dosubot[bot] commented on issue #30184:
URL: https://github.com/apache/superset/issues/30184#issuecomment-2343325321
<!-- Answer -->
To correctly configure the SSAS connection in Apache Superset for domain
user authentication using Kerberos or LDAP, and ensure the connection is fully
registered and usable, follow these steps:
### 1. Install the Required Database Driver
Ensure you have the necessary driver for SSAS. Since SSAS is not explicitly
listed, you may need to find a compatible SQLAlchemy dialect and Python driver
for SSAS.
### 2. Configure Kerberos Authentication
In the `Secure Extra` field of the database connection configuration, add
the following JSON configuration for Kerberos authentication:
```json
{
"auth_method": "kerberos",
"auth_params": {
"service_name": "superset",
"config": "/path/to/krb5.config"
}
}
```
Ensure you have the `trino[kerberos]` or `trino[all]` package installed:
```bash
pip install trino[kerberos]
```
### 3. Configure LDAP Authentication
If you prefer LDAP, you will need to configure it similarly in the `Secure
Extra` field. However, specific details for LDAP configuration are not provided
in the given context.
### 4. Register the Connection
After configuring the authentication, register the connection through the
Superset web UI:
- Go to **Settings -> Data: Database Connections**.
- Click the **+DATABASE** button.
- Fill in the connection details, including the connection string and the
`Secure Extra` field.
### 5. Display the Entire SSAS Data
Once the connection is successfully tested and saved, Superset should be
able to display all databases and dimensions available in SSAS to the
authenticated user.
### Example Configuration for Kerberos in the `Secure Extra` Field
```json
{
"auth_method": "kerberos",
"auth_params": {
"service_name": "superset",
"config": "/path/to/krb5.config"
}
}
```
Ensure the connection string and other parameters are correctly set
according to the SSAS driver documentation
<sup>[[1]](https://github.com/apache/superset/blob/master/docs/docs/configuration/databases.mdx)</sup>.
### Custom DB Engine Spec Implementation
Your custom DB engine spec for SSAS looks good. Ensure you have implemented
the necessary methods and attributes to support metadata fetching and query
execution. Here are some key methods and attributes you might need:
#### Methods:
- `fetch_metadata`: Fetch metadata from the database.
- `execute`: Execute SQL queries against the database.
- `get_dimensions`: Fetch dimensions from SSAS.
- `get_databases`: Fetch databases from SSAS.
#### Attributes:
- `engine`: Specifies the engine type.
- `engine_name`: Specifies the engine name.
### Example Custom DB Engine Spec
```python
from superset.db_engine_specs.base import BaseEngineSpec
class SSASEngineSpec(BaseEngineSpec):
engine = 'ssas'
engine_name = 'SQL Server Analysis Services'
@classmethod
def execute(cls, cursor, query, **kwargs):
cursor.execute(query)
return cursor.fetchall()
@classmethod
def get_dimensions(cls, cursor):
cursor.execute("SELECT * FROM $system.DISCOVER_DIMENSIONS")
return cursor.fetchall()
@classmethod
def get_databases(cls, cursor):
cursor.execute("SELECT * FROM $system.DISCOVER_CATALOGS")
return cursor.fetchall()
```
### Register the New Engine Spec
Add the new engine spec to the list of supported engines in Superset:
```python
# superset/config.py
from superset.db_engine_specs.ssas import SSASEngineSpec
DATABASES = {
'ssas': SSASEngineSpec,
# other database specs
}
```
By following these steps, you should be able to configure the SSAS
connection in Superset for domain user authentication, register the connection,
and display the entire SSAS data to the user upon successful authentication
<sup>[[1]](https://github.com/apache/superset/blob/master/docs/docs/configuration/databases.mdx)</sup><sup>[[2]](https://github.com/apache/superset/blob/master/superset/db_engine_specs/__init__.py)</sup>.
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