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Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineering team is setting up deployment automation. To deploy workspace assets remotely using the Databricks CLI command, they must configure it with proper authentication.
Which authentication approach will provide the highest level of security?

A) Use a service principal ID and its OAuth client secret.
B) Use a service principal and its Personal Access Token.
C) Use a service principal with OAuth token federation.
D) Use a shared user account and its OAuth client secret.


2. A junior data engineer has been asked to develop a streaming data pipeline with a grouped aggregation using DataFrame df. The pipeline needs to calculate the average humidity and average temperature for each non-overlapping five-minute interval. Incremental state information should be maintained for 10 minutes for late-arriving data.
Streaming DataFrame df has the following schema:
"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"
Code block:

Choose the response that correctly fills in the blank within the code block to complete this task.

A) await("event_time + `10 minutes'")
B) withWatermark("event_time", "10 minutes")
C) delayWrite("event_time", "10 minutes")
D) slidingWindow("event_time", "10 minutes")
E) awaitArrival("event_time", "10 minutes")


3. A data engineer is brining an existing production Databricks job under asset bundle management and wants to ensure that:
- The job's current configuration is captured as YAML, and all
referenced files are included in their bundle project.
- Future changes to the bundle's YAML will update the existing job in-
place (not create a new job)
How should the data engineer successfully move the production job under asset bundle management?

A) Manually create the YAML configuration for the job in your bundle project, ensuring all settings match the existing job. Then, run Databricks bundle deploy the bundle, which will update the existing job in your workspace.
B) Run Databricks bundle generate job --existing-job-id to generate the YAML and download referenced files. Then, run Databricks bundle deploy to deploy the bundle, which will always update the existing job automatically.
C) Export the job definition as JSON, convert it to YAML, and place it in your bundle. Then, run Databricks bundle deploy to update the existing job.
D) Run databricks bundle generate job --existing-job-id to generate the YAML and download referenced files. Then, run Databricks bundle deployment, bind to link the bundle's job resource to the existing job in Databricks.


4. Which statement describes integration testing?

A) Validates an application use case
B) Requires manual intervention
C) Validates interactions between subsystems of your application
D) Validates behavior of individual elements of your application
E) Requires an automated testing framework


5. 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?

A) Filter all records in the reviews_raw table based on the review_timestamp; batch append those records produced in the last 48 hours.
B) Reprocess all records in reviews_raw and overwrite the next table in the pipeline.
C) 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.
D) Configure a Structured Streaming read against the reviews_raw table using the trigger once execution mode to process new records as a batch job.
E) 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.


Solutions:

Question # 1
Answer: C
Question # 2
Answer: B
Question # 3
Answer: D
Question # 4
Answer: C
Question # 5
Answer: D

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