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https://issues.apache.org/jira/browse/AIRFLOW-4796?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17003386#comment-17003386
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t oo commented on AIRFLOW-4796:
-------------------------------
[~jlowin] [~bolke] [~mariusvniekerk] cc
> 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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