Thanks for the post Mark!

On partitioning limits: For usability purposes I ended up settling on yearly tables — there I can leverage all benefits of partitioned tables, while also the ability to UNION them with a * pattern match. It makes my life easier too, when I want to query for any given year. For more clustering examples, check out the post I left at:

Data Cloud Advocate at Snowflake ❄️. Originally from Chile, now in San Francisco and around the world. Previously at Google. Let’s talk data.

Data Cloud Advocate at Snowflake ❄️. Originally from Chile, now in San Francisco and around the world. Previously at Google. Let’s talk data.