![]() ![]() Table_name = db. 'retry_delay': datetime.timedelta(minutes=5), # If a task fails, retry it once after waiting at least 5 minutes # To email on failure or retry set 'email' arg to your email and enable # Setting start date as yesterday starts the DAG immediately when it is Document overriding XCom.clear for data lifecycle management (17589) Path correction in docs for airflow core (17567) docs(celery): reworded. Insert_into='INSERT INTO study(study) VALUES (\'' my_name '\' ) 'įull example combined with Airflow dag and Python BranchOperator ( also committed to git)įrom import bigquery_to_gcsįrom import gcs_to_bqįrom _operator import DummyOperatorįrom airflow.operators import BashOperatorįrom import gcs_to_gcsįrom _operator import BigQueryOperatorįrom airflow.operators import PythonOperatorįrom _operator import BranchPythonOperatorĭ() - datetime.timedelta(1), Query = db.select().where(study_圜ol2 =my_name ) I try to remove the Xcom variables for a task within a certain execution-date to create and use another instance of the Xcom variable for the same task. Study_table = db.Table('my_table', metadata, autoload=True, autoload_with=engine) Removing Airflow's xcom variables isn't working with Operational Error : 'Incorrect datetime value in 'executiondate' at row 1' Asked Viewed 718 times 0 I am facing a strange error in airflow. To learn quickly SQLAlchemy: I used this blog for the select and this blog for the insert, 1 hour later the below sample code was born.Įngine = get_name_from_airflow_db(my_name): Implements apache-airflow-providers-google package Project description Package apache-airflow-providers-google Release: 10.1. ImportError: this is MySQLdb version (1, 2, 4, 'beta', 4), but _mysql is version (1, 2, 5, 'final', 1) I tried using SQLAlchemy because I assumed since airflow is using it, the packages will be set. Push1 > pull1 > push2 > pull2 > push3 > pull3 > push4 > pull4Įventually, it was so frustrating using XCom, started checking how fast and simple would be to query the MySQL db directly from the dag (using a pythonOperator). ![]() Go over airflow DAG – “example_xcom” trigger the DAG For each PythonOperator – and view log –> watch the Xcom section
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