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DAG Runs — Airflow Documentation

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A DAG Run is an object representing an instantiation of the DAG in time. Any time the DAG is executed, a DAG Run is created and all tasks inside it are executed. The status of the DAG Run depends on the tasks states. Each DAG Run is run separately from one another, meaning that you can have many runs of a DAG at the same time. A DAG Run status is determined when the execution of the DAG is finished. The execution of the DAG depends on its containing tasks and their dependencies. The status is assigned to the DAG Run when all of the tasks are in the one of the terminal states (i.e. if there is no possible transition to another state) like success, failed or skipped. The DAG Run is having the status assigned based on the so-called “leaf nodes” or simply “leaves”. Leaf nodes are the tasks with no children. There are two possible terminal states for the DAG Run: success if all of the leaf nodes states are either success or skipped, failed if any of the leaf nodes state is either failed or

Dag Runs - Airflow 3.3.0 Documentation Content Version: 3.3.0 Search docs ⌘ K Content Overview Quick Start Installation of Airflow® Security Tutorials How-to Guides UI Overview Core Concepts Architecture Overview Dags Dag Runs Dag Run Status Data Interval Manual Triggering and Data Intervals Re-run Dag Catchup Backfill UI CLI Re-run Tasks Task Instance History External Triggers Passing Parameters when triggering Dags Wait for a Dag Run Using CLI To Keep in Mind Tasks Operators Sensors TaskFlow Resumable Tasks Executor Auth manager Multi-Team Object Storage Backfill Message Queues XComs Variabl

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