Answer-first summary for fast verification
Answer: Scheduled Workflows can reduce resource consumption and expense since the cluster runs only long enough to execute the pipeline.
Scheduled Workflows in Databricks are designed to run at specified intervals, and the associated clusters are started only when the workflow is triggered. This approach minimizes resource consumption and costs because the cluster terminates after the job completes. Option A is incorrect because always-running clusters are not required for scheduled workflows. Option B describes streaming/continuous processing, not scheduled batch workflows. Option D incorrectly implies workflows run continuously, which applies to streaming jobs, not scheduled ones.
Author: LeetQuiz Editorial Team
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What approach should a Data Engineer use to guarantee that Workflows are triggered according to their scheduled timetable?
A
Scheduled Workflows require an always-running cluster, which is more expensive but reduces processing latency.
B
Scheduled Workflows process data as it arrives at configured sources.
C
Scheduled Workflows can reduce resource consumption and expense since the cluster runs only long enough to execute the pipeline.
D
Scheduled Workflows run continuously until manually stopped.