I’m trying to make a Google Sheets Add-on that needs to work with a ton of data. The problem is, Google’s time-trigger rules mean we can’t run things more than once an hour. That’s really annoying when dealing with huge amounts of data.
I’ve tried triggering it, but it fires only once, and I can’t chain triggers to keep the process going. Anyone know a workaround for this? Perhaps there’s a method to handle large datasets within these limits?
I’d appreciate any insights or suggestions for managing big data with Google Sheets Add-ons.
hey ethan, have you considered chunking ur data? break it into smaller bits that can be processed within the hourly limit. then use a counter in a cell to track progress and trigger the next chunk. might take longer but could work around the restriction. good luck mate!
I’ve dealt with similar challenges when working on large-scale data processing in Google Sheets. One approach that’s worked well for me is implementing a queue system. Essentially, you create a separate sheet to act as a job queue. Each row represents a task, with columns for status, priority, and other relevant metadata.
Your hourly trigger can then process tasks from this queue, marking them as complete as it goes. This way, you’re not trying to process everything at once, but rather working through the backlog steadily. It’s more complex to set up initially, but it’s quite robust and flexible once in place.
Another trick I’ve used is leveraging Google Apps Script’s ability to make external API calls. If you have access to a server or cloud function, you can offload some of the heavy lifting there, using Sheets as more of a front-end and data storage solution. This can help bypass some of the limitations of Sheets’ processing capabilities.
Have you considered using Google BigQuery in conjunction with your Sheets Add-on? BigQuery is designed for handling massive datasets and can process terabytes of data quickly. You could set up your Add-on to export data to BigQuery, run your heavy computations there, and then import the results back into Sheets. This approach sidesteps the time limitations in Sheets while still allowing you to work with large amounts of data efficiently.
Another option is to use Apps Script’s UrlFetchApp to send data to an external API or service for processing. This way, you’re not limited by Sheets’ processing power or time constraints. You could set up a simple server (even a free-tier cloud service) to handle the heavy lifting, then pull the results back into your spreadsheet.
Both methods require some additional setup, but they’re solid solutions for managing big data within Google Sheets’ ecosystem.