[jira] [Created] (AIRFLOW-4796) DOCO - DaskExecutor logs

["t oo (JIRA)" <ji...@apache.org>]

t oo created AIRFLOW-4796:
-----------------------------

             Summary: 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


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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