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RAN-DBDEA-00025
Ranvier · DBDEA

Exam DBDEA Topics: ingestion Difficulty: hard

A retailer wants to ingest files from cloud object storage into a Unity Catalog-governed table once per night. The pipeline should start on a schedule, process whatever files have arrived, and then stop, so the team pays only for a short run instead of compute that stays on around the clock. Which design matches these requirements?

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  1. A. Start a stream with .trigger(processingTime='1 hour') and leave it running continuously, so each micro-batch picks up new files as they arrive
  2. B. Use .trigger(availableNow=True): process all available data, then stop — scheduled via a time-based trigger in a Lakeflow Job
  3. C. Run Trigger.Once inside a while loop in a single notebook so the stream never gets a chance to idle
  4. D. Skip Auto Loader entirely and use a one-time spark.read.parquet, because Auto Loader cannot be used for scheduled batch-style loads
Reveal answer

Correct answer: Use .trigger(availableNow=True): process all available data, then stop — scheduled via a time-based trigger in a Lakeflow Job

Reference: https://docs.databricks.com/aws/en/ingestion/cloud-object-storage/auto-loader/best-practices

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Official Answer (B): Use .trigger(availableNow=True): process all available data, then stop — scheduled via a time-based trigger in a Lakeflow Job

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