Airflow task with null status
I'am having an issue with airflow when running it on a 24xlarge machine on EC2.
I must note that the parallelism level is 256.
For some days the dagrun finishes with status 'failed' for two undetermined reasons :
Some task has the status 'upstream_failed', which is not true because we can see clearly that all the previous steps where successful.
Other tasks have not the status 'null', they have not started yet and they cause the dagrun to fail.
I must note that the logs for both of these tasks are empty
And here is the tast instance details for these cases :
Any solutions please ?
python amazon-s3 airflow airflow-scheduler
add a comment |
I'am having an issue with airflow when running it on a 24xlarge machine on EC2.
I must note that the parallelism level is 256.
For some days the dagrun finishes with status 'failed' for two undetermined reasons :
Some task has the status 'upstream_failed', which is not true because we can see clearly that all the previous steps where successful.
Other tasks have not the status 'null', they have not started yet and they cause the dagrun to fail.
I must note that the logs for both of these tasks are empty
And here is the tast instance details for these cases :
Any solutions please ?
python amazon-s3 airflow airflow-scheduler
Operator is also null?
– mad_
Nov 15 '18 at 10:44
Yes it is always null
– I.Chorfi
Nov 15 '18 at 17:13
add a comment |
I'am having an issue with airflow when running it on a 24xlarge machine on EC2.
I must note that the parallelism level is 256.
For some days the dagrun finishes with status 'failed' for two undetermined reasons :
Some task has the status 'upstream_failed', which is not true because we can see clearly that all the previous steps where successful.
Other tasks have not the status 'null', they have not started yet and they cause the dagrun to fail.
I must note that the logs for both of these tasks are empty
And here is the tast instance details for these cases :
Any solutions please ?
python amazon-s3 airflow airflow-scheduler
I'am having an issue with airflow when running it on a 24xlarge machine on EC2.
I must note that the parallelism level is 256.
For some days the dagrun finishes with status 'failed' for two undetermined reasons :
Some task has the status 'upstream_failed', which is not true because we can see clearly that all the previous steps where successful.
Other tasks have not the status 'null', they have not started yet and they cause the dagrun to fail.
I must note that the logs for both of these tasks are empty
And here is the tast instance details for these cases :
Any solutions please ?
python amazon-s3 airflow airflow-scheduler
python amazon-s3 airflow airflow-scheduler
edited Nov 16 '18 at 17:09
I.Chorfi
asked Nov 15 '18 at 10:15
I.ChorfiI.Chorfi
335
335
Operator is also null?
– mad_
Nov 15 '18 at 10:44
Yes it is always null
– I.Chorfi
Nov 15 '18 at 17:13
add a comment |
Operator is also null?
– mad_
Nov 15 '18 at 10:44
Yes it is always null
– I.Chorfi
Nov 15 '18 at 17:13
Operator is also null?
– mad_
Nov 15 '18 at 10:44
Operator is also null?
– mad_
Nov 15 '18 at 10:44
Yes it is always null
– I.Chorfi
Nov 15 '18 at 17:13
Yes it is always null
– I.Chorfi
Nov 15 '18 at 17:13
add a comment |
2 Answers
2
active
oldest
votes
This can happen when the task status was manually changed (likely through the "Mark Success" option), or forced into a state (as in upstream_failed
) and the task never receives a hostname
value on the record and wouldn't have any logs or PID
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
Theupstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.
– joeb
Nov 17 '18 at 0:49
add a comment |
The other case where I've experienced the second condition ("Other tasks have not the status 'null'"), is when the task instance has changed, and specifically changed operator type.
I'm hoping you already got an answer / were able to move on. I've been stuck on this issue a few times in the last month, so I figured I would document what I ended up doing to solve the issue.
Example:
- Task Instance originally is an instance of a SubDag Operator
- Requirements cause the type of the operator to change from a SubDag Operator to a Python Operator
- After the change, the Python Operator is set to state NULL
As best I can piece together, what's happening is:
- Airflow is introspecting the operator associated with each task
- Each task instance is logged into the database table
task_instance
- This table has an attribute called
operator
- This table has an attribute called
- When the scheduler re-introspects the code, it looks for the
task_instance
with the correct operator type; not seeing it, it updates the associated database record(s) as state = 'removed' - When the DAG subsequently schedules, airflow
You can see tasks impacted by this process with the query:
SELECT *
FROM task_instance
WHERE state = 'removed'
It looks like there's been work on this issue for airflow 1.10:
- https://github.com/aliceabe/incubator-airflow/commit/b6f6c732700d1e53793c96ca74b0e2dc1e10405e
That being said, I'm not 100% sure based on the commits that I can find that it would resolve this issue. It seems like the general philosophy is still "when a DAG changes, you should increment / change the DAG name".
I don't love that solution, because it makes it hard to iterate on what is fundamentally one pipeline. The alternative I used was to follow (partially) the recommendations from Astronomer and "blow out" the DAG history. In order to do that, you need to:
- Stop the scheduler
Delete the history from the dag- This should result in the DAG completely disappearing from the web UI
- If it doesn't completely disappear, somewhere the scheduler is still running
- Restart the scheduler
- Note: if you're running the DAG on a schedule, be prepared for it to backfill / catchup / run its latest schedule, because you've removed the history
- If you don't want it to do this, Astronomer's "Fast Forward a DAG" suggestions could be applied
add a comment |
Your Answer
StackExchange.ifUsing("editor", function ()
StackExchange.using("externalEditor", function ()
StackExchange.using("snippets", function ()
StackExchange.snippets.init();
);
);
, "code-snippets");
StackExchange.ready(function()
var channelOptions =
tags: "".split(" "),
id: "1"
;
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function()
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled)
StackExchange.using("snippets", function()
createEditor();
);
else
createEditor();
);
function createEditor()
StackExchange.prepareEditor(
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader:
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
,
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
);
);
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53317104%2fairflow-task-with-null-status%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
This can happen when the task status was manually changed (likely through the "Mark Success" option), or forced into a state (as in upstream_failed
) and the task never receives a hostname
value on the record and wouldn't have any logs or PID
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
Theupstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.
– joeb
Nov 17 '18 at 0:49
add a comment |
This can happen when the task status was manually changed (likely through the "Mark Success" option), or forced into a state (as in upstream_failed
) and the task never receives a hostname
value on the record and wouldn't have any logs or PID
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
Theupstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.
– joeb
Nov 17 '18 at 0:49
add a comment |
This can happen when the task status was manually changed (likely through the "Mark Success" option), or forced into a state (as in upstream_failed
) and the task never receives a hostname
value on the record and wouldn't have any logs or PID
This can happen when the task status was manually changed (likely through the "Mark Success" option), or forced into a state (as in upstream_failed
) and the task never receives a hostname
value on the record and wouldn't have any logs or PID
answered Nov 16 '18 at 1:51
joebjoeb
2,22611519
2,22611519
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
Theupstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.
– joeb
Nov 17 '18 at 0:49
add a comment |
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
Theupstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.
– joeb
Nov 17 '18 at 0:49
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
This is weird, because there was no manual intervention that took place.
– I.Chorfi
Nov 16 '18 at 17:09
The
upstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.– joeb
Nov 17 '18 at 0:49
The
upstream_failed
state is applied to tasks where they're unable to run due to failed dependencies.– joeb
Nov 17 '18 at 0:49
add a comment |
The other case where I've experienced the second condition ("Other tasks have not the status 'null'"), is when the task instance has changed, and specifically changed operator type.
I'm hoping you already got an answer / were able to move on. I've been stuck on this issue a few times in the last month, so I figured I would document what I ended up doing to solve the issue.
Example:
- Task Instance originally is an instance of a SubDag Operator
- Requirements cause the type of the operator to change from a SubDag Operator to a Python Operator
- After the change, the Python Operator is set to state NULL
As best I can piece together, what's happening is:
- Airflow is introspecting the operator associated with each task
- Each task instance is logged into the database table
task_instance
- This table has an attribute called
operator
- This table has an attribute called
- When the scheduler re-introspects the code, it looks for the
task_instance
with the correct operator type; not seeing it, it updates the associated database record(s) as state = 'removed' - When the DAG subsequently schedules, airflow
You can see tasks impacted by this process with the query:
SELECT *
FROM task_instance
WHERE state = 'removed'
It looks like there's been work on this issue for airflow 1.10:
- https://github.com/aliceabe/incubator-airflow/commit/b6f6c732700d1e53793c96ca74b0e2dc1e10405e
That being said, I'm not 100% sure based on the commits that I can find that it would resolve this issue. It seems like the general philosophy is still "when a DAG changes, you should increment / change the DAG name".
I don't love that solution, because it makes it hard to iterate on what is fundamentally one pipeline. The alternative I used was to follow (partially) the recommendations from Astronomer and "blow out" the DAG history. In order to do that, you need to:
- Stop the scheduler
Delete the history from the dag- This should result in the DAG completely disappearing from the web UI
- If it doesn't completely disappear, somewhere the scheduler is still running
- Restart the scheduler
- Note: if you're running the DAG on a schedule, be prepared for it to backfill / catchup / run its latest schedule, because you've removed the history
- If you don't want it to do this, Astronomer's "Fast Forward a DAG" suggestions could be applied
add a comment |
The other case where I've experienced the second condition ("Other tasks have not the status 'null'"), is when the task instance has changed, and specifically changed operator type.
I'm hoping you already got an answer / were able to move on. I've been stuck on this issue a few times in the last month, so I figured I would document what I ended up doing to solve the issue.
Example:
- Task Instance originally is an instance of a SubDag Operator
- Requirements cause the type of the operator to change from a SubDag Operator to a Python Operator
- After the change, the Python Operator is set to state NULL
As best I can piece together, what's happening is:
- Airflow is introspecting the operator associated with each task
- Each task instance is logged into the database table
task_instance
- This table has an attribute called
operator
- This table has an attribute called
- When the scheduler re-introspects the code, it looks for the
task_instance
with the correct operator type; not seeing it, it updates the associated database record(s) as state = 'removed' - When the DAG subsequently schedules, airflow
You can see tasks impacted by this process with the query:
SELECT *
FROM task_instance
WHERE state = 'removed'
It looks like there's been work on this issue for airflow 1.10:
- https://github.com/aliceabe/incubator-airflow/commit/b6f6c732700d1e53793c96ca74b0e2dc1e10405e
That being said, I'm not 100% sure based on the commits that I can find that it would resolve this issue. It seems like the general philosophy is still "when a DAG changes, you should increment / change the DAG name".
I don't love that solution, because it makes it hard to iterate on what is fundamentally one pipeline. The alternative I used was to follow (partially) the recommendations from Astronomer and "blow out" the DAG history. In order to do that, you need to:
- Stop the scheduler
Delete the history from the dag- This should result in the DAG completely disappearing from the web UI
- If it doesn't completely disappear, somewhere the scheduler is still running
- Restart the scheduler
- Note: if you're running the DAG on a schedule, be prepared for it to backfill / catchup / run its latest schedule, because you've removed the history
- If you don't want it to do this, Astronomer's "Fast Forward a DAG" suggestions could be applied
add a comment |
The other case where I've experienced the second condition ("Other tasks have not the status 'null'"), is when the task instance has changed, and specifically changed operator type.
I'm hoping you already got an answer / were able to move on. I've been stuck on this issue a few times in the last month, so I figured I would document what I ended up doing to solve the issue.
Example:
- Task Instance originally is an instance of a SubDag Operator
- Requirements cause the type of the operator to change from a SubDag Operator to a Python Operator
- After the change, the Python Operator is set to state NULL
As best I can piece together, what's happening is:
- Airflow is introspecting the operator associated with each task
- Each task instance is logged into the database table
task_instance
- This table has an attribute called
operator
- This table has an attribute called
- When the scheduler re-introspects the code, it looks for the
task_instance
with the correct operator type; not seeing it, it updates the associated database record(s) as state = 'removed' - When the DAG subsequently schedules, airflow
You can see tasks impacted by this process with the query:
SELECT *
FROM task_instance
WHERE state = 'removed'
It looks like there's been work on this issue for airflow 1.10:
- https://github.com/aliceabe/incubator-airflow/commit/b6f6c732700d1e53793c96ca74b0e2dc1e10405e
That being said, I'm not 100% sure based on the commits that I can find that it would resolve this issue. It seems like the general philosophy is still "when a DAG changes, you should increment / change the DAG name".
I don't love that solution, because it makes it hard to iterate on what is fundamentally one pipeline. The alternative I used was to follow (partially) the recommendations from Astronomer and "blow out" the DAG history. In order to do that, you need to:
- Stop the scheduler
Delete the history from the dag- This should result in the DAG completely disappearing from the web UI
- If it doesn't completely disappear, somewhere the scheduler is still running
- Restart the scheduler
- Note: if you're running the DAG on a schedule, be prepared for it to backfill / catchup / run its latest schedule, because you've removed the history
- If you don't want it to do this, Astronomer's "Fast Forward a DAG" suggestions could be applied
The other case where I've experienced the second condition ("Other tasks have not the status 'null'"), is when the task instance has changed, and specifically changed operator type.
I'm hoping you already got an answer / were able to move on. I've been stuck on this issue a few times in the last month, so I figured I would document what I ended up doing to solve the issue.
Example:
- Task Instance originally is an instance of a SubDag Operator
- Requirements cause the type of the operator to change from a SubDag Operator to a Python Operator
- After the change, the Python Operator is set to state NULL
As best I can piece together, what's happening is:
- Airflow is introspecting the operator associated with each task
- Each task instance is logged into the database table
task_instance
- This table has an attribute called
operator
- This table has an attribute called
- When the scheduler re-introspects the code, it looks for the
task_instance
with the correct operator type; not seeing it, it updates the associated database record(s) as state = 'removed' - When the DAG subsequently schedules, airflow
You can see tasks impacted by this process with the query:
SELECT *
FROM task_instance
WHERE state = 'removed'
It looks like there's been work on this issue for airflow 1.10:
- https://github.com/aliceabe/incubator-airflow/commit/b6f6c732700d1e53793c96ca74b0e2dc1e10405e
That being said, I'm not 100% sure based on the commits that I can find that it would resolve this issue. It seems like the general philosophy is still "when a DAG changes, you should increment / change the DAG name".
I don't love that solution, because it makes it hard to iterate on what is fundamentally one pipeline. The alternative I used was to follow (partially) the recommendations from Astronomer and "blow out" the DAG history. In order to do that, you need to:
- Stop the scheduler
Delete the history from the dag- This should result in the DAG completely disappearing from the web UI
- If it doesn't completely disappear, somewhere the scheduler is still running
- Restart the scheduler
- Note: if you're running the DAG on a schedule, be prepared for it to backfill / catchup / run its latest schedule, because you've removed the history
- If you don't want it to do this, Astronomer's "Fast Forward a DAG" suggestions could be applied
answered Feb 27 at 0:45
Adam BethkeAdam Bethke
56111021
56111021
add a comment |
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53317104%2fairflow-task-with-null-status%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Operator is also null?
– mad_
Nov 15 '18 at 10:44
Yes it is always null
– I.Chorfi
Nov 15 '18 at 17:13