This might help:
On Tue, Oct 18, 2016 at 12:30 AM, Buntu Dev <buntu...@gmail.com> wrote:
> I got table of user purchases and subscriptions with various product skus
> along with user attributes in a single table (~1g and 20M rows).
> Due to the number of combinations for slicing and dicing the data, it takes
> a while to query for churn, retention, etc. on the dataset for various time
> periods and product skus selected and makes it not ideal the frontend.
> Generating a precomputed table with all the combinations is pretty
> exhausting, so I'm look to see if there are any best practices in designing
> a schema to overcome these issues.