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Databricks Certified Data Engineer Professional Sample Questions:

1. Two of the most common data locations on Databricks are the DBFS root storage and external object storage mounted with dbutils.fs.mount().
Which of the following statements is correct?

A) The DBFS root stores files in ephemeral block volumes attached to the driver, while mounted directories will always persist saved data to external storage between sessions.
B) By default, both the DBFS root and mounted data sources are only accessible to workspace administrators.
C) The DBFS root is the most secure location to store data, because mounted storage volumes must have full public read and write permissions.
D) DBFS is a file system protocol that allows users to interact with files stored in object storage using syntax and guarantees similar to Unix file systems.
E) Neither the DBFS root nor mounted storage can be accessed when using %sh in a Databricks notebook.

2. A junior data engineer has manually configured a series of jobs using the Databricks Jobs UI.
Upon reviewing their work, the engineer realizes that they are listed as the "Owner" for each job.
They attempt to transfer "Owner" privileges to the "DevOps" group, but cannot successfully accomplish this task.
Which statement explains what is preventing this privilege transfer?
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

A) A user can only transfer job ownership to a group if they are also a member of that group.
B) Databricks jobs must have exactly one owner; "Owner" privileges cannot be assigned to a group.
C) Only workspace administrators can grant "Owner" privileges to a group.
D) The creator of a Databricks job will always have "Owner" privileges; this configuration cannot be changed.
E) Other than the default "admins" group, only individual users can be granted privileges on jobs.

3. A nightly batch job is configured to ingest all data files from a cloud object storage container where records are stored in a nested directory structure YYYY/MM/DD. The data for each date represents all records that were processed by the source system on that date, noting that some records may be delayed as they await moderator approval. Each entry represents a user review of a product and has the following schema:
user_id STRING, review_id BIGINT, product_id BIGINT, review_timestamp TIMESTAMP, review_text STRING The ingestion job is configured to append all data for the previous date to a target table reviews_raw with an identical schema to the source system. The next step in the pipeline is a batch write to propagate all new records inserted into reviews_raw to a table where data is fully deduplicated, validated, and enriched.
Which solution minimizes the compute costs to propagate this batch of data?
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A) Perform a batch read on the reviews_raw table and perform an insert-only merge using the natural composite key user_id, review_id, product_id, review_timestamp.
B) Configure a Structured Streaming read against the reviews_raw table using the trigger once execution mode to process new records as a batch job.
C) Use Delta Lake version history to get the difference between the latest version of reviews_raw and one version prior, then write these records to the next table.
D) Reprocess all records in reviews_raw and overwrite the next table in the pipeline.
E) Filter all records in the reviews_raw table based on the review_timestamp; batch append those records produced in the last 48 hours.

4. Incorporating unit tests into a PySpark application requires upfront attention to the design of your jobs, or a potentially significant refactoring of existing code.
Which statement describes a main benefit that offset this additional effort?

A) Validates a complete use case of your application
B) Ensures that all steps interact correctly to achieve the desired end result
C) Troubleshooting is easier since all steps are isolated and tested individually
D) Improves the quality of your data
E) Yields faster deployment and execution times

5. The view updates represents an incremental batch of all newly ingested data to be inserted or Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from 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 0 table; all writes are append only with no changes to existing values.
B) 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.
C) The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
D) The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.

Solutions: