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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

1. Spill occurs as a result of executing various wide transformations. However, diagnosing spill requires one to proactively look for key indicators.
Where in the Spark UI are two of the primary indicators that a partition is spilling to disk?

A) Executor's detail screen and Executor's log files
B) Stage's detail screen and Query's detail screen
C) Driver's and Executor's log files
D) Stage's detail screen and Executor's log files
E) Query's detail screen and Job's detail screen

2. A Delta Lake table in the Lakehouse named customer_parsams is used in churn prediction by the machine learning team. The table contains information about customers derived from a number of upstream sources. Currently, the data engineering team populates this table nightly by overwriting the table with the current valid values derived from upstream data sources.
Immediately after each update succeeds, the data engineer team would like to determine the difference between the new version and the previous of the table. Given the current implementation, which method can be used?

A) Execute a query to calculate the difference between the new version and the previous version using Delta Lake's built-in versioning and time travel functionality.
B) Parse the Delta Lake transaction log to identify all newly written data files.
C) Parse the Spark event logs to identify those rows that were updated, inserted, or deleted.
D) Execute DESCRIBE HISTORY customer_churn_params to obtain the full operation metrics for the update, including a log of all records that have been added or modified.

3. What statement is true regarding the retention of job run history?

A) It is retained for 90 days or until the run-id is re-used through custom run configuration
B) It is retained for 60 days, during which you can export notebook run results to HTML
C) It is retained until you export or delete job run logs
D) It is retained for 60 days, after which logs are archived
E) It is retained for 30 days, during which time you can deliver job run logs to DBFS or S3

4. A data engineer is implementing Unity Catalog governance for a multi-team environment. Data scientists need interactive clusters for basic data exploration tasks, while automated ETL jobs require dedicated processing. How should the data engineer configure cluster isolation policies to enforce least privilege and ensure Unity Catalog compliance?

A) Create compute policies with STANDARD access mode for interactive workloads and DEDICATED access mode for automated jobs.
B) Allow all users to create any cluster type and rely on manual configuration to enable Unity Catalog access modes.
C) Use only DEDICATED access mode for both interactive workloads and automated jobs to maximize security isolation.
D) Configure all clusters with NO ISOLATION_SHARED access mode since Unity Catalog works with any cluster configuration.

5. A data engineer is building a Lakeflow Declarative Pipelines pipeline to process healthcare claims data. A metadata JSON file defines data quality rules for multiple tables, including:
{
"claims": [
{"name": "valid_patient_id", "constraint": "patient_id IS NOT NULL"},
{"name": "non_negative_amount", "constraint": "claim_amount >= 0"}
]
}
The pipeline must dynamically apply these rules to the claims table without hardcoding the rules.
How should the data engineer achieve this?

A) Load the JSON metadata, loop through its entries, and apply expectations using dlt.expect_all.
B) Use a SQL CONSTRAINT block referencing the JSON file path.
C) Reference each expectation with @dlt.expect decorators in the table declaration.
D) Invoke an external API to validate records against the metadata rules.

Solutions: