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

Databricks Certified Data Engineer Professional Sample Questions:

1. Which statement describes Delta Lake Auto Compaction?

A) An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 128 MB.
B) An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an optimize job is executed toward a default of 1 GB.
C) Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.
D) Data is queued in a messaging bus instead of committing data directly to memory; all data is committed from the messaging bus in one batch once the job is complete.
E) Before a Jobs cluster terminates, optimize is executed on all tables modified during the most recent job.

2. A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch named dev-2.3.9 is not available from the branch selection dropdown.
Which approach will allow this developer to review the current logic for this notebook?

A) Use Repos to pull changes from the remote Git repository and select the dev-2.3.9 branch.
B) Merge all changes back to the main branch in the remote Git repository and clone the repo again
C) Use Repos to merge the current branch and the dev-2.3.9 branch, then make a pull request to sync with the remote repository
D) Use Repos to checkout the dev-2.3.9 branch and auto-resolve conflicts with the current branch
E) Use Repos to make a pull request use the Databricks REST API to update the current branch to dev-2.3.9

3. The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. The recent_sensor_recordings table contains an identifying sensor_id alongside the timestamp and temperature for the most recent 5 minutes of recordings.
The below query is used to create the alert:

The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger when mean (temperature) > 120. Notifications are triggered to be sent at most every 1 minute.
If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?

A) The total average temperature across all sensors exceeded 120 on three consecutive executions of the query
B) The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query
C) The recent_sensor_recordingstable was unresponsive for three consecutive runs of the query
D) The source query failed to update properly for three consecutive minutes and then restarted
E) The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query

4. A large company seeks to implement a near real-time solution involving hundreds of pipelines with parallel updates of many tables with extremely high volume and high velocity data.
Which of the following solutions would you implement to achieve this requirement?

A) Isolate Delta Lake tables in their own storage containers to avoid API limits imposed by cloud vendors.
B) Partition ingestion tables by a small time duration to allow for many data files to be written in parallel.
C) Store all tables in a single database to ensure that the Databricks Catalyst Metastore can load balance overall throughput.
D) Use Databricks High Concurrency clusters, which leverage optimized cloud storage connections to maximize data throughput.
E) Configure Databricks to save all data to attached SSD volumes instead of object storage, increasing file I/O significantly.

5. A data engineer is masking a column containing email addresses. The goal is to produce output strings of identical length for all rows, while generating different outputs for different email values.
Which SQL function should be used to achieve this?

A) sha2(email, 0)
B) sha1(email)
C) hash(email)
D) mask(email, '?')

Solutions: