I met an issue that my task in a tag never got pick up by workers for some reason.
When I look at the task details:
All dependencies are met but the task instance is not running. In most
cases this just means that the task will probably be scheduled soon
unless:
- The scheduler is down or under heavy load
If this task instance does not start soon please contact your Airflow
administrator for assistance.
I checked the scheduler, no errors in the log, also restarted it a few times.
I also checked the airflow websever log, only notice this:
22/11/2018 12:10:39[2018-11-22 01:10:39,747] {{cli.py:644}} DEBUG - [5
/ 5] killing 1 workers 22/11/2018 12:10:39[2018-11-22 01:10:39 +0000]
[43] [INFO] Handling signal: ttou 22/11/2018 12:10:39[2018-11-22
01:10:39 +0000] [348] [INFO] Worker exiting (pid: 348)
Not sure what happens, it worked fine before.
Airflow version 1.9.0, never change the version, only playing around some of the config: min_file_process_interval and dag_dir_list_interval (but I put it back to default when encounter this issue)
I do notice that this happens when I am playing around with some of the airflow config and rebuild our docker airflow image, then I revert it back to the original version, which used to work. Then the problem solved.
I also notice one error occurred (but not always captured) in my celery workers when I use the newly built image:
Unrecoverable error: AttributeError("'float' object has no attribute 'items'",)
So find that it is related to the latest redis release (Celery will use redis), you can find more details.
Related
Hi I'm currently running airflow on a Dataproc cluster. My DAGs used to run fine but facing this issue where tasks are ending up in 'retry' state without any logs when I click on task instance -> logs on airflow UI
I see the following error in terminal where I started the airflow webserver
2022-06-24 07:30:36.544 [ERROR] Executor reports task instance
<TaskInstance: **task name** 2022-06-23 07:00:00+00:00 [queued]> finished (failed)
although the task says its queued. Was the task killed externally?
None
[2022-06-23 06:08:33,202] {models.py:1758} INFO - Marking task as UP_FOR_RETRY
2022-06-23 06:08:33.202 [INFO] Marking task as UP_FOR_RETRY
What I tried so far
restarted webserver
Started server from 3 different ports
re-ran backfill command with 3 different timestamps
deleted dag runs for my dag, created a new dag run and then re-ran backfill command
cleared the PID as mentioned here How do I restart airflow webserver? and restarted the webserver
None of these worked. This issue is persistent for the past two days, appreciate any help here.At this point I'm guessing this is to do with a shared DB but not sure how to fix this.
<<update>> So what I also found is these tasks eventually go to success or failure state. when that happens the logs are available, but still no logs for the retry attempts in $airflow_home or our remote directory
The issue was there was another celery worker listening on the same queue. since this second worker was not configured properly it was failing the task and not writing the logs to remote location.
Airflow was working fine for several weeks and suddenly started getting errors for a few days.
Dags fail randomly with this error.
Log file does not exist: airflow_path/1.log
Fetching from: http://:8793/airflow_path/1.log
*** Failed to fetch log file from worker. The request to ':///' is missing either an 'http://
I had a similar issue, and I figured that in my case the worker node (I was using Celery Executor) was exhausted and therefore unavailable to execute any dags on it, can you check the CPU and memory utilized by the worker node (or its alternative if you are not using celery executor).
You can try to increase the CPU and memory for that applicable node and try.
Happened to me as well using LocalExecutor and an Airflow setup on Docker Compose. Eventually, I figured that the webserver would fail to fetch old logs whenever I recreated my Docker containers. Digging deeper, I realized that the webserver was failing to fetch the logs because it didn't have access to the filesystem of the scheduler (where the logs live).
The fix was to ensure that both the scheduler and the webserver services in docker-compose.yml share a volume with the logs, i.e.:
# docker-compose.yml
version: "3.9"
services:
scheduler:
image: ...
volumes:
- airflow_logs:/airflow/logs
...
webserver:
image: ...
volumes:
- airflow_logs:/airflow/logs
...
volumes:
airflow_logs:
Our airflow installation is using CeleryExecutor.
The concurrency configs were
# The amount of parallelism as a setting to the executor. This defines
# the max number of task instances that should run simultaneously
# on this airflow installation
parallelism = 16
# The number of task instances allowed to run concurrently by the scheduler
dag_concurrency = 16
# Are DAGs paused by default at creation
dags_are_paused_at_creation = True
# When not using pools, tasks are run in the "default pool",
# whose size is guided by this config element
non_pooled_task_slot_count = 64
# The maximum number of active DAG runs per DAG
max_active_runs_per_dag = 16
[celery]
# This section only applies if you are using the CeleryExecutor in
# [core] section above
# The app name that will be used by celery
celery_app_name = airflow.executors.celery_executor
# The concurrency that will be used when starting workers with the
# "airflow worker" command. This defines the number of task instances that
# a worker will take, so size up your workers based on the resources on
# your worker box and the nature of your tasks
celeryd_concurrency = 16
We have a dag that executes daily. It has around some tasks in parallel following a pattern that senses whether the data exists in hdfs then sleep 10 mins, and finally upload to s3.
Some of the tasks has been encountering the following error:
2019-05-12 00:00:46,212 ERROR - Executor reports task instance <TaskInstance: example_dag.task1 2019-05-11 04:00:00+00:00 [queued]> finished (failed) although the task says its queued. Was the task killed externally?
2019-05-12 00:00:46,558 INFO - Marking task as UP_FOR_RETRY
2019-05-12 00:00:46,561 WARNING - section/key [smtp/smtp_user] not found in config
This kind of error occurs randomly in those tasks. When this error happens, the state of task instance is immediately set to up_for_retry, and no logs in the worker nodes. After some retries, they execute and finished eventually.
This problem sometimes gives us large ETL delay. Anyone knows how to solve this problem?
We were facing similar problems , which was resolved by
"-x, --donot_pickle" option.
For more information :- https://airflow.apache.org/cli.html#backfill
I was seeing very similar symptoms in my DagRuns. I thought it was due to the ExternalTaskSensor and concurrency issues given the queuing and killed task language that looked like this: Executor reports task instance <TaskInstance: dag1.data_table_temp_redshift_load 2019-05-20 08:00:00+00:00 [queued]> finished (failed) although the task says its queued. Was the task killed externally? But when I looked at the worker logs, I saw there was an error caused by setting a variable with Variable.set in my DAG. The issue is described here duplicate key value violates unique constraint when adding path variable in airflow dag where the scheduler polls the dagbag at regular intervals to refresh any changes dynamically. The error with every heartbeat was causing significant ETL delays.
Are you performing any logic in your wh_hdfs_to_s3 DAG (or others) that might be causing errors or delays / these symptoms?
We fixed this already. Let me answer myself question:
We have 5 airflow worker nodes. After installing flower to monitor the tasks distributed to these nodes. We found out that the failed task was always sent to a specific node. We tried to use airflow test command to run the task in other nodes and they worked. Eventually, the reason was a wrong python package in that specific node.
Airflow stopped running tasks all of a sudden. Below are all running
airflow scheduler
airflow webserver
airflow worker
webui message
All dependencies are met but the task instance is not running. In most
cases this just means that the task will probably be scheduled soon
unless:
- The scheduler is down or under heavy load
If this task instance does not start soon please contact your Airflow
administrator for assistance.
Scheduler seems to be in a loop, keeps repeating the below messages. WebUI shows tasks are in queued state. Tried restarting the scheduler, didn't help.
[2018-11-17 22:03:45,809] {{jobs.py:1607}} DEBUG - Starting Loop...
[2018-11-17 22:03:45,809] {{jobs.py:1627}} INFO - Heartbeating the process manager
[2018-11-17 22:03:45,810] {{jobs.py:1662}} INFO - Heartbeating the executor
[2018-11-17 22:03:45,810] {{base_executor.py:103}} DEBUG - 124 running task instances
[2018-11-17 22:03:45,810] {{base_executor.py:104}} DEBUG - 0 in queue
[2018-11-17 22:03:45,810] {{base_executor.py:105}} DEBUG - 76 open slots
[2018-11-17 22:03:45,810] {{base_executor.py:132}} DEBUG - Calling the <class 'airflow.executors.celery_executor.CeleryExecutor'> sync method
[2018-11-17 22:03:45,810] {{celery_executor.py:80}} DEBUG - Inquiring about 124 celery task(s)
Airflow setup:
apache-airflow[celery, redis, all]==1.9.0
I also checked these posts but didn't help me:
Airflow 1.9.0 is queuing but not launching tasks
Airflow tasks get stuck at "queued" status and never gets running
Problem solved. This is a problem when you create your build on or after 2018-11-15 Turns out apache-airflow[celery, redis, all]==1.9.0 takes the latest version of redis-py 3.0.1 which does not work with celery 4.2.1.
Solution is to use redis-py 2.10.6
redis==2.10.6
apache-airflow[celery, all]==1.9.0
airflow 1.8.1
Scheduler, worker and webserver are running in separate dockers on AWS.
The system was operational, and now for some reason all tasks are staying in queued state...
No errors in scheduler logs.
In worker I see this error (not sure if its related since scheduler should move tasks from queued state):
[2018-01-23 20:46:00,428] {base_task_runner.py:95} INFO - Subtask: [2018-01-23 20:46:00,428] {models.py:1122} INFO - Dependencies not met for , dependency 'Task Instance State' FAILED: Task is in the 'success' state which is not a valid state for execution. The task must be cleared in order to be run.
I tried reboots, airflow clear and then resetdb commands but it did not help.
Any idea what else can be done to fix that problem?
Thanks