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Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer is working in an interactive notebook with many transformations before outputting the result from display(df.collect() ). The notebook includes wide transformations and a cross join.
The data engineer is getting the following error: "The spark driver has stopped unexpectedly and is restarting. Your notebook will be automatically reattached." Which action should the data engineer take?

A) Run the notebook on a single node cluster to keep driver from falling.
B) Rewrite their code to avoid putting memory pressure on the driver node.
C) Look at the compute metrics UI to see if the executors have higher than 90% memory utilization.
D) Check into the Spark UI to see how many jobs are assigned to each stage as they are employing fewer executors.

2. A company wants to implement Lakehouse Federation across multiple data sources but is concerned about data consistency and ensuring that all teams access the same authoritative version of their data. Which statement is applicable for Lakehouse Federations to maintain data consistency?

A) Federation implements change data capture (CDC) from all sources.
B) Federation creates local copies that must be manually refreshed.
C) Federation provides read-only access that reflects the current state of source systems.
D) A separate data synchronization service must be deployed.

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

4. A data engineer wants to refactor the following DLT code, which includes multiple table definitions with very similar code.

In an attempt to programmatically create these tables using a parameterized table definition, the data engineer writes the following code.

The pipeline runs an update with this refactored code, but generates a different DAG showing incorrect configuration values for these tables.
How can the data engineer fix this?

A) Wrap the for loop inside another table definition, using generalized names and properties to replace with those from the inner table definition.
B) Move the table definition into a separate function, and make calls to this function using different input parameters inside the for loop.
C) Convert the list of configuration values to a dictionary of table settings, using table names as keys.
D) Load the configuration values for these tables from a separate file, located at a path provided by a pipeline parameter.

5. A platform engineer needs to report the resource consumption, categorized by SKU tier, across all workspaces. The engineer decides to use the system.billing.usage system table to create a query. Which SQL query will accurately return the daily usage by product?

A)

B)

C)

D)

Solutions: