Performance: View that filters out data versus archiving data

[telepet]

I have a View based on about 6 related tables.  One of these tables has about 60,000 records that span the last 20 years, which is by far the largest table.  I really only need the last 5 years of data from this table for Caspio purposes, so I'm wondering if it might be worth it to archive any data in that table that's older as a means of improving performance.  That said-- unless there's a huge performance boost, my preference would be to create a View that filters out all years from prior what I need.

[jhernandez]

I do a lot of this as well. 

The easiest solution I found would be to "date" all your source data with a corresponding year. If you export the data to Excel, add a new column called "Valuation Year" where you will store the year as a number. Then, for example, for records 1 - 10,000 add "2012" on the column, then records 10,001 to 20,000 would be "2013" so on and so forth.

Once that's done you can re upload the table to Caspio. If your data already has a date identifier , you can add the the column to your View and go to "Criteria" and filter for the years you need. You need to be very careful here since you will need to add several "OR" properties to the logic.

Performance wise, I don't know if there will be that much of an improvement, but I suppose you can try it yourself. My guess is the performance wouldn't be increased too much since the View is always pulling data from the source Tables. That said, actual performance depends how Caspio works behind the scenes: if it wants to filter first, then pull all the remaining rows from the sources, then performance should improve, but if it loads the source first and then runs the filters, performance wouldn't improve.

Edited July 6, 2017 by jhernandez
Edit spelling for clarity.

[telepet]

Thanks @jhernandez .  I'll incorporate what you highlighted.  Thankfully, my data set has date info, so not too much extra work.  I'll post back if I can discern any performance impact.   Thanks again!