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feat: rename TABLE_NAMES_CACHE_CONFIG to DATA_CACHE_CONFIG (#11509)

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* feat: rename TABLE_NAMES_CACHE_CONFIG to DATA_CACHE_CONFIG

The corresponding cache will now also cache the query results.

* Slice use DATA_CACHE_CONFIG CACHE_DEFAULT_TIMEOUT

* Add test for default cache timeout

* rename FAR_FUTURE to ONE_YEAR_IN_SECS
This commit is contained in:
Jesse Yang
2020-11-13 22:35:10 -08:00
committed by GitHub
parent 68693c7c0a
commit 4cfcaebb61
22 changed files with 438 additions and 379 deletions
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docs/src/pages/docs/installation/caching.mdx
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@@ -8,12 +8,16 @@ 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.
Superset uses [Flask-Cache](https://pythonhosted.org/Flask-Cache/) 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.
Flask-Cache supports multiple caching backends (Redis, Memcached, SimpleCache (in-memory), or the
local filesystem).
Configuring caching is as easy as providing `CACHE_CONFIG` and `DATA_CACHE_CONFIG` in your
`superset_config.py` that complies with [the Flask-Cache specifications](https://flask-caching.readthedocs.io/en/latest/#configuring-flask-caching).
Flask-Cache supports various caching backends, including 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.
@@ -21,12 +25,12 @@ local filesystem).
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`.
For chart data, Superset goes up a “timeout search path”, from a slice's configuration
to the datasource’s, the database’s, then ultimately falls back to the global default
defined in `DATA_CACHE_CONFIG`.
```
CACHE_CONFIG = {
DATA_CACHE_CONFIG = {
'CACHE_TYPE': 'redis',
'CACHE_DEFAULT_TIMEOUT': 60 * 60 * 24, # 1 day default (in secs)
'CACHE_KEY_PREFIX': 'superset_results',