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fix(ingestion/airflow-plugin): updated the document for developers #10633

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Jun 6, 2024
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fix(ingestion/airflow-plugin): updated the document for developers #10633

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fix(ingestion/airflow-plugin): updated the document for developers
dushayntAW Jun 2, 2024
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fix(ingestion/airflow-plugin): fixed review comments
dushayntAW Jun 5, 2024
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2 changes: 1 addition & 1 deletion docs/lineage/airflow.md
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Expand Up @@ -69,7 +69,7 @@ enabled = True # default
| -------------------------- | -------------------- | ---------------------------------------------------------------------------------------- |
| enabled | true | If the plugin should be enabled. |
| conn_id | datahub_rest_default | The name of the datahub rest connection. |
| cluster | prod | name of the airflow cluster |
| cluster | prod | name of the airflow cluster, this is equivalent to the `env` of the instance |
| capture_ownership_info | true | Extract DAG ownership. |
| capture_tags_info | true | Extract DAG tags. |
| capture_executions | true | Extract task runs and success/failure statuses. This will show up in DataHub "Runs" tab. |
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21 changes: 21 additions & 0 deletions metadata-ingestion/developing.md
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Expand Up @@ -34,6 +34,27 @@ cd metadata-ingestion-modules/airflow-plugin
../../gradlew :metadata-ingestion-modules:airflow-plugin:installDev
source venv/bin/activate
datahub version # should print "DataHub CLI version: unavailable (installed in develop mode)"

# start the airflow web server
export AIRFLOW_HOME=~/airflow
airflow webserver --port 8090 -d

# start the airflow scheduler
airflow scheduler

# access the airflow service and run any of the DAG
open http://localhost:8090/
select any DAG and click on the `play arrow` button to start the DAG
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This should be commented as this is not a shell command.


# add the debug lines in the codebase, i.e. in ./src/datahub_airflow_plugin/datahub_listener.py
logger.debug("this is the sample debug line")

# run the DAG again and you can see the debug lines in the task_run log at,
1. click on the `timestamp` in the `Last Run` column
2. select the task
3. click on the `log` option

P.S. if you are not able to see the log lines, then restart the `airflow scheduler` and rerun the DAG
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The shell command should be closed before this and a new one started after this. Please see the rendering and use different code blocks as appropriate.

```
### (Optional) Set up your Python environment for developing on Dagster Plugin

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