dosubot[bot] commented on issue #35085:
URL: https://github.com/apache/superset/issues/35085#issuecomment-3274245711

   <!-- Answer -->
   This is a known issue in Superset 4.1.3, especially with Databricks and 
other slow or non-responsive databases. The root cause is that Superset relies 
on Python-level timeouts, which do not reliably interrupt native/ODBC driver 
calls—so if the database or driver hangs, Superset can become unresponsive 
until the underlying call returns or the process is killed. This is 
particularly problematic with Databricks, where datasource creation or query 
execution can get stuck in long loops or blocked calls, making the UI hang or 
requests time out, even though the operation may eventually succeed after a 
long delay ([details](https://github.com/apache/superset/issues/33388)).
   
   You can try to mitigate this by enabling asynchronous query execution (with 
Celery), tuning timeouts like `SQLLAB_TIMEOUT`, `SUPERSET_WEBSERVER_TIMEOUT`, 
and increasing Nginx/Gunicorn timeouts ([config 
example](https://github.com/apache/superset/issues/33218)). However, these 
settings do not guarantee protection against hangs caused by unresponsive 
database drivers.
   
   Recent Superset releases (after 4.1.3) have added improvements:  
   - `SQLLAB_QUERY_RESULT_TIMEOUT` lets you set a timeout for fetching query 
results in SQL Lab ([PR #29959](https://github.com/apache/superset/pull/29959)).
   - `SQLLAB_PAYLOAD_MAX_MB` limits result payload size to prevent browser 
hangs with large results ([PR 
#30522](https://github.com/apache/superset/pull/30522)).
   
   These help with some causes of unresponsiveness, but do not fully solve the 
issue with slow or non-responsive databases at the driver level. If your 
database/driver supports connection or read timeouts, set those at the driver 
or connection string level. Otherwise, monitor for future Superset releases 
with improved handling for these scenarios.
   
   
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