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You have an Azure Databricks workspace that uses serverless compute. You need to ingest data by using Lakeflow Jobs. New records must be processed as soon as they become available. Which type of job trigger should you use for the ingestion?
Correct Answer: D
The correct answer is D - Continuous trigger. A Continuous trigger keeps the job running as a perpetual loop. As soon as one micro-batch or iteration completes, the next begins. New records are picked up with the shortest possible latency - as close to real- time as a Lakeflow Jobs pipeline gets. File Arrival (Option B) is event-driven but introduces per-file trigger overhead and is best suited for file-based ingestion rather than continuous streaming workloads. Scheduled (Option C) runs at fixed clock intervals - if new data arrives between runs, it waits until the next scheduled execution. Manual (Option A) requires a human to start each run. The question specifies serverless compute, which pairs naturally with Continuous trigger because serverless handles cluster lifecycle automatically - the job stays active without managing a persistent cluster. 'New records must be processed as soon as they become available' is the exact use case the Continuous trigger is designed for. Reference: https://learn.microsoft.com/en-us/azure/databricks/jobs/triggers
