chore(cache): default to SimpleCache in debug mode (#18976)

* chore(cache): default to SimpleCache in debug mode

* lint

* clean up type

* use util

* fix integration test cache configs

* remove util from cache manager

* remove trailing comma

* fix more tests

* fix truthiness check

* fix tests and improve deprecation notice

* fix default cache threshold

* move debug check to cache_manager

* remove separate getter

* update docs

* remove default cache config

docs/docs/installation/cache.mdx

@@ -7,20 +7,25 @@ version: 1
 
 ## Caching
 
-Superset uses [Flask-Caching](https://flask-caching.readthedocs.io/) for caching purpose. For security reasons,
-there are two separate cache configs for Superset's own metadata (`CACHE_CONFIG`) and charting data queried from
-connected datasources (`DATA_CACHE_CONFIG`). However, Query results from SQL Lab are stored in another backend
-called `RESULTS_BACKEND`, See [Async Queries via Celery](/docs/installation/async-queries-celery) for details.
-
-Configuring caching is as easy as providing `CACHE_CONFIG` and `DATA_CACHE_CONFIG` in your
+Superset uses [Flask-Caching](https://flask-caching.readthedocs.io/) for caching purpose. Configuring caching is as easy as providing a custom cache config in your
 `superset_config.py` that complies with [the Flask-Caching specifications](https://flask-caching.readthedocs.io/en/latest/#configuring-flask-caching).
-
 Flask-Caching supports various caching backends, including Redis, Memcached, SimpleCache (in-memory), or the
-local filesystem.
+local filesystem. Custom cache backends are also supported. See [here](https://flask-caching.readthedocs.io/en/latest/#custom-cache-backends) for specifics.
+The following cache configurations can be customized:
+- Metadata cache (optional): `CACHE_CONFIG`
+- Charting data queried from datasets (optional): `DATA_CACHE_CONFIG`
+- SQL Lab query results (optional): `RESULTS_BACKEND`. See [Async Queries via Celery](/docs/installation/async-queries-celery) for details
+- Dashboard filter state (required): `FILTER_STATE_CACHE_CONFIG`.
+- Explore chart form data (required): `EXPLORE_FORM_DATA_CACHE_CONFIG`
 
+Please note, that Dashboard and Explore caching is required. When running Superset in debug mode, both Explore and Dashboard caches will default to `SimpleCache`;
+However, trying to run Superset in non-debug mode without defining a cache for these will cause the application to fail on startup. When running
+superset in single-worker mode, any cache backend is supported. However, when running Superset in on a multi-worker setup, a dedicated cache is required. For this
+we recommend using either Redis or Memcached:
+
+- Redis (recommended): we recommend the [redis](https://pypi.python.org/pypi/redis) Python package
 - 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.
 
@@ -28,16 +33,7 @@ For chart data, Superset goes up a “timeout search path”, from a slice's con
 to the datasource’s, the database’s, then ultimately falls back to the global default
 defined in `DATA_CACHE_CONFIG`.
 
-```
-DATA_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.
+## Celery beat
 
 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`: