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Hourly run dag in Airflow

By : Marcia
Date : September 14 2020, 06:00 AM
like below fixes the issue It is not a time synchronization problem, it is due to the start_date and schedule_interval, airflow by default calculates how many times it should have been executed from start_date until the current date and start a DAG Run for any interval that has not been executed check here.
In your case the start date is 7:01 and according to your schedule_interval the execution intervals are 8:00, 9:00, 10:00 ...
code :
dag = DAG('Hourly_test_2', catchup=False, schedule_interval='0 * * * *', default_args=default_args)

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Python 3.5 to compute a person's salary from their hourly wage and hourly payrate

By : user7337786
Date : March 29 2020, 07:55 AM
wish helps you Few things here.
You are trying to print salary, which can either be the variable or the function. I would suggest renaming the function or the variable. I think you are trying to call salary in the print function. However, you have made pay a parameter which isn't being used in the print function. print(salary) You are working with numbers, so it would be best to convert the input functions to int's straight away, like this - payrate= int(input("How much do you get paid per hour")), do the same with the other one.

Airflow: what do `airflow webserver`, `airflow scheduler` and `airflow worker` exactly do?

By : Hafiz Atanda
Date : March 29 2020, 07:55 AM
To fix this issue Each process does what they are built to do while they are running (webserver provides a UI, scheduler determines when things need to be run, and workers actually run the tasks).
I think your confusion is that you may be seeing them as commands that tell some sort of "Airflow service" to do something, but they are each standalone commands that start the processes to do stuff. ie. Starting from nothing, you run airflow scheduler: now you have a scheduler running. Run airflow webserver: now you have a webserver running. When you run airflow webserver, it is starting a python flask app. While that process is running, the webserver is running, if you kill command, is goes down.

Airflow long running hourly DAG's missing few hours

By : pwladm
Date : March 29 2020, 07:55 AM
Any of those help This appears to be a perfect scenario for using TimeDeltaSensor
code :
import datetime

from airflow.models import DAG
from airflow.operators.dummy_operator import DummyOperator
from airflow.operators.python_operator import PythonOperator
from airflow.sensors.time_delta_sensor import TimeDeltaSensor
from airflow.utils.trigger_rule import TriggerRule

# create DAG object
my_dag: DAG = DAG(dag_id="my_dag",
                  start_date=datetime.datetime(year=2019, month=3, day=11),
                  schedule_interval="0 0 0 * * *")

# create dummy begin & end tasks
my_begin_task: DummyOperator = DummyOperator(dag=my_dag,
my_end_task: DummyOperator = DummyOperator(dag=my_dag,

# populate the DAG
for i in range(1, 24, 1):
    # create sensors and actual tasks for all hours of the day
    my_time_delta_sensor: TimeDeltaSensor = TimeDeltaSensor(dag=my_dag,
    my_actual_task: PythonOperator = PythonOperator(dag=my_dag,
    # wire-up tasks together
    my_begin_task >> my_time_delta_sensor >> my_actual_task >> my_end_task

apache airflow external task sensor on hourly running task

By : onroof
Date : March 29 2020, 07:55 AM
seems to work fine You can create a file (i.e. SUCCESS) at the end of your hourly DAG (delete SUCCESS as the first task of this dag) and add a file sensor task in your daily job.
In this case, as long as your hourly task running, your daily job cannot be executed.

Run airflow process and airflow webserver as airflow user

By : prabhas raju
Date : March 29 2020, 07:55 AM
should help you out Have you tried actually following the directions as listed in the linked offical docs? I believe that as long as you use Airflow supplied SystemD configs all processes should start using airflow:airflow.
This happens in these two lines
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