-
Notifications
You must be signed in to change notification settings - Fork 13.9k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Several statsd timers record seconds rather than milliseconds #10629
Labels
kind:bug
This is a clearly a bug
priority:critical
Showstopper bug that should be patched immediately
Milestone
Comments
mjpieters
added a commit
to mjpieters/airflow
that referenced
this issue
Nov 21, 2020
I think there may be one left -- in DagBag.collect_dags
Oh, that's a guage. |
ashb
added a commit
to astronomer/airflow
that referenced
this issue
Dec 5, 2020
Dags with a schedule interval of None, or `@once` don't have a following schedule, so we can't realistically calculate this metric. Additionally, this changes the emitted metric from seconds to milliseconds -- all timers to statsd should be in milliseconds -- this is what Statsd and apps that consume data from there expect. See apache#10629 for more details. This will be a "breaking" change from 1.10.14, where the metric was back-ported to, but was (incorrectly) emitting seconds.
ashb
added a commit
that referenced
this issue
Dec 5, 2020
) Dags with a schedule interval of None, or `@once` don't have a following schedule, so we can't realistically calculate this metric. Additionally, this changes the emitted metric from seconds to milliseconds -- all timers to statsd should be in milliseconds -- this is what Statsd and apps that consume data from there expect. See #10629 for more details. This will be a "breaking" change from 1.10.14, where the metric was back-ported to, but was (incorrectly) emitting seconds.
kaxil
pushed a commit
that referenced
this issue
Dec 7, 2020
) Dags with a schedule interval of None, or `@once` don't have a following schedule, so we can't realistically calculate this metric. Additionally, this changes the emitted metric from seconds to milliseconds -- all timers to statsd should be in milliseconds -- this is what Statsd and apps that consume data from there expect. See #10629 for more details. This will be a "breaking" change from 1.10.14, where the metric was back-ported to, but was (incorrectly) emitting seconds. (cherry picked from commit 4a02e0a)
kaxil
pushed a commit
that referenced
this issue
Jan 22, 2021
cfei18
pushed a commit
to cfei18/incubator-airflow
that referenced
this issue
Mar 5, 2021
…che#12835) Dags with a schedule interval of None, or `@once` don't have a following schedule, so we can't realistically calculate this metric. Additionally, this changes the emitted metric from seconds to milliseconds -- all timers to statsd should be in milliseconds -- this is what Statsd and apps that consume data from there expect. See apache#10629 for more details. This will be a "breaking" change from 1.10.14, where the metric was back-ported to, but was (incorrectly) emitting seconds. (cherry picked from commit 4a02e0a)
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Labels
kind:bug
This is a clearly a bug
priority:critical
Showstopper bug that should be patched immediately
Apache Airflow version: 1.10.11
What happened:
Statsd timers for 3 categories are reporting values 1000x off as the code passes seconds, rather rather than milliseconds (or a
timedelta()
instance) toStatsClient.timing()
.What you expected to happen:
The timings should be reported in milliseconds.
How to reproduce it:
Enable the
statsd
client and track reporting timings for:dag.loading-duration.*
(emitted frommodels/dagbag.py
)dag.<dag_id>.<task_id>.duration
(emitted frommodels/taskinstance.py
)dag_processing.last_duration.<filename>
(emitted fromutils/dag_processing.py
) and it's deprecated aliasdag_processing.last_runtime.*
Anything else we need to know:
This was reported before, for the
dag_processing.last_*
stats, at https://issues.apache.org/jira/browse/AIRFLOW-6088.The accompanying pull request #6682, fixed 2 out of 3 of these, but only for Airflow 2.0.
The text was updated successfully, but these errors were encountered: