GitHub user dosubot[bot] added a comment to the discussion: Why i try to select native filters options results in Network error: Network error while attempting to fetch resource in superset5.0
<!-- Answer --> This is a common issue when dashboards have many native filters. Each filter triggers a separate database query to populate its dropdown values, and with 10+ filters firing concurrently, the backend can get overwhelmed — resulting in timeouts that surface as "Network error while attempting to fetch resource" [[1]](https://github.com/apache/superset/discussions/33223#discussioncomment-12927442). Here are the most likely causes and solutions: **1. Increase timeout settings** The default `SUPERSET_WEBSERVER_TIMEOUT` is 60 seconds [[2]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/config.py#L172-L176). With many filters, queries may collectively exceed this. In your `superset_config.py`: ```python SUPERSET_WEBSERVER_TIMEOUT = 120 # or higher ``` Also ensure your reverse proxy (Nginx, etc.) timeout is set higher than this value. **2. Increase worker capacity** More Gunicorn workers/threads help handle concurrent filter requests [[3]](https://github.com/apache/superset/issues/35085): ``` SERVER_WORKER_AMOUNT = 12 SERVER_THREADS_AMOUNT = 15 ``` **3. Enable caching** Configure Redis caching to serve filter values from cache on subsequent loads, reducing database pressure. **4. Use filter dependencies** If some filters are related, configure parent-child dependencies between them. This serializes queries (reducing concurrent load) and narrows child filter queries using parent filter values [[4]](https://github.com/apache/superset/issues/36676). **5. Set a fetch values predicate** On your datasets, configure the "Autocomplete query predicate" (`fetch_values_predicate`) to limit the scope of filter value queries [[5]](https://github.com/apache/superset/blob/829e4d92d91ceae4b43b1ed3b063ffe45377799c/superset/models/helpers.py#L1359-L1360). **6. Reduce filter row limits** In `superset_config.py`, lower the max rows fetched for filter dropdowns: ```python NATIVE_FILTER_DEFAULT_ROW_LIMIT = 500 # default is 1000 ``` **Database-specific notes:** - **DuckDB**: Doesn't support concurrent queries — pin to `duckdb-engine==0.14.1` [[6]](https://github.com/apache/superset/issues/31978) - **BigQuery**: Make filters depend on a time filter to pass partition filters [[4]](https://github.com/apache/superset/issues/36676) Could you share which database you're using and what your current timeout/proxy settings look like? That would help narrow down the root cause further. <!-- Dosu Comment Footer --> *To reply, just mention [@dosu](https://go.dosu.dev/dosubot?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=reply-with-mention&utm_term=apache%2Fsuperset).* --- Share context across your team and agents. Try [Dosu](https://dosu.dev?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-tagline&utm_term=apache%2Fsuperset). [](https://app.dosu.dev/response-feedback?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-feedback&utm_term=apache%2Fsuperset&message_id=a783fd1e-27ef-4a20-97a1-02a1de36710c) [](https://github.dosu.com/apache/superset?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-learn-repo&utm_term=apache%2Fsuperset) [](https://app.dosu.dev/signup?referrer=openSource&source=github-footer&utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-add-team&utm_term=apache%2Fsuperset) GitHub link: https://github.com/apache/superset/discussions/40703#discussioncomment-17165100 ---- This is an automatically sent email for [email protected]. To unsubscribe, please send an email to: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
