Databricks Certified Data Engineer Professional — Question 109

A DLT pipeline includes the following streaming tables:

• raw_iot ingests raw device measurement data from a heart rate tracking device.
• bpm_stats incrementally computes user statistics based on BPM measurements from raw_iot.

How can the data engineer configure this pipeline to be able to retain manually deleted or updated records in the raw_iot table, while recomputing the downstream table bpm_stats table when a pipeline update is run?

Answer options

• A. Set the pipelines.reset.allowed property to false on raw_iot
• B. Set the skipChangeCommits flag to true on raw_iot
• C. Set the pipelines.reset.allowed property to false on bpm_stats
• D. Set the skipChangeCommits flag to true on bpm_stats

Correct answer: A

Explanation

The correct answer, A, allows the raw_iot table to preserve records that have been manually deleted or updated by preventing the pipeline from resetting its state. Options B and D do not address the requirement of retaining deleted or modified records, as they relate to the change commit behavior rather than the reset property. Option C is also incorrect because it focuses on the downstream table bpm_stats, which is not where the retention is needed.