Architectural logic: Retries handle transient failures; timeouts prevent hung tasks from blocking DAGs. Configuration: default_args or per-task: retries, retry_delay, retry_exponential_backoff, execution_timeout. Example: retries=3, retry_delay=timedelta(minutes=2),...
This easy-level Cloud/Tools question appears frequently in data engineering interviews at companies like Aarete. While less common, it tests deeper understanding that distinguishes strong candidates.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Architectural logic: Retries handle transient failures; timeouts prevent hung tasks from blocking DAGs. Configuration: default_args or per-task: retries, retry_delay, retry_exponential_backoff, execution_timeout. Example: retries=3, retry_delay=timedelta(minutes=2), retry_exponential_backoff=True, execution_timeout=timedelta(minutes=45). Why exponential backoff: Reduces thundering herd on downstream services. Scalability: Too many retries on large DAGs can delay subsequent runs. Cost: Failed tasks still consume worker time. Best practice: Use exponential backoff; set timeouts; on_failure_callback for alerts; trigger_rule for downstream behavior.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked Cloud/Tools interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.