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Databricks Certified Data Engineer Professional Sample Questions:
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 impression led to monitizable clicks.
Which solution would improve the performance?
A) 
B) 
C) 
D) 
2. In order to prevent accidental commits to production data, a senior data engineer has instituted a policy that all development work will reference clones of Delta Lake tables. After testing both deep and shallow clone, development tables are created using shallow clone. A few weeks after initial table creation, the cloned versions of several tables implemented as Type 1 Slowly Changing Dimension (SCD) stop working. The transaction logs for the source tables show that vacuum was run the day before.
Why are the cloned tables no longer working?
A) Because Type 1 changes overwrite existing records, Delta Lake cannot guarantee data consistency for cloned tables.
B) Running vacuum automatically invalidates any shallow clones of a table; deep clone should always be used when a cloned table will be repeatedly queried.
C) The metadata created by the clone operation is referencing data files that were purged as invalid by the vacuum command
D) Tables created with SHALLOW CLONE are automatically deleted after their default retention threshold of 7 days.
E) The data files compacted by vacuum are not tracked by the cloned metadata; running refresh on the cloned table will pull in recent changes.
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 until you export or delete job run logs
C) It is retained for 60 days, during which you can export notebook run results to HTML
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. In a Databricks Asset Bundle project, in the file resources/app.yml, the data engineer would like to deploy a Databricks Apps databricks_app_deployed and Volume volume_deployed and grant the Service Principal behind Databricks Apps permissions to READ and WRITE to the Volume.
How should the data engineer achieve the deployment?
A) 
B) 
C) 
D) 
5. 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?
A) Databricks jobs must have exactly one owner; "Owner" privileges cannot be assigned to a group.
B) The creator of a Databricks job will always have "Owner" privileges; this configuration cannot be changed.
C) Only workspace administrators can grant "Owner" privileges to a group.
D) A user can only transfer job ownership to a group if they are also a member of that group.
E) Other than the default "admins" group, only individual users can be granted privileges on jobs.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: A |
By Chester
