You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@airflow.apache.org by "Daniel Imberman (JIRA)" <ji...@apache.org> on 2019/04/18 22:36:00 UTC
[jira] [Commented] (AIRFLOW-4346) Kubernetes Executor Fails for
Large Wide DAGs
[ https://issues.apache.org/jira/browse/AIRFLOW-4346?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16821541#comment-16821541 ]
Daniel Imberman commented on AIRFLOW-4346:
------------------------------------------
[~vcastane] can you post your scheduler logs? When tasks fail the scheduler shouldn't need to be aware of those failures as long as the DB is updated.
> Kubernetes Executor Fails for Large Wide DAGs
> ---------------------------------------------
>
> Key: AIRFLOW-4346
> URL: https://issues.apache.org/jira/browse/AIRFLOW-4346
> Project: Apache Airflow
> Issue Type: Bug
> Components: DAG, executor, kubernetes
> Affects Versions: 1.10.2, 1.10.3
> Reporter: Vincent Castaneda
> Priority: Blocker
> Attachments: configmap-airflow-share.yaml, wide_dag_bash_test.py, wide_dag_test_100_300.py, wide_dag_test_300_300.py
>
>
> When running large DAGs–those with parallelism of over 100 task instances to be running concurrently--several tasks fail on the executor and are reported to the database, but the scheduler is never aware of them failing.
> Attached are:
> - A test DAG that we can use to replicate the issue.
> - The configmap-airflow.yaml file
> I will be available to answer any other questions that are raised about our configuration. We are running this on GKE and giving the scheduler and web pod a base 100m for execution.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)