dosubot[bot] commented on issue #43764:
URL: https://github.com/apache/superset/issues/43764#issuecomment-5495508982

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   <!-- Answer -->
   @Devika7733 yes — the import does more than just upload metadata. It runs 
live database operations for every dataset (and every referenced database 
connection) in the ZIP, which is why 293 datasets pushed you past the gunicorn 
timeout.
   
   Here's what happens under the hood:
   
   **For each database** referenced in the bundle, 
[`import_database()`](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/database/importers/v1/utils.py#L74-L93)
 connects to your external database and calls 
[`add_permissions()`](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/database/utils.py#L54-L104),
 which enumerates all schemas (and catalogs, for engines that support them) to 
register access permissions. This issues real connections/queries against the 
source database.
   
   **For each dataset**, 
[`import_dataset()`](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/dataset/importers/v1/utils.py#L105-L192):
   
   - Writes/updates the `SqlaTable` row (and its columns/metrics) via 
`SqlaTable.import_from_dict()` 
[[1]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/dataset/importers/v1/utils.py#L159-L170).
   - Calls 
[`dataset.database.has_table()`](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/models/core.py#L1078-L1081),
 which opens a connection to the source database via SQLAlchemy's engine and 
checks whether the table exists 
[[2]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/dataset/importers/v1/utils.py#L175-L184).
   - If a `data` URI is present and the table doesn't already exist (or 
`force_data` is set), it downloads and loads CSV data into the table 
[[3]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/dataset/importers/v1/utils.py#L186-L187).
 In your case this branch is likely skipped since you're importing existing 
datasets, but the `has_table` existence check still runs a live query per 
dataset.
   
   So with 293 datasets, you're triggering roughly that many live "does this 
table exist" round-trips to your source database(s), plus schema/catalog 
enumeration for each connected database — all inside a single synchronous HTTP 
request. The [`_import` 
method](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/dataset/importers/v1/__init__.py#L44-L72)
 processes databases first, then iterates over every dataset. The entire 
operation is wrapped in [one 
transaction](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/commands/importers/v1/__init__.py#L82-L91),
 and there's [no async/Celery 
offload](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/datasets/api.py#L819-L951)
 for the `/api/v1/dataset/import/` endpoint, so everything must complete within 
the gunicorn worker timeout. The default timeout in Superset's container 
entrypoint is [60 seconds](https://gith
 
ub.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/docker/entrypoints/run-server.sh#L30),
 so bumping `--timeout` to 300 is the expected workaround.
   
   If you want to reduce the load rather than just raising the timeout, 
splitting the ZIP into smaller batches would cut down the number of live 
table-existence checks and permission-enumeration calls per request.
   
   
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