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Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer needs to productionize a new Spark application written by teammate. This application has numerous external dependencies, including libraries, and requires custom environment variables and Spark configuration parameters to be set. Which two methods will help the data engineer accomplish the task? (Choose two.)

A) Install libraries on DBFS
B) Create init scripts on DBFS.
C) Use secrets in init scripts to store configuration data
D) Use compute policies to set system properties, environment variables, and Spark configuration parameters.
E) Add libraries to compute policies

2. A table is registered with the following code:

Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders?

A) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
B) Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
C) The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
D) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
E) All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.

3. A data engineer wants to ingest a large collection of image files (JPEG and PNG) from cloud object storage into a Unity Catalog-managed table for analysis and visualization. Which two configurations and practices are recommended to incrementally ingest these images into the table? (Choose two.)

A) Use the pathGlobFilter option to select only image files (e.g., "*.jpg,*.png").
B) Use Auto Loader and set cloudFiles.format to "IMAGE".
C) Move files to a volume and read with SQL editor.
D) Use Auto Loader and set cloudFiles.format to "BINARYFILE".
E) Use Auto Loader and set cloudFiles.format to "TEXT".

4. A streaming video analytics team ingests billions of events daily into a Unity Catalog-managed Delta table video_events. Analysts run ad-hoc point-lookup queries on columns like user_id, campaign_id, and region. The team manually runs OPTIMIZE video_events ZORDER BY (user_id, campaign_id, region), but still sees poor performance on recent data and dislikes the operational overhead. The team wants a hands-off way to keep hot columns co-located as query patterns evolve. Which Delta capability should the team leverage on video_events?

A) Schedule OPTIMIZE/ZORDER to run after each job to improve recent file performance.
B) Enable auto-compaction (optimizeWrite and autoCompact).
C) Enable Delta caching.
D) Utilize Liquid Clustering (CLUSTER BY AUTO) and Predictive Optimization.

5. The data engineer team is configuring environment for development testing, and production before beginning migration on a new data pipeline. The team requires extensive testing on both the code and data resulting from code execution, and the team want to develop and test against similar production data as possible.
A junior data engineer suggests that production data can be mounted to the development testing environments, allowing pre production code to execute against production data. Because all users have Admin privileges in the development environment, the junior data engineer has offered to configure permissions and mount this data for the team.
Which statement captures best practices for this situation?

A) All developer, testing and production code and data should exist in a single unified workspace; creating separate environments for testing and development further reduces risks.
B) Because access to production data will always be verified using passthrough credentials it is safe to mount data to any Databricks development environment.
C) In environments where interactive code will be executed, production data should only be accessible with read permissions; creating isolated databases for each environment further reduces risks.
D) Because delta Lake versions all data and supports time travel, it is not possible for user error or malicious actors to permanently delete production data, as such it is generally safe to mount production data anywhere.

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