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Sometimes difficult to find errors in DAG Businesses opt to go for a custom code using Airflow. Verify DAG file is in correct folder - it must be an absolute pathĭetermine the DAGs folder via airflow.cfg Syntax errors Not enough tasks free within the executor to run Modify the attributes to meet your requirements INFO - Using SequentialExecutor Debugging and troubleshooting in Airflow Typical issues.įix by running airflow scheduler from the command-lineĪt least one schedule_interval hasn't passed SequentialExecutor - the default - runs one task at a time useful for debugging while functional, not really recommended for production LocalExecutor - treats tasks as processes parallelism defined by the user can utilize all resources of a given host systemĬeleryExecutor - ]: a general queuing system written in Python that allows multiple systems to communicate as a basic cluster multiple worker systems can be defined significantly more difficult to setup and configure extremely powerful for organizations with extensive workflowsĮ.g. To add task repetition without loops ]sĭifferent executors handle running the tasks differently Many others in nsors and libraries Why sensors? SqlSensor - Runs a SQL query to check for content
#AIRFLOW MACROS INSTALL#
HttpSensor - Request a web URL and check for content You should probably install apache-airflow in a venv and before putting your code into a running system cd DAGSDIRECTORY PYTHONPATH. Init_sales_cleanup > file_sensor_task > generate_report Other sensorsĮxternalTaskSensor - wait for a task in another DAG to complete
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