Databricks Data Engineer Associate · Free practice question 5 of 12
Triggered vs continuous pipeline mode
A Lakeflow Spark Declarative Pipeline (formerly a Delta Live Tables pipeline) at Fenmore Transit only needs its tables refreshed once every morning before business hours, and the team wants compute to shut down between refreshes. Which pipeline execution mode fits?
- A.Continuous mode
- B.Triggered mode, run on a schedule
- C.Continuous mode combined with development mode
- D.Continuous mode with a larger cluster size
Show answer and explanation
Correct answer: B. Triggered mode, run on a schedule
Why: In triggered mode, each update processes the available data and then stops, so it can be scheduled, for example from a job, and compute shuts down between runs. Continuous mode keeps the pipeline running to process new data with low latency, which adds cost when a daily refresh is enough. Development mode affects compute reuse and retries rather than how often updates run.
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