Documentation, under "Remove files no longer referenced by a Delta table" section.


NEW QUESTION # 42
You have accidentally deleted records from a table called transactions, what is the easiest way to restore the records deleted or the previous state of the table? Prior to deleting the version of the table is 3 and after delete the version of the table is 4.

  • A. COPY OVERWRITE transactions from VERSION as of 3
  • B. 1.INSERT INTO OVERWRITE transactions
    2.SELECT * FROM transactions VERSION AS OF 4
    3.INTERSECT
    4.SELECT * FROM transactions
  • C. RESTORE TABLE transactions TO VERSION as of 3
    C .
    1.INSERT INTO OVERWRITE transactions
    2.SELECT * FROM transactions VERSION AS OF 3
    3.MINUS
    4.SELECT * FROM transactions
  • D. RESTORE TABLE transactions FROM VERSION as of 4

Answer: C

Explanation:
Explanation
RESTORE (Databricks SQL) | Databricks on AWS
1.RESTORE [TABLE] table_name [TO] time_travel_version
Time travel supports using timestamp or version number
1.time_travel_version
2. { TIMESTAMP AS OF timestamp_expression |
3. VERSION AS OF version }
*timestamp_expression can be any one of:
*'2018-10-18T22:15:12.013Z', that is, a string that can be cast to a timestamp
*cast('2018-10-18 13:36:32 CEST' as timestamp)
*'2018-10-18', that is, a date string
*current_timestamp() - interval 12 hours
*date_sub(current_date(), 1)
*Any other expression that is or can be cast to a timestamp


NEW QUESTION # 43
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 have full permissions on the prod database and can also assign permissions to other users or groups.
  • B. Group members are able to query and modify all tables and views in the prod database, but cannot create new tables or views.
  • C. Group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database.
  • D. Group members are able to create, query, and modify all tables and views in the prod database, but cannot define custom functions.
  • E. 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.

Answer: C

Explanation:
Explanation
The GRANT USAGE ON DATABASE prod TO eng command grants the eng group the permission to use the prod database, which means they can list and access the tables and views in the database. The GRANT SELECT ON DATABASE prod TO eng command grants the eng group the permission to select data from the tables and views in the prod database, which means they can query the data using SQL or DataFrame API.
However, these commands do not grant the eng group any other permissions, such as creating, modifying, or deleting tables and views, or defining custom functions. Therefore, the eng group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database. References:
Grant privileges on a database:
https://docs.databricks.com/en/security/auth-authz/table-acls/grant-privileges-database.html Privileges you can grant on Hive metastore objects:
https://docs.databricks.com/en/security/auth-authz/table-acls/privileges.html


NEW QUESTION # 44
In order to use Unity catalog features, which of the following steps needs to be taken on man-aged/external tables in the Databricks workspace?

  • A. Migrate/upgrade objects in workspace managed/external tables/view to unity catalog
  • B. Enable unity catalog feature in workspace settings
  • C. Upgrade to DBR version 15.0
  • D. Copy data from workspace to unity catalog
  • E. Upgrade workspace to Unity catalog

Answer: A

Explanation:
Explanation
Upgrade tables and views to Unity Catalog - Azure Databricks | Microsoft Docs Managed table: Upgrade a managed to Unity Catalog External table: Upgrade an external table to Unity Catalog


NEW QUESTION # 45
Which statement regarding spark configuration on the Databricks platform is true?

  • A. The Databricks REST API can be used to modify the Spark configuration properties for an interactive cluster without interrupting jobs.
  • B. Spark configuration properties set for an interactive cluster with the Clusters UI will impact all notebooks attached to that cluster.
  • C. When the same spar configuration property is set for an interactive to the same interactive cluster.
  • D. Spark configuration set within an notebook will affect all SparkSession attached to the same interactive cluster

Answer: B

Explanation:
When Spark configuration properties are set for an interactive cluster using the Clusters UI in Databricks, those configurations are applied at the cluster level. This means that all notebooks attached to that cluster will inherit and be affected by these configurations. This approach ensures consistency across all executions within that cluster, as the Spark configuration properties dictate aspects such as memory allocation, number of executors, and other vital execution parameters. This centralized configuration management helps maintain standardized execution environments across different notebooks, aiding in debugging and performance optimization.
Reference:
Databricks documentation on configuring clusters: https://docs.databricks.com/clusters/configure.html


NEW QUESTION # 46
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