Can not run DAGs since upgraded from Airflow 1.7 - airflow

We installed Airflow 1.7, and used it for several months. I used PIP to uninstall ariflow 1.7 and install 1.9 (gory details are [here|airflow initdb failed: ImportError: No module named log.logging_mixin
Since then, I haven't had a single DAG run. I renamed and moved log files to match the 1.9 expectations, but still nothing happens.
I have a "run every 40 minutes" DAG, it hasn't run since 3/28. When I manually trigger it, no log file is created, nothing happens except I get a running DAG listed under "DAG Runs" (I do NOT get anything listed under "Recent Tasks", and "Last Run" does not get updated.
I have a "Run once" DAG that I created. I triggered it, same behavior.
I have also tried running the example_bash_operator DAG. Same behavior.

The Airflow documentation is a bit thin on all the requirements needed to run DAGs correctly.
Aside from the webserver, make sure the scheduler is running as well. Also check if the DAG is configured with a correct schedule and there is scheduling information in the "Task Instance Information" page.
See this answer for more "checkpoints": Airflow 1.9.0 is queuing but not launching tasks

Related

airflow UI list of dags doesn't update

I'm encountering a problem where valid dags that show up in airflow dags list don't show up in the UI
The dags_folder points to the right location and I have restarted the webserver and scheduler many times, as well as ran the occasional airflow db reset
I think that my airflow is just ignoring the cfg file, because I changed load_examples to False and all the example dags still show up
I'm on airflow 2.4.0 working in a venv on ubuntu. What could be causing this?

How do you create a triggerer process in an Airflow installation?

In an Airflow DAG, I am trying to use a TimeDeltaTrigger:
from airflow.triggers.temporal import TimeDeltaTrigger
...
self.defer(trigger=TimeDeltaTrigger(timedelta(seconds=15)), method_name="execute")
But when my DAG runs, I get a warning in the GUI:
In the GUI, if I go to Browse -> Triggers I see one trigger, but it is not for TimeDeltaTrigger:
The documentation for Deferrable Operators (https://airflow.apache.org/docs/apache-airflow/stable/concepts/deferring.html) says:
Ensure your Airflow installation is running at least one triggerer process, as well as the normal scheduler
But it is not clear how to do this.
How can I configure my Airflow installation so that I can use a TimeDeltaTrigger?
triggerer is a process like scheduler, webserver, and worker. You need to start a process or container dedicated to running the triggerer to use deferrable operators.
To start a triggerer process, run airflow triggerer in your Airflow environment. You should see an output similar to the below image.
Triggerer Logs

Can't delete dag from airflow UI after deleting from dag_bag

I deleted dag from airflow dag_bag and corresponding .pyc file as well. When I try to delete the same dag from airflow UI it is showing this error:
Dag id MY_DAG_ID is still in DagBag. Remove the DAG file first.
The airflow version I am using is 1.10.4
Even after restarting airflow I'm not able to delete from UI. I was using 1.10.3 previously, but I never faced this issue. I was able to delete from UI after deleting from dags folder.
When I click on that dag in UI it is showing :
DAG "MY_DAG_ID" seems to be missing.( this is expected as I deleted dag from folder)
Try stopping the scheduler and the webserver and then deleting the DAG from the command line:
airflow delete_dag 'MY_DAG_ID'
I had the same issues after I upgraded to 1.10.6. Here's what I did:
Before removing the DAG, make sure no instance is on running, retry status. Then Pause it
Delete on UI or using the command airflow delete_dag dag_id
Restart the scheduler and webserver
Try to execute airflow list_dags to see if it really got deleted.
If it doesn't work, try to upgrade to the latest version.

Airflow scheduler does not appear to be running after execute a task

When there is a task running, Airflow will pop a notice saying the scheduler does not appear to be running and it kept showing until the task finished:
The scheduler does not appear to be running. Last heartbeat was received 5 minutes ago.
The DAGs list may not update, and new tasks will not be scheduled.
Actually, the scheduler process is running, as I have checked the process. After the task finished, the notice will disappear and everything back to normal.
My task is kind of heavy, may running for couple hours.
I think it is expected for Sequential Executor. Sequential Executor runs one thing at a time so it cannot run heartbeat and task at the same time.
Why do you need to use Sequential Executor / Sqlite? The advice to switch to other DB/Executor make perfect sense.
You have started airflow webserver and you haven't started your airflow scheduler.
Run airflow scheduler in background
airflow scheduler > /console/scheduler_log.log &
I had the same issue.
I switch to postgresql by updating airflow.cfg file > sql_alchemy_conn =postgresql+psycopg2://airflow#localhost:5432/airflow
and executor = LocalExecutor
This link may help how to set this up locally
https://medium.com/#taufiq_ibrahim/apache-airflow-installation-on-ubuntu-ddc087482c14
A quick fix could be to run the airflow scheduler separately. Perhaps not the best solution but it did work for me. To do so, run this command in the terminal:
airflow scheduler
I had a similar issue and have been trying to troubleshoot this for a while now.
I managed to fix it by setting this value in airflow.cfg:
scheduler_health_check_threshold = 240
PS: Based on a recent conversation in Airflow Slack Community, it could happen due to contention at the Database side. So, another workaround suggested was to scale up the database. In my case, this was not a viable solution.
EDIT:
This was last tested with Airflow Version 2.3.3
I have solved this issue by deleting airflow-scheduler.pid file.
then
airflow scheduler -D
Check the airflow-scheduler.err and airflow-scheduler.log files.
I got an error like this:
Traceback (most recent call last):
File "/home/myVM/venv/py_env/lib/python3.8/site-packages/lockfile/pidlockfile.py", ine 77, in acquire
write_pid_to_pidfile(self.path)
File "/home/myVM/venv/py_env/lib/python3.8/site-packages/lockfile/pidlockfile.py", line 161, in write_pid_to_pidfile
pidfile_fd = os.open(pidfile_path, open_flags, open_mode)
FileExistsError: [Errno 17] File exists: '/home/myVM/venv/py_env/airflow-scheduler.pid'
I removed the existing airflow-scheduler.pid file and started the scheduler again by airflow scheduler -D. It was working fine then.
Our problem is that the file "logs/scheduler.log" is too large, 1TB. After cleaning this file everything is fine.
I had the same issue while using sqlite. There was a special message in Airflow logs: ERROR - Cannot use more than 1 thread when using sqlite. Setting max_threads to 1. If you use only 1 thread, the scheduler will be unavailable while executing a dag.
So if use sqlite, try to switch to another database. If you don't, check max_threads value in your airflow.cfg.
On Composer page, click on your environment name, and it will open the Environment details, go to the PyPIPackages tab.
Click on Edit button, increase the any package version.
For example:
I increased the version of pymsql packages, and this restarted the airflow environment, it took a while for it to update. Once it is done, I'm no longer have this error.
You can also add a Python package, it will restart the airflow environment.
I've had the same issue after changing the airflow timezone. I then restarted the airflow-scheduler and it works. You can also check if the airflow-scheduler and airflow-worker are on different servers.
In simple words, using LocalExecutor and postgresql could fix this error.
Running Airflow locally, following the instruction, https://airflow.apache.org/docs/apache-airflow/stable/start/local.html.
It has the default config
executor = SequentialExecutor
sql_alchemy_conn = sqlite:////Users/yourusername/airflow/airflow.db
It will use SequentialExecutor and sqlite by default, and it will have this "The scheduler does not appear to be running." error.
To fix it, I followed Jarek Potiuk's advice. I changed the following config:
executor = LocalExecutor
sql_alchemy_conn = postgresql://postgres:masterpasswordforyourlocalpostgresql#localhost:5432
And then I rerun the "airflow db init"
airflow db init
airflow users create \
--username admin \
--firstname Peter \
--lastname Parker \
--role Admin \
--email spiderman#superhero.org
After the db inited. Run
airflow webserver --port 8080
airflow scheduler
This fixed the airflow scheduler error.
This happens to me when AIRFLOW_HOME is not set.
By setting AIRFLOW_HOME to the correct path, the indicated executor will be selected.
If it matters: somehow, the -D flag causes a lot of problems for me. The airflow webserver -D immediately crashes after starting, and airflow scheduler -D somehow does next to nothing for me.
Weirdly enough, it works without the detach flag. This means I can just run the program normally, and make it run in the background, with e.g. nohup airflow scheduler &.
After change executor from SequentialExecutor to LocalExecutor, it works!
in airflow.cfg:
executor = LocalExecutor

How ro remove unwanted broken DAGs in airflow

I write something wrong in my sql_test.py,and run python sql_test.py,the error is 'no module named xxx',and in web-ui it shows a red error - Broken DAG.
And then I run airflow list_dags the same error occurs again .This is strange and I don't know what's happening.
I tried to run airflow delete_dags sql_test but there is no such id.
How can I :
remove the waning in web-ui
get sql_test out of list_dags
There's some syntactical mistake in your dag-definition file, resulting in failure in parsing the DAG. When Airflow fails to parse a DAG, several functionalities get broken (like list_dags in your case)
Of course deleting the problematic dag-definition file would fix it, but that's not a solution. So here's how you can understand what's wrong and fix it
From linux shell, go to Airflow's logs folder
cd $AIRFLOW_HOME/logs/scheduler/latest/
Run tree command to see directory structure
tree -I "__init__.py|__pycache__|*.pyc"
View the last few lines of the log file of your corresponding broken dag
tail -n 25 /path/to/my/broken-dag.py.log
This will give you the stack-trace that Airflow threw while trying to parse your broken dag file. That would hopefully help you diagnose the problem and patch it.
Once your dag-definition file is fixed
the broken dag message would disappear from UI
DAG would appear in the UI (refresh it a few times)
list_dags command would also start working
If you don't want to repair your DAG and ignore it, you can remove the unwanted DAG by specifying the DAG's underlying file in an .airflowignore file.

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