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Databricks Certified Data Engineer Professional Sample Questions:

1. In order to prevent accidental commits to production data, a senior data engineer has instituted a policy that all development work will reference clones of Delta Lake tables. After testing both deep and shallow clone, development tables are created using shallow clone. A few weeks after initial table creation, the cloned versions of several tables implemented as Type 1 Slowly Changing Dimension (SCD) stop working. The transaction logs for the source tables show that vacuum was run the day before.
Why are the cloned tables no longer working?

A) The metadata created by the clone operation is referencing data files that were purged as invalid by the vacuum command
B) Because Type 1 changes overwrite existing records, Delta Lake cannot guarantee data consistency for cloned tables.
C) The data files compacted by vacuum are not tracked by the cloned metadata; running refresh on the cloned table will pull in recent changes.
D) Running vacuum automatically invalidates any shallow clones of a table; deep clone should always be used when a cloned table will be repeatedly queried.
E) Tables created with SHALLOW CLONE are automatically deleted after their default retention threshold of 7 days.

2. A data engineer, User A, has promoted a new pipeline to production by using the REST API to programmatically create several jobs. A DevOps engineer, User B, has configured an external orchestration tool to trigger job runs through the REST API. Both users authorized the REST API calls using their personal access tokens.
Which statement describes the contents of the workspace audit logs concerning these events?

A) Because User A created the jobs, their identity will be associated with both the job creation events and the job run events.
B) Because User B last configured the jobs, their identity will be associated with both the job creation events and the job run events.
C) Because the REST API was used for job creation and triggering runs, a Service Principal will be automatically used to identity these events.
D) Because these events are managed separately, User A will have their identity associated with the job creation events and User B will have their identity associated with the job run events.
E) Because the REST API was used for job creation and triggering runs, user identity will not be captured in the audit logs.

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

4. 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)

5. The view updates represents an incremental batch of all newly ingested data to be inserted or updated in the customers table.
The following logic is used to process these records.
MERGE INTO customers
USING (
SELECT updates.customer_id as merge_ey, updates .*
FROM updates
UNION ALL
SELECT NULL as merge_key, updates .*
FROM updates JOIN customers
ON updates.customer_id = customers.customer_id
WHERE customers.current = true AND updates.address <> customers.address ) staged_updates ON customers.customer_id = mergekey WHEN MATCHED AND customers. current = true AND customers.address <> staged_updates.address THEN UPDATE SET current = false, end_date = staged_updates.effective_date WHEN NOT MATCHED THEN INSERT (customer_id, address, current, effective_date, end_date) VALUES (staged_updates.customer_id, staged_updates.address, true, staged_updates.effective_date, null) Which statement describes this implementation?

A) The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
B) The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.
C) The customers table is implemented as a Type 2 table; old values are maintained but marked as no longer current and new values are inserted.
D) The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.

Solutions: