Quick Start¶
The installation is quick and straightforward.
# airflow needs a home, ~/airflow is the default,
# but you can lay foundation somewhere else if you prefer
# (optional)
export AIRFLOW_HOME=~/airflow
# install from pypi using pip
pip install apache-airflow
# initialize the database
airflow initdb
# start the web server, default port is 8080
airflow webserver -p 8080
# start the scheduler
airflow scheduler
# visit localhost:8080 in the browser and enable the example dag in the home page
Note
On November 2020, new version of PIP (20.3) has been released with a new, 2020 resolver. This resolver
does not yet work with Apache Airflow and might leads to errors in installation - depends on your choice
of extras. In order to install Airflow you need to either downgrade pip to version 20.2.4
pip upgrade --pip==20.2.4 or, in case you use Pip 20.3, you need to add option
--use-deprecated legacy-resolver to your pip install command.
Upon running these commands, Airflow will create the $AIRFLOW_HOME folder
and lay an “airflow.cfg” file with defaults that get you going fast. You can
inspect the file either in $AIRFLOW_HOME/airflow.cfg, or through the UI in
the Admin->Configuration menu. The PID file for the webserver will be stored
in $AIRFLOW_HOME/airflow-webserver.pid or in /run/airflow/webserver.pid
if started by systemd.
Out of the box, Airflow uses a sqlite database, which you should outgrow
fairly quickly since no parallelization is possible using this database
backend. It works in conjunction with the airflow.executors.sequential_executor.SequentialExecutor which will
only run task instances sequentially. While this is very limiting, it allows
you to get up and running quickly and take a tour of the UI and the
command line utilities.
Here are a few commands that will trigger a few task instances. You should
be able to see the status of the jobs change in the example1 DAG as you
run the commands below.
# run your first task instance
airflow run example_bash_operator runme_0 2015-01-01
# run a backfill over 2 days
airflow backfill example_bash_operator -s 2015-01-01 -e 2015-01-02
What’s Next?¶
From this point, you can head to the Tutorial section for further examples or the How-to Guides section if you’re ready to get your hands dirty.