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Databricks Certified Data Engineer Professional Exam Sample Questions (Q110-Q115):

NEW QUESTION # 110
The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.
Which approach will ensure that this requirement is met?

A. When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.
B. When data is saved to a table, make sure that a full file path is specified alongside the Delta format.
C. When the workspace is being configured, make sure that external cloud object storage has been mounted.
D. When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.
E. When a database is being created, make sure that the LOCATION keyword is used.

Answer: A

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from To create an external or unmanaged Delta Lake table, you need to use the EXTERNAL keyword in the CREATE TABLE statement. This indicates that the table is not managed by the catalog and the data files are not deleted when the table is dropped. You also need to provide a LOCATION clause to specify the path where the data files are stored.
For example:
CREATE EXTERNAL TABLE events ( date DATE, eventId STRING, eventType STRING, data STRING) USING DELTA LOCATION `/mnt/delta/events'; This creates an external Delta Lake table named events that references the data files in the
`/mnt/delta/events' path. If you drop this table, the data files will remain intact and you can recreate the table with the same statement.

NEW QUESTION # 111
Which distribution does Databricks support for installing custom Python code packages?

A. jars
B. CRAN
C. CRAM
D. sbt
E. nom
F. Wheels

Answer: E

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Explanation:
https://learn.microsoft.com/en-us/azure/databricks/workflows/jobs/how-to/use-python-wheels-in- workflows

NEW QUESTION # 112
A junior data engineer is migrating a workload from a relational database system to the Databricks Lakehouse. The source system uses a star schema, leveraging foreign key constrains and multi-table inserts to validate records on write.
Which consideration will impact the decisions made by the engineer while migrating this workload?

A. Databricks only allows foreign key constraints on hashed identifiers, which avoid collisions in highly-parallel writes.
B. Committing to multiple tables simultaneously requires taking out multiple table locks and can lead to a state of deadlock.
C. Databricks supports Spark SQL and JDBC; all logic can be directly migrated from the source system without refactoring.
D. All Delta Lake transactions are ACID compliance against a single table, and Databricks does not enforce foreign key constraints.
E. Foreign keys must reference a primary key field; multi-table inserts must leverage Delta Lake's upsert functionality.

Answer: D

Explanation:
In Databricks and Delta Lake, transactions are indeed ACID-compliant, but this compliance is limited to single table transactions. Delta Lake does not inherently enforce foreign key constraints, which are a staple in relational database systems for maintaining referential integrity between tables. This means that when migrating workloads from a relational database system to Databricks Lakehouse, engineers need to reconsider how to maintain data integrity and relationships that were previously enforced by foreign key constraints. Unlike traditional relational databases where foreign key constraints help in maintaining the consistency across tables, in Databricks Lakehouse, the data engineer has to manage data consistency and integrity at the application level or through careful design of ETL processes.

NEW QUESTION # 113
A table named user_ltv is being used to create a view that will be used by data analysts on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
The user_ltv table has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:

An analyst who is not a member of the auditing group executes the following query:
SELECT * FROM user_ltv_no_minors
Which statement describes the results returned by this query?

A. All values for the age column will be returned as null values, all other columns will be returned with the values in user_ltv.
B. All columns will be displayed normally for those records that have an age greater than 17; records not meeting this condition will be omitted.
C. All columns will be displayed normally for those records that have an age greater than 18; records not meeting this condition will be omitted.
D. All records from all columns will be displayed with the values in user_ltv.
E. All age values less than 18 will be returned as null values all other columns will be returned with the values in user_ltv.

Answer: C

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Explanation:
Given the CASE statement in the view definition, the result set for a user not in the auditing group would be constrained by the ELSE condition, which filters out records based on age. Therefore, the view will return all columns normally for records with an age greater than 18, as users who are not in the auditing group will not satisfy the is_member('auditing') condition. Records not meeting the age > 18 condition will not be displayed.

NEW QUESTION # 114
In order to facilitate near real-time workloads, a data engineer is creating a helper function to Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from leverage the schema detection and evolution functionality of Databricks Auto Loader. The desired function will automatically detect the schema of the source directly, incrementally process JSON files as they arrive in a source directory, and automatically evolve the schema of the table when new fields are detected.
The function is displayed below with a blank:

Which response correctly fills in the blank to meet the specified requirements?

A.
B.
C. Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
D.
E.

Answer: B

Explanation:
https://docs.databricks.com/en/ingestion/auto-loader/schema.html

NEW QUESTION # 115
......

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