Miscellaneous

Reporting a Security Vulnerability

Please report security vulnerabilities to [email protected].

In the event a community member discovers a security flaw in Superset, it is important to follow the Apache Security Guidelines and release a fix as quickly as possible before public disclosure. Reporting security vulnerabilities through the usual GitHub Issues channel is not ideal as it will publicize the flaw before a fix can be applied.

SQL Lab Async

It's possible to configure a local database to operate in async mode, to work on async related features.

To do this, you'll need to:

Add an additional database entry. We recommend you copy the connection string from the database labeled main, and then enable SQL Lab and the features you want to use. Don't forget to check the Async box
Configure a results backend, here's a local FileSystemCache example, not recommended for production, but perfect for testing (stores cache in /tmp)
python
```
from flask_caching.backends.filesystemcache import FileSystemCache
RESULTS_BACKEND = FileSystemCache('/tmp/sqllab')
```

Start up a celery worker

shell

celery --app=superset.tasks.celery_app:app worker -O fair

Note that:

for changes that affect the worker logic, you'll have to restart the celery worker process for the changes to be reflected.
The message queue used is a sqlite database using the SQLAlchemy experimental broker. Ok for testing, but not recommended in production
In some cases, you may want to create a context that is more aligned to your production environment, and use the similar broker as well as results backend configuration

Async Chart Queries

It's possible to configure database queries for charts to operate in async mode. This is especially useful for dashboards with many charts that may otherwise be affected by browser connection limits. To enable async queries for dashboards and Explore, the following dependencies are required:

Redis 5.0+ (the feature utilizes Redis Streams)
Cache backends enabled via the CACHE_CONFIG and DATA_CACHE_CONFIG config settings
Celery workers configured and running to process async tasks