Airflow Local Executor Not Running Dags - airflow

I recently just switched my airflow server over from SequentialExecutor to a LocalExecutor. I changed my sql_alchemy_conn from sqlite to an sql database. I initialized the database and changed the executor over. However, none of my dags are running. I need them to run in parallel and they do not run at all. After changing over the config files I reset the scheduler and it says the scheduler is running without issue when i check its status on ubuntu.
However, the UI says that it does not appear to be running and that new tasks will not be scheduled.

Related

How to watch tasks logs via CLI in Airflow?

So I am having a problem: there are no logs displaying in Airflow UI I am currently working with, I don't know the reason, but I've already informed my colleagues about it and they're looking for a solution.
Meanwhile I need to watch logs of certain tasks of my Dag. Is there any way to do it via airflow CLI?
I am using airflow tasks run command but it only seems to run tasks, but doesn't show a thing in command line.
By default Airflow should store your logs at $AIRFLOW_HOME/logs/ maybe you'll find them there, if they are still generated.
In the meantime you can use airflow tasks test <dag_id> <task_id> this tests a specific task and displays the logs in your terminal.

Unable to create dag with apache airflow

I am running airflow 2.0, setting up airflow dag for the first time, and following quick start tutorials.
After creating and running the py file I don't see the dag created it does not list for me.
setting:
airflow.cfg:dags_folder = /Users/vik/src/airflow/dags
my python file is in this folder. There are no errors here.
I am able to see the example dags in example-dags.
I did airflow db init
airflow webserver
airflow scheduler
then try to list the dags
I think I am missing something
I don't know exactly how you installed everything, but I highly recommend Astronomer CLI for simplicity and quick setup. With that you'll be able to setup a first DAG pretty quickly. Here is also the video tutorial that helps you understand how to install / setup everything.
A few things to try:
Make sure the scheduleris running (run airflow scheduler) or try to restart it .
Using the Airflow CLI, run airflow config list and make sure that the loaded config is in fact what you are expecting, check the value of dags_folder.
Try running airflow dags list from the CLI, and check the the filepath if your dag is shown in the results.
If there was an error parsing your DAG, and therefore could not be loaded by the scheduler, you can find the logs in ${AIRFLOW_HOME}/logs/scheduler/${date}/your_dag_id.log

Cloud composer import custom plugin to all existing dags

I am using Cloud Composer to schedule multiple DAGs. These DAGs are built dynamically using this method and they use custom plugins.
I would like to know how to proceed when adding / modifying a plugin which concerns all DAGs (let's say it adds a new task to each DAGs)?
Do we need to pause all the running DAGs when doing so?
What I did so far when adding /modifying a plugin, is :
Upload the plugins into the plugins bucket of the Composer cluster (using gcloud composer command)
Do a dummy update in the Airflow config -> add a dummy value to the airflow.cfg (using gcloud composer commands)
I did that to force the DAGs to pause, and once the update is finished then the DAGs are resumed but with the new plugins and hence the new tasks (or if its not in this dagrun then it's the next one). Is it useless?
Thanks if you can help.
As explained in the architecture diagram, the Airflow webserver where you view your DAG and plugin code runs in a Google-managed tenant project, whereas the Airflow workers which actually run your DAG and plugin code are directly in your project.
When a DAG/Plugin is placed in the Composer bucket, the Airflow webserver(which falls under tenant project) validates the code and updates any new scheduling changes in the Airflow database.
At the same time, the Airflow scheduler (in your project) asks the Airflow database for the next DAG to run and notifies the Airflow workers to perform the scheduled work. The Airflow workers (in your project) then grab the DAG/Plugin code from the Composer bucket and compile them in order to run that specific task.
Thus, any updates made to your DAGs/Plugin code is read separately by the Airflow webserver and Airflow workers, at different times.
If you do not see your new code in the Airflow webserver, it should still be picked up by the Workers when they grab the code fresh on the new task run.
Therefore you shouldn't have to restart Composer for the workers to pick up the changes.
You cannot force a worker to grab and re-compile the new code mid task execution.
There are two ways to refresh the Airflow Webserver to see the Plugin code changes if it is not updating:
Set the reload_on_plugin_change property to True in the [webserver] section via the ‘AIRFLOW CONFIGURATIONS OVERRIDE’ tab in the Console.
OR, you can specifically add/remove/update a PYPI Package via the ‘PYPI PACKAGES’ Console tab. Non PYPI Package changes will not trigger the web server restart. Note this will also initiate an entire Composer environment restart which may take ~20 minutes.

Airflow initdb stuck on "add max tries column to task instance"

I'm using Airflow with MSSQL 2016 as backend. I started Airflow for the first time, running first Airflow initdb.
It seems to be fine until it get stuck (for more than an hour) on Running upgrade 127d2bf2dfa7 -> cc1e65623dc7, add max tries column to task instance.
I'm not sure why does it take so long, as this is the first time I'm running Airflow, thus the DB is empty, and no actual migration should happen...
If you look at migration file you'll see the loop for all dags and tasks. You probably have a lot of them. Just make airflow think there is no dags in the dags folder.
Solution: set environment variable AIRFLOW__CORE__DAGS_FOLDER to, for example, /tmp/123 (any empty directory will work), and run airflow initdb again

Airflow DAG "seems to be existing only locally. The master scheduler doesn't seem to be aware of its existence"

I used airflow for workflow of Spark jobs. After installation, I copy the DAG files into DAGs folder set in airflow.cfg. I can backfill the DAG to run the BashOperators successfully. But there is always a warning like the one mentioned. I didn't verify if the scheduling is fine, but I doubt scheduling can work as the warning said the master scheduler doesn't know of my DAG's existence. How can I eliminate this warning and get scheduling work? Anybody run into the same issue who can help me out?
This is usually connected to the Scheduler not running or the refresh interval being too wide. There are no log entries present so we cannot analyze from there. Also, unfortunately the very cause might have been ignored, because this is usually the root of the problem:
I didn't verify if the scheduling is fine.
So first you should check if both of the following services are running:
airflow webserver
and
airflow scheduler
If that won't help, see this post for more reference: Airflow 1.9.0 is queuing but not launching tasks

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