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BigData / Apache Airflow Interview Questions

What is the Airflow metadata database and what does it store?

The metadata database (metastore) is a relational database (PostgreSQL or MySQL recommended for production; SQLite for local testing) that is the central state store for Airflow. It persists:

  • DAG definitions and schedules
  • DAG Runs and their states
  • Task Instances and their states, logs, and XCom values
  • Connections and Variables
  • User accounts and RBAC roles (when auth is enabled)
  • Pool and slot usage

The database schema is managed through Alembic migrations and upgraded via airflow db upgrade.

Which database is recommended for the Airflow metadata store in production?

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More Related questions...

What is Apache Airflow? What is a DAG in Apache Airflow? What are Operators in Apache Airflow? What is the Airflow Scheduler? What are the main components of Apache Airflow? What is an Executor in Airflow and what types are available? What is an Airflow Connection? What is an Airflow Variable? What is XCom in Airflow and how is it used? What are Hooks in Apache Airflow? What is the difference between a DAG Run and a Task Instance in Airflow? What are Sensors in Apache Airflow? What is catchup in Airflow and how does it work? What is backfilling in Apache Airflow? What is the TaskFlow API in Airflow? What is the difference between schedule_interval and timetable in Airflow? What is a SubDAG and why is it generally discouraged? What is a TaskGroup in Airflow? What is branching in Airflow and how is BranchPythonOperator used? What are trigger rules in Airflow? What is the Airflow metadata database and what does it store? How does the CeleryExecutor work in Airflow? What is the KubernetesExecutor and what are its benefits? What are Pools in Apache Airflow? What are Airflow Providers? What is dynamic task mapping in Airflow? What is the difference between depends_on_past and wait_for_downstream in Airflow? What is the Airflow Web UI and what can you do with it? What are Airflow task states and what do they mean? What are retries and retry_delay in Airflow tasks? What is a Deferrable Operator (async operator) in Airflow? What are Airflow Plugins? How does Airflow handle templating and macros? What is idempotency in the context of Airflow tasks? What are best practices for writing efficient Airflow DAGs? What is the ExternalTaskSensor in Airflow? What is the KubernetesPodOperator in Airflow? What are SLAs in Apache Airflow and how are they configured? How does Airflow handle task concurrency and parallelism? What is an Airflow Dataset and how does data-driven scheduling work? What is the difference between Airflow and Apache Spark? How do you deploy Apache Airflow using Docker Compose? What is Airflow on Kubernetes (KEDA) autoscaling? What is the SparkSubmitOperator in Airflow? What is Managed Airflow (MWAA) on AWS? How does Airflow handle secrets management? What is the difference between PythonOperator and PythonVirtualenvOperator? What is the Grid view in Airflow 2.x? What are common Airflow anti-patterns to avoid? What is Airflow 2 vs Airflow 1 — key differences?
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