Superset uses Flask-Caching for caching purposes. Flask-Caching supports various caching backends, including Redis (recommended), Memcached, SimpleCache (in-memory), or the local filesystem. Custom cache backends are also supported.
Caching can be configured by providing a dictionaries in
superset_config.py
that comply withthe Flask-Caching config specifications.
The following cache configurations can be customized in this way:
- Dashboard filter state (required):
FILTER_STATE_CACHE_CONFIG
. - Explore chart form data (required):
EXPLORE_FORM_DATA_CACHE_CONFIG
- Metadata cache (optional):
CACHE_CONFIG
- Charting data queried from datasets (optional):
DATA_CACHE_CONFIG
For example, to configure the filter state cache using redis:
FILTER_STATE_CACHE_CONFIG = {
'CACHE_TYPE': 'RedisCache',
'CACHE_DEFAULT_TIMEOUT': 86400,
'CACHE_KEY_PREFIX': 'superset_filter_cache',
'CACHE_REDIS_URL': 'redis://localhost:6379/0'
}
Dependencies
In order to use dedicated cache stores, additional python libraries must be installed
- For Redis: we recommend the redis Python package
- Memcached: we recommend using pylibmc client library as
python-memcached
does not handle storing binary data correctly.
These libraries can be installed using pip.
Fallback Metastore Cache
Note, that some form of Filter State and Explore caching are required. If either of these caches are undefined, Superset falls back to using a built-in cache that stores data in the metadata database. While it is recommended to use a dedicated cache, the built-in cache can also be used to cache other data.
For example, to use the built-in cache to store chart data, use the following config:
DATA_CACHE_CONFIG = {
"CACHE_TYPE": "SupersetMetastoreCache",
"CACHE_KEY_PREFIX": "superset_results", # make sure this string is unique to avoid collisions
"CACHE_DEFAULT_TIMEOUT": 86400, # 60 seconds * 60 minutes * 24 hours
}
Chart Cache Timeout
The cache timeout for charts may be overridden by the settings for an individual chart, dataset, or database. Each of these configurations will be checked in order before falling back to the default value defined in `DATA_CACHE_CONFIG.
Note, that by setting the cache timeout to -1
, caching for charting data can be disabled, either
per chart, dataset or database, or by default if set in DATA_CACHE_CONFIG
.
SQL Lab Query Results
Caching for SQL Lab query results is used when async queries are enabled and is configured using
RESULTS_BACKEND
.
Note that this configuration does not use a flask-caching dictionary for its configuration, but instead requires a cachelib object.
See Async Queries via Celery for details.
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,
}
By default thumbnails are rendered per user, and will fall back to the Selenium user for anonymous users.
To always render thumbnails as a fixed user (admin
in this example), use the following configuration:
from superset.tasks.types import ExecutorType
THUMBNAIL_SELENIUM_USER = "admin"
THUMBNAIL_EXECUTE_AS = [ExecutorType.SELENIUM]
For this feature you will need a cache system and celery workers. All thumbnails are stored on cache and are processed asynchronously by the workers.
An example config where images are stored on S3 could be:
from flask import Flask
from s3cache.s3cache import S3Cache
...
class CeleryConfig(object):
broker_url = "redis://localhost:6379/0"
imports = (
"superset.sql_lab",
"superset.tasks.thumbnails",
)
result_backend = "redis://localhost:6379/0"
worker_prefetch_multiplier = 10
task_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:
def auth_driver(driver: WebDriver, user: "User") -> WebDriver:
pass
Then on configuration:
WEBDRIVER_AUTH_FUNC = auth_driver