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Define Airflow and explain it as a workflow orchestration tool.

Spark/Big Dataeasy0.3 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Fossil Group
Key Concepts Tested
airflow
Expert AnswerPremium
68 wordsInterview-ready
**Why Airflow matters**: DAG-as-code, dependency management, retries—industry standard for pipeline orchestration. **Definition**: Workflow orchestrator; DAGs define tasks and dependencies; scheduler triggers; workers execute. **Features**: Retries, backfill, monitoring, sensors for async dependencies. **Scalability trade-offs**: Scheduler can bottleneck; CeleryExecutor for parallelism. **Cost implications**: Self-managed = EC2 + ops; Managed (MWAA) = pay per worker....
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