[ISSUE] FeatureEngineeringClient does not authenticate using OAuth profile from .dbksconfig while WorkspaceClient works
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Valutazione
- Difficoltà
- 4/5
- Tempo stimato
- 3-5 giorni
- Idoneità per principianti
- 48/100
- Tipo di issue
- Bug
- Chiarezza
- Abbastanza chiara
- Stato di attività
- Attiva
- Stack tecnologico
- python
- Ambito
- authentication, backend-api-design
Direzione di ricerca
Start by tracing how FeatureEngineeringClient constructs or obtains its Databricks SDK client and resolves credentials, then compare that path with WorkspaceClient's OAuth profile handling. Reproduce with the supplied .dbksconfig profile and compare the failing Feature Engineering call with the working WorkspaceClient call. Done means FeatureEngineeringClient authenticates successfully using the same profile; the issue does not name relevant source files or tests.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
FeatureEngineeringClient does not authenticate using OAuth profile from .dbksconfig while WorkspaceClient works
Description
FeatureEngineeringClient cannot authenticate when credentials are provided through a Databricks OAuth profile configured in .dbksconfig and selected via environment variables/profile resolution. The client works with SPARK_REMOTE environment variable.
The same authentication configuration works correctly with both WorkspaceClient. However, Feature Engineering API calls fail with:
{
"error_code": 401,
"message": "Credential was not sent or was of an unsupported type for this API. [ReqId: 53b397d5-e1f2-406c-b3fc-1805a73e19fc]"
}
Additionally, the behavior appears consistent with the issue discussed in the Databricks Community thread below:
This suggests that FeatureEngineeringClient may not be resolving OAuth credentials from profiles in the same way as WorkspaceClient and Databricks Connect.
Reproduction
A minimal example is shown below.
from databricks.sdk import WorkspaceClient
from databricks.feature_engineering import FeatureEngineeringClient
import os
os.environ["DATABRICKS_CONFIG_PROFILE"] = "DEFAULT" # or your profile name
# Uses OAuth profile from .dbksconfig
w = WorkspaceClient()
# Works correctly
print(w.current_user.me())
# Fails with 401
fe = FeatureEngineeringClient()
fe.read_table(
name="<catalog>.<schema>.<feature_table>"
)
Authentication is configured through .dbksconfig and selected through the standard Databricks SDK profile/environment-variable mechanism.
For comparison, Databricks Connect using the same profile successfully creates a Spark session and executes queries.
Expected behavior
FeatureEngineeringClient should resolve credentials from the same OAuth profile mechanism supported by WorkspaceClient and Databricks Connect.
If the profile is valid and successfully used by the Databricks SDK, Feature Engineering operations should authenticate successfully without requiring alternative authentication methods or additional configuration.
Is it a regression?
Unknown.
This is the first version tested.
Observed environment:
- databricks-feature-engineering==0.18.2
- databricks-sdk==0.154.0
- databricks-connect==15.4.26
- mlflow==3.4.0
Debug Logs
Authentication failure returned by the API:
{
"error_code": 401,
"message": "Credential was not sent or was of an unsupported type for this API. [ReqId: 53b397d5-e1f2-406c-b3fc-1805a73e19fc]"
}
Additional DEBUG logs can be provided if required.
Other Information
- OS: Windows 11
- Python: 3.12.0
- databricks-feature-engineering: 0.18.2
- databricks-sdk: 0.154.0
- databricks-connect: 15.4.26
- mlflow: 3.4.0
Additional context
The following components work successfully using the same OAuth profile:
databricks.sdk.WorkspaceClient- Databricks Connect (
spark.remote)
Only Feature Engineering API calls fail with an authentication error.
The behavior may indicate that FeatureEngineeringClient is not fully honoring the Databricks SDK OAuth profile configuration or is using a different credential resolution path.
- Lingua principale
- Python
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