I am using (to be precise, pilot testing & feature/performance assessment still pending) the Tabulator tables library for displaying a (rather large - some ~30 columns and 10k rows) data set and was wondering about the most efficient way of implementing the column filtering using formatted data.
By formatted data I mean the data I am displaying to the user in the table after applying a cell format on the original data. This way, lets say I have a Date column formatted to "dd/mm/yyyy" and I would then want to let the user to find all rows matching September 2021 on that column by typing "9/2021" into the column filter box. Now, I could do this in 2 ways I know about:
Implement a custom filter. With this method I would have to re-apply the transformation (formatting) to the data every time and then match it to the user input. CPU heavy.
Implement a mutator. This way I would once (upon data load) transform the data, creating a new (as in not present in the original data array I load into the table) "column" in the backing data array, and upon filtering the table would simply filter against those new values. Would need to introduce a new "column" in the data for every column requiring this. RAM heavy.
From these I tend to pick option 2) as my target is mostly desktop browsers and the table is slow as it is (column filter / sort easily take 1-2 seconds even with a low number of rows such as 200-300). Perhaps I missed a better way?
