providers/microsoft/azure/docs/connections/adl.rst
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.. _howto/connection:azure_data_lake:
The Microsoft Azure Data Lake connection type enables the Azure Data Lake Integrations.
There is one way to connect to Azure Data Lake using Airflow.
token credentials <https://docs.microsoft.com/en-us/azure/developer/python/azure-sdk-authenticate?tabs=cmd#authenticate-with-token-credentials>_
i.e. add specific credentials (client_id, secret, tenant) and account name to the Airflow connection.DefaultAzureCredential <https://docs.microsoft.com/en-us/python/api/overview/azure/identity-readme?view=azure-python#defaultazurecredential>_.
This includes a mechanism to try different options to authenticate: Managed System Identity, environment variables, authentication through Azure CLI...All hooks and operators related to Microsoft Azure Data Lake use azure_data_lake_default by default.
Login (optional)
Specify the client_id used for the initial connection.
This is needed for token credentials authentication mechanism.
It can be left out to fall back on DefaultAzureCredential.
Password (optional)
Specify the secret used for the initial connection.
This is only needed for token credentials authentication mechanism.
It can be left out to fall back on DefaultAzureCredential.
Extra (optional) Specify the extra parameters (as json dictionary) that can be used in Azure Data Lake connection. The following parameters are all optional:
* ``tenant``: (optional) Specify the tenant to use.
This is needed for *token credentials* authentication mechanism.
It can be left out to fall back on ``DefaultAzureCredential``.
* ``account_name``: Specify the azure data lake account name.
This is sometimes called the ``store_name``
When specifying the connection in environment variable you should specify it using URI syntax.
Note that all components of the URI should be URL-encoded.
For example:
.. code-block:: bash
export AIRFLOW_CONN_AZURE_DATA_LAKE_DEFAULT='azure-data-lake://client%20id:secret@?tenant=tenant+id&account_name=store+name'