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From "Darren Weber (Jira)" <j...@apache.org>
Subject [jira] [Commented] (AIRFLOW-4796) DOCO - DaskExecutor logs
Date Thu, 02 Jan 2020 17:53:00 GMT

    [ https://issues.apache.org/jira/browse/AIRFLOW-4796?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17006987#comment-17006987
] 

Darren Weber commented on AIRFLOW-4796:
---------------------------------------

I don't know enough to propose any implementation details to solve this, I can only suggest
the following tip to follow up on somehow.  If the airflow task has access to the dask-executor-client
and possibly also a worker-id, then it might be able to use a client call to get the logs
and parse them for relevant log details, e.g.

- [https://distributed.dask.org/en/latest/api.html#distributed.Client.get_worker_logs]

> DOCO - DaskExecutor logs
> ------------------------
>
>                 Key: AIRFLOW-4796
>                 URL: https://issues.apache.org/jira/browse/AIRFLOW-4796
>             Project: Apache Airflow
>          Issue Type: Improvement
>          Components: executors, logging
>    Affects Versions: 1.10.3
>            Reporter: t oo
>            Priority: Major
>
> I have an Airflow installation (on Kubernetes). My setup uses {{DaskExecutor}}. I also
configured remote logging to S3. However when the task is running I cannot see the log, and
I get this error instead:
> *** Log file does not exist: /airflow/logs/dbt/run_dbt/2018-11-01T06:00:00+00:00/3.log
> *** Fetching from: http://airflow-worker-74d75ccd98-6g9h5:8793/log/dbt/run_dbt/2018-11-01T06:00:00+00:00/3.log
> *** Failed to fetch log file from worker. HTTPConnectionPool(host='airflow-worker-74d75ccd98-6g9h5',
port=8793): Max retries exceeded with url: /log/dbt/run_dbt/2018-11-01T06:00:00+00:00/3.log
(Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f7d0668ae80>:
Failed to establish a new connection: [Errno -2] Name or service not known',))
>  
> Once the task is done, the log is shown correctly.
> I believe what Airflow is doing is:
>  * for finished tasks read logs from s3
>  * for running tasks, connect to executor's _log server endpoint_ and show that.
> Looks like Airflow is using {{celery.worker_log_server_port}} to connect to my dask executor
to fetch logs from there.
> h3. How to configure {{DaskExecutor}} to expose _log server endpoint_?
> my configuration:
>  
>  
> core remote_logging True 
> core remote_base_log_folder s3://some-s3-path
> core executor DaskExecutor 
> dask cluster_address 127.0.0.1:8786
> celery worker_log_server_port 8793 
>  
>  
> what i verified: - verified that the log file exists and is being written to on the executor
while the task is running - called {{netstat -tunlp}} on executor container, but did not find
any extra port exposed, where logs could be served from.
>  
>  
>  
> We solved the problem by simply starting a python HTTP handler on a worker.
> Dockerfile:
>  
> RUN mkdir -p $AIRFLOW_HOME/serve
> RUN ln -s $AIRFLOW_HOME/logs $AIRFLOW_HOME/serve/log
> worker.sh (run by Docker CMD):
>  
> #!/usr/bin/env bash
> cd $AIRFLOW_HOME/serve
> python3 -m http.server 8793 &
> cd -
> dask-worker $@
>  
>  
>  
> see [https://stackoverflow.com/questions/53121401/airflow-live-executor-logs-with-daskexecutor]
>  
>  



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