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Posted to commits@airflow.apache.org by GitBox <gi...@apache.org> on 2021/11/30 18:30:59 UTC
[GitHub] [airflow] alexakra opened a new issue #19901: No scheduling when max_active_runs is 1
alexakra opened a new issue #19901:
URL: https://github.com/apache/airflow/issues/19901
### Apache Airflow version
2.2.2 (latest released)
### Operating System
Debian
### Versions of Apache Airflow Providers
_No response_
### Deployment
Official Apache Airflow Helm Chart
### Deployment details
_No response_
### What happened
Since version 2.2 a field `DAG.next_dagrun_create_after` is not calculated when `DAG.max_active_runs` is 1.
### What you expected to happen
https://github.com/apache/airflow/blob/fca2b19a5e0c081ab323479e76551d66ab478d07/airflow/models/dag.py#L2466
If this condition is evaluated when a state is "running" then it is incorrect.
### How to reproduce
Create a DAG with a `schedule_interval` and `max_active_runs=1.`
### Anything else
_No response_
### Are you willing to submit PR?
- [ ] Yes I am willing to submit a PR!
### Code of Conduct
- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
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[GitHub] [airflow] ephraimbuddy commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
ephraimbuddy commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989953755
I ran your dag and it ran perfectly well
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[GitHub] [airflow] github-actions[bot] commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-1015946233
This issue has been automatically marked as stale because it has been open for 30 days with no response from the author. It will be closed in next 7 days if no further activity occurs from the issue author.
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[GitHub] [airflow] holyachon edited a comment on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
holyachon edited a comment on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-1029889193
@easontm @alexakra
Hello. I'm also experiencing a similar situation closer to @easontm, where the scheduler does not schedule a DAG in Airflow 2.2.3.
I have a "DAG for health check" of which schedule_interval is `*/10 * * * *` (runs every ten minutes). And almost every specific time(02:20), this dag is not scheduled and column `DAG.next_dagrun_create_after` is NULL.
After a few minutes later (ex. 02:25~30), the dag is scheduled only then. So there is a delay in dag scheduling. ( `airflow_dagrun_schedule_delay` metric is below)
I think it happens because many tasks are running and scheduled at 02:20, but they work(run or scheduled) well except "health check DAG".
> Another correlated symptom is that affected DAGs no longer get any scheduler/processing logs (in $AIRFLOW_HOME/logs/scheduler/<DATE>/...).
Also there is no scheduler log about affected DAG same as @easontm.
Is there any other workaround or solution without downgrade?
Thank you in advance :)
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[GitHub] [airflow] holyachon commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
holyachon commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-1029889193
@easontm @alexakra
Hello. I'm also experiencing a similar situation closer to @easontm, where the scheduler does not schedule a DAG in Airflow 2.2.3.
I have a "DAG for health check" of which schedule_interval is `*/10 * * * *` (runs every ten minutes). And almost every specific time(02:20), this dag is not scheduled and column `DAG.next_dagrun_create_after` is NULL.
I think it happens because many tasks are running and scheduled at 02:20, but they work(run or scheduled) well except "health check DAG".
> Another correlated symptom is that affected DAGs no longer get any scheduler/processing logs (in $AIRFLOW_HOME/logs/scheduler/<DATE>/...).
Also there is no scheduler log about affected DAG same as @easontm.
Is there any other workaround or solution without downgrade?
Thank you in advance :)
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[GitHub] [airflow] alexakra commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989593193
> What do you mean by no scheduling? Is it that dagruns are not created at all?
There is a record in the "dag" table in which `next_dagrun_create_after` remains `null`.
In the description above, I pointed to the exact line in the code. It was changed in 2.2.
And "If this condition is evaluated when a state is "running" then it is incorrect.", i.e. condition should be ">" instead of ">=".
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[GitHub] [airflow] alexakra commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-997402308
I didn't notice whether the processing logs were created or not.
I have just looked for "Setting next_dagrun for %s to %s" in the logs and it was missing. This is the reason I assumed that the condition that I mentioned in the description is True, i.e. `orm_dag.next_dagrun_create_after = None`.
I have dozens of scheduled DAGs and this happened for all of them immediately after upgrade to 2.2.2. So, I reverted back to 2.1.4.
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[GitHub] [airflow] alexakra commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989962919
Could it be related to an upgraded from 2.1.4?
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[GitHub] [airflow] github-actions[bot] commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-1021726083
This issue has been closed because it has not received response from the issue author.
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[GitHub] [airflow] easontm commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
easontm commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-1031045146
@holyachon I have created a truly horrifying script to prevent this from occurring. I actually bundled it with some scheduling delay measurement I was trying to do, because when a DAGrun isn't created the built-in schedule delay metric isn't accurate.
The tl;dr is I look at all active DAGs, look at the latest DAG run, and use the schedule to determine if there should be a DAGrun between the latest and now. If I detect a delay, I touch the file which forces the dagprocessor to reexamine the file. I run this on an independent pod in my deployment. Just take out all the statsd stuff if you don't want measurement. And adapt the connection for whatever backend DB you're using.
I previously just tried to touch all DAG files (in small batches spread over a couple hours), but that actually made things worse. So I have this slightly more surgical application.
<details>
<summary markdown="span">code</summary>
```python
import subprocess
import sys
import traceback
from datetime import datetime, timedelta
from json import loads
from os import environ, path
from pathlib import Path
from pprint import pformat
from time import sleep
from mysql.connector import connection
from statsd import StatsClient
subprocess.check_call([sys.executable, "-m", "pip", "install", "croniter"])
statsd = StatsClient("airflow-scheduler", 9125)
SLEEP_TIME = 60
SQL_ALCHEMY_CONN = environ["SQL_ALCHEMY_CONN"]
user = SQL_ALCHEMY_CONN.split("://")[1].split(":")[0]
password = SQL_ALCHEMY_CONN.split("/" + user + ":")[1].split("@")[0]
host = SQL_ALCHEMY_CONN.split("@")[1].split(":3306/")[0]
database = SQL_ALCHEMY_CONN.split(":3306/")[1]
def process_dag(dag, check_time):
from croniter import croniter
exec_date = dag["execution_date"]
end_date = dag["end_date"]
mar = dag["max_active_runs"]
schedule_interval = dag["schedule_interval"]
dag_id = dag["dag_id"]
state = dag["state"]
if exec_date is None:
print(f"[WARN] No run found for {dag_id} in the last 10 days.")
return
if schedule_interval[0] == "{":
j = loads(schedule_interval)
td = timedelta(
days=j["attrs"]["days"],
seconds=j["attrs"]["seconds"],
microseconds=j["attrs"]["microseconds"],
)
current_theoretical_start = exec_date + td
next_theoretical_start = exec_date + td + td
else:
try:
cron = croniter(schedule_interval, exec_date)
except Exception:
raise Exception(
f"Cron gen failed: {dag_id}. schedule interval is {schedule_interval}"
)
current_theoretical_start = cron.get_next(datetime)
next_theoretical_start = cron.get_next(datetime)
try:
if state == "running":
# This gets its own case because a running DAG could either be in a backfill
# or part of a regular run. That is, next_theoretical_start may be before
# OR after check_time, and we can't use that switch by itself.
# if we are evaluating a running DAGrun we will measure the best between
# 1. difference between previous end and this start
# a. If this is negative (overlapping runs) we will use 0
# 2. the difference between the actual and scheduled start
return 0
elif (
next_theoretical_start < check_time
): # if the next one should have started already
# It's possible that a DAGrun didn't start because we reached peak concurrency for
# some time. While this can happen for any MAR value, 1 is the most dangerous one
# for natural reasons. In case the previous DAG took a long time, we will take the
# delta between the previous ending and the current check time. This can probably
# be refined in the future.
if mar == 1:
return min(
(check_time - next_theoretical_start).total_seconds(),
(check_time - end_date).total_seconds(),
)
else:
return (check_time - next_theoretical_start).total_seconds()
else:
# We will consider DAGs whose runs are caught up to not be in a delay state
# even if the previous run was delayed, because this will make the metric
# represent the current state of the system. Any delays will be present in
# the historical values.
return 0
except Exception as e:
print(f"Error processing DAG {dag}")
print(f"current_theoretical_start: {current_theoretical_start}")
print(f"next_theoretical_start: {next_theoretical_start}")
print(f"check_time: {check_time}")
print(traceback.format_exc())
print(e)
while True:
now = datetime.now()
print(f"Starting check: {now}")
with connection.MySQLConnection( # mysql.connector.connect(
host=host, user=user, password=password, database=database,
) as mydb:
with mydb.cursor() as cur:
query = f"""
SELECT
dag.dag_id
,fileloc
,schedule_interval
,max_active_runs
,state
,execution_date
,start_date
,end_date
,gap
FROM dag
LEFT JOIN (
SELECT dag_id
,execution_date
,start_date
,end_date
,state
,RANK() OVER (PARTITION BY dag_id ORDER BY execution_date DESC) AS rnk
,TIMEDIFF(
start_date, LAG(end_date) OVER (PARTITION BY dag_id ORDER BY execution_date ASC)
) AS gap
FROM dag_run
WHERE DATE(start_date) >= DATE'{str(now - timedelta(days=10))[:10]}'
AND run_id NOT LIKE 'manual%'
) runs
ON dag.dag_id = runs.dag_id
WHERE NOT is_paused
AND is_active
AND NOT is_subdag
AND schedule_interval <> 'null'
AND schedule_interval <> '"@once"'
AND (rnk = 1 OR rnk IS NULL)
-- AND state <> 'running'
"""
print(f"Executing query: \n{query}")
cur.execute(query)
col_names = [i[0] for i in cur.description]
results = cur.fetchall()
r_maps = [
{
col_names[i]: r[i] if type(r[i]) != str else r[i].strip('"')
for i in range(len(col_names))
}
for r in results
]
touched = []
delayed = []
total_delay = 0
for dag in r_maps:
delay = process_dag(dag, now)
if delay is None:
continue
if delay > 600:
delayed.append((dag["dag_id"], round(delay)))
if now.timestamp() - path.getmtime(dag["fileloc"]) > delay:
Path(dag["fileloc"]).touch()
touched.append((dag["dag_id"], round(delay)))
total_delay += delay
print(f"DAG: {dag['dag_id']} -- delay: {round(delay, 2)}")
statsd.gauge(f"airflow.custom_dag_delay.{dag['dag_id']}", delay)
avg_delay = round(total_delay / len(r_maps))
# statsd.gauge(f"airflow.custom_dag_delay_avg.{avg_delay}", delay)
print(f"Delayed DAGs: {pformat(delayed)}")
print(f"Touched DAGs: {pformat(touched)}")
print(
f"Total delay: {round(total_delay)}s across {len(r_maps)} DAGs. {avg_delay}s per DAG"
)
print(f"End loop. Sleeping for {SLEEP_TIME} seconds.")
sleep(SLEEP_TIME)
```
</details>
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[GitHub] [airflow] alexakra edited a comment on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra edited a comment on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989593193
> What do you mean by no scheduling? Is it that dagruns are not created at all?
There is a record in the "dag" table in which `next_dagrun_create_after` remains `null`.
In the description above, I pointed to the exact line in the code. It was changed in 2.2.
And "If this condition is evaluated when a state is "running" then it is incorrect.", i.e. condition should be ">" instead of ">=".
When `next_dagrun_create_after` remains `null`, the dag doesn't run/scheduled anymore.
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[GitHub] [airflow] easontm commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
easontm commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-997355672
> yes, just another single run
I think I'm experiencing a similar circumstance (on 2.2.2), however I usually get more than one run after causing a re-process.
It's not specific to any particular DAG, but there is some kind of condition (that I can't replicate on-demand) which results in the scheduler no longer creating new DAGruns. It always happens with DAGs whose `max_active_runs` is easy to hit, in the 1-3 range. IIRC every time I've seen this, the column `DAG.next_dagrun_create_after` is empty for that DAG -- but not every DAG that has this field empty has this issue. Another correlated symptom is that affected DAGs no longer get any scheduler/processing logs (in `$AIRFLOW_HOME/logs/scheduler/<DATE>/...`).
This happens to me maybe 2-3 times a month and I have all my (`INFO`) scheduler logs, although I haven't seen any anomalies myself. If anyone with better insight on the scheduler's state machine can tell me what to look for in the logs I can search deeper. Or I can even add some log points on my installation to collect until the anomaly occurs again.
@alexakra do your blocked DAGs have processing logs in the above path? And just wondering, what's your setting for `schedule_after_task_execution`?
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[GitHub] [airflow] github-actions[bot] closed issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
github-actions[bot] closed issue #19901:
URL: https://github.com/apache/airflow/issues/19901
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[GitHub] [airflow] ephraimbuddy commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
ephraimbuddy commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989672432
> > What do you mean by no scheduling? Is it that dagruns are not created at all?
>
> There is a record in the "dag" table in which `next_dagrun_create_after` remains `null`. In the description above, I pointed to the exact line in the code. It was changed in 2.2. And "If this condition is evaluated when a state is "running" then it is incorrect.", i.e. condition should be ">" instead of ">=". When `next_dagrun_create_after` remains `null`, the dag doesn't run/scheduled anymore.
max_active_runs is for dag_runs in `running` state. Do you mean that when you set `max_active_runs=1` in your DAG that you don't see any dagruns in `running` state? I'm trying to understand your issue. What is the issue? Not asking for the code explanation but the issue you face when you use `max_active_runs` in your dag
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[GitHub] [airflow] holyachon commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
holyachon commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-1031131364
@easontm Thank you for your reply :)
I think I don't have the confidence to manage that DAG well..
Fortunately, the airflow's bug related the problem in this issue was found.
Therefore, after https://github.com/apache/airflow/pull/21214 PR is merged, we can all be happy 😄
Thanks again for sharing your idea!
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[GitHub] [airflow] ephraimbuddy closed issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
ephraimbuddy closed issue #19901:
URL: https://github.com/apache/airflow/issues/19901
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[GitHub] [airflow] alexakra commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989769506
[test_dag.py.txt](https://github.com/apache/airflow/files/7684689/test_dag.py.txt)
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[GitHub] [airflow] easontm commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
easontm commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989027957
Just out of curiosity, does the scheduler create another run if you modify the file?
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[GitHub] [airflow] alexakra commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989589446
> Just out of curiosity, does the scheduler create another run if you modify the file?
yes, just another single run
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[GitHub] [airflow] ephraimbuddy commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
ephraimbuddy commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989082654
@alexakra This issue need more information. What do you mean by no scheduling? Is it that dagruns are not created at all? Please explain with more information
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[GitHub] [airflow] ephraimbuddy commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
ephraimbuddy commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989734385
> Yes, when I set `max_active_runs=1` in a DAG, I don't see any dagruns in running state. It is not triggered anymore after it ran only once.
This looks like an issue with your schedule interval and not max_active_runs because I have a dag with max_active_runs=1 that is running correctly with airflow 2.2.2.
Can you share your DAG file
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[GitHub] [airflow] alexakra commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
alexakra commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-989689023
Yes, when I set `max_active_runs=1` in a DAG, I don't see any dagruns in running state. It is not triggered anymore after it ran only once.
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[GitHub] [airflow] ephraimbuddy commented on issue #19901: No scheduling when max_active_runs is 1
Posted by GitBox <gi...@apache.org>.
ephraimbuddy commented on issue #19901:
URL: https://github.com/apache/airflow/issues/19901#issuecomment-990092176
> Could it be related to an upgraded from 2.1.4?
Not sure but check your logs if there's anything you can see
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