Background Tasks for Snowflake
These background tasks can run on a schedule.
This task should run often as it refreshes the meta data of your tables (e.g. every hour). It does not start a warehouse. It discovers tables, views, external tables and materialized views.
The data profiler is the most expensive task. It's usually enough to run it daily or even weekly. It generates a sample of 100k rows for every table or view, computes data quality metrics and the data profiles. If it can not compute a profile for a view within 5 minutes it will stop. The sampler is super fast, even for big tables (TBs) the calculation usually completes within 5 minutes.
This task also starts a warehouse. Running it every 8 hours or daily is a good default. The query parser is responsible for the timeline, usage statistics and lineage. If your query history is really big this can take some time to complete. This task also extracts information from other system tables that track e.g. how often materialized views get updated.
This task starts a warehouse. Running it daily is a good default. This job writes back important meta data to Snowflake. Which enables you to create custom analysis on top of your meta data. It also writes back user activity data to track how useful Sled is in your organization.