---
name: Caching
menu: Installation and Configuration
route: /docs/installation/cache
index: 5
version: 1
---

## Caching

Superset uses [Flask-Cache](https://pythonhosted.org/Flask-Cache/) for caching purpose. Configuring
your caching backend is as easy as providing a `CACHE_CONFIG`, constant in your `superset_config.py`
that complies with the Flask-Cache specifications.

Flask-Cache supports multiple caching backends (Redis, Memcached, SimpleCache (in-memory), or the
local filesystem).

- Memcached: we recommend using [pylibmc](https://pypi.org/project/pylibmc/) client library as
  `python-memcached` does not handle storing binary data correctly.
- Redis: we recommend the [redis](https://pypi.python.org/pypi/redis) Python package

Both of these libraries can be installed using pip.

For setting your timeouts, this is done in the Superset metadata and goes up the “timeout
searchpath”, from your slice configuration, to your data source’s configuration, to your database’s
and ultimately falls back into your global default defined in `CACHE_CONFIG`.

```
CACHE_CONFIG = {
    'CACHE_TYPE': 'redis',
    'CACHE_DEFAULT_TIMEOUT': 60 * 60 * 24, # 1 day default (in secs)
    'CACHE_KEY_PREFIX': 'superset_results',
    'CACHE_REDIS_URL': 'redis://localhost:6379/0',
}
```

Custom cache backends are also supported. See [here](https://flask-caching.readthedocs.io/en/latest/#custom-cache-backends) for specifics.

Superset has a Celery task that will periodically warm up the cache based on different strategies.
To use it, add the following to the `CELERYBEAT_SCHEDULE` section in `config.py`:

```python
CELERYBEAT_SCHEDULE = {
    'cache-warmup-hourly': {
        'task': 'cache-warmup',
        'schedule': crontab(minute=0, hour='*'),  # hourly
        'kwargs': {
            'strategy_name': 'top_n_dashboards',
            'top_n': 5,
            'since': '7 days ago',
        },
    },
}
```

This will cache all the charts in the top 5 most popular dashboards every hour. For other
strategies, check the `superset/tasks/cache.py` file.

### Caching Thumbnails

This is an optional feature that can be turned on by activating it’s feature flag on config:

```
FEATURE_FLAGS = {
    "THUMBNAILS": True,
    "THUMBNAILS_SQLA_LISTENERS": True,
}
```

For this feature you will need a cache system and celery workers. All thumbnails are store on cache
and are processed asynchronously by the workers.

An example config where images are stored on S3 could be:

```python
from flask import Flask
from s3cache.s3cache import S3Cache

...

class CeleryConfig(object):
    BROKER_URL = "redis://localhost:6379/0"
    CELERY_IMPORTS = ("superset.sql_lab", "superset.tasks", "superset.tasks.thumbnails")
    CELERY_RESULT_BACKEND = "redis://localhost:6379/0"
    CELERYD_PREFETCH_MULTIPLIER = 10
    CELERY_ACKS_LATE = True


CELERY_CONFIG = CeleryConfig

def init_thumbnail_cache(app: Flask) -> S3Cache:
    return S3Cache("bucket_name", 'thumbs_cache/')


THUMBNAIL_CACHE_CONFIG = init_thumbnail_cache
# Async selenium thumbnail task will use the following user
THUMBNAIL_SELENIUM_USER = "Admin"
```

Using the above example cache keys for dashboards will be `superset_thumb__dashboard__{ID}`. You can
override the base URL for selenium using:

```
WEBDRIVER_BASEURL = "https://superset.company.com"
```

Additional selenium web drive configuration can be set using `WEBDRIVER_CONFIGURATION`. You can
implement a custom function to authenticate selenium. The default function uses the `flask-login`
session cookie. Here's an example of a custom function signature:

```python
def auth_driver(driver: WebDriver, user: "User") -> WebDriver:
    pass
```

Then on configuration:

```
WEBDRIVER_AUTH_FUNC = auth_driver
```
