I'm storing an event calendar where events are often repeated at different times and locations. For simplicity, let's say I'm storing these fields:
(I defined uid to be a identifier for unique events based on title and description, which I'm using in my app to group the events.)
Having a separate document for each instance of a repeating event makes it easy to do search and filter, but it bothers me that the tf-idf scoring is not quite correct since there are so many duplicates.
I've read about nested datatypes and also results aggregation, but I'm not sure which if either are right for me. What's the right way to design an index so that scoring functions are only considering "unique" events?