Hi,
We have a use case where we need to support sorting and pagination on aggregated data and it should be exact(not approximate).We tried different approaches but could not achieve what we wanted. "Collapse" helped in solving all the problem except one that we were not able to sort the data based on terms aggregation count .
So we decide to go for dataframes and store the aggregated result in new index. Our issue here is we need to filter based on the time as well eg last 30days, last 90 days etc in data frames .
We are planning to achieve this by creating multiple continuous sync data frames
such that each filter will store the data in different index (for 30days new index,for 90 days another index)and also we need to clear the old data in these destinations indices to get the proper result.
We are not very sure how good this solution is and we would be very grateful if we can get any different approach to solve this problem. Your help will be appreciated.
Thanks & Regards,