Databricks Certified Data Engineer Professional - Certified-Data-Engineer-Professional

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Databricks Certified-Data-Engineer-Professional 試験シラバストピック:

Databricks Certified Data Engineer Professional 認定 Certified-Data-Engineer-Professional 試験問題：

1. A data engineer wants to join a stream of advertisement impressions (when an ad was shown) with another stream of user clicks on advertisements to correlate when impressions led to monetizable clicks.
In the code below, Impressions is a streaming DataFrame with a watermark ("event_time", "10 minutes")

The data engineer notices the query slowing down significantly.
Which solution would improve the performance?

A) Joining on event time constraint: clickTime >= impressionTime AND clickTime <= impressionTime interval 1 hour
B) Joining on event time constraint: clickTime + 3 hours < impressionTime - 2 hours
C) Joining on event time constraint: clickTime >= impressionTime - interval 3 hours and removing watermarks
D) Joining on event time constraint: clickTime == impressionTime using a leftOuter join

2. A data engineer is testing a collection of mathematical functions, one of which calculates the area under a curve as described by another function.
assert(myIntegrate(lambda x: x*x, 0, 3) [0] == 9)
Which kind of the test does the above line exemplify?

A) End-to-end
B) functional
C) Unit
D) Integration
E) Manual

3. In order to facilitate near real-time workloads, a data engineer is creating a helper function to leverage the schema detection and evolution functionality of Databricks Auto Loader. The desired function will automatically detect the schema of the source directly, incrementally process JSON files as they arrive in a source directory, and automatically evolve the schema of the table when new fields are detected.
The function is displayed below with a blank:

Which response correctly fills in the blank to meet the specified requirements?

A)

B)

C)

D)

E)

4. 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.

5. The data governance team is reviewing code used for deleting records for compliance with GDPR. They note the following logic is used to delete records from the Delta Lake table named users.

Assuming that user_id is a unique identifying key and that delete_requests contains all users that have requested deletion, which statement describes whether successfully executing the above logic guarantees that the records to be deleted are no longer accessible and why?

A) Yes; the Delta cache immediately updates to reflect the latest data files recorded to disk.
B) No; files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files.
C) No; the Delta cache may return records from previous versions of the table until the cluster is restarted.
D) No; the Delta Lake delete command only provides ACID guarantees when combined with the merge into command.
E) Yes; Delta Lake ACID guarantees provide assurance that the delete command succeeded fully and permanently purged these records.

質問と回答：