Crucial Exams

GCP Professional Data Engineer Practice Question

A retail analytics team deploys the following daily Cloud Composer workflow:

  • LocalFilesystemToGCSOperator uploads the previous day's CSV files
  • DataflowTemplateOperator transforms the files
  • GCSToBigQueryOperator loads the results into a partitioned table

After the DAG is first published, Airflow immediately tries to schedule every daily interval back to the start_date, quickly exceeding the project's Dataflow quota. The team wants the DAG to run only for intervals that begin after the deployment moment, while keeping the existing schedule_interval and start_date. What modification to the DAG definition will accomplish this goal?

  • Change schedule_interval to None to prevent historical and future automatic scheduling.

  • Set depends_on_past=True so each run waits for the previous one to finish before starting.

  • Configure max_active_runs=1 to limit the DAG to a single concurrent run.

  • Add catchup=False to the DAG constructor to disable back-filling of missed intervals.

GCP Professional Data Engineer
Maintaining and automating data workloads
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