| Loading a 4GB+ workbook with over 500 million cells with random floating-point numbers and text strings - 8 worksheets, ~12 million rows each should take less than 30s on a computer with 16GB RAM. Updating 12 million vlookups searching 12 million rows takes seconds. Effective use of up to 64 processor cores for calculations applying any functions, including any number of user-created functions that can both extend and replace the default built-in set of ~390 functions. Filtering, regular expressions, Monte Carlo simulations, pivot tables with up to 12 million rows, scripting. GS-Calc can be installed on any portable storage device and used without performing any registry modifications. The installation folder requires ~8.5MB. https://citadel5.com/gs-calc.htm
(incl. YT videos with examples) Any suggestions, especially regarding the ETL-related functions, are welcome. Thanks |
Google sheets is a bit harder to figure out -- it doesn't have an explicit row limit, but does have a cell limit of 10M cells - so depending on your number of columns you can back out to the max rows.
If you want to see some practical effects of these row limits, check out the time that England misreported thousands of covid cases - because their Excel file ran out of space silently [1]. Oops.
This looks like a pretty sweet engineering effort! Anything cool you learned while building this that you can share here that helped you achieve this performance? What language did you use to build this application?
I'm asking for interest and for selfish reasons -- fellow spreadsheet builder of Mito [2] - which is pretty much just a UI wrapper for Pandas dataframes (and so can support 10M+ rows as well).
[1] https://www.bbc.com/news/technology-54423988 [1] https://trymito.io