I’m working on a project that needs to display a huge amount of data in a spreadsheet on a webpage. I’m using a library called handsontable with jQuery. It works okay for smaller datasets but when I try to load more than 100,000 rows from my MongoDB, it gets super slow and eats up a ton of memory.
I thought about only showing 2000 rows at a time and loading more as the user scrolls. But that might cause problems if someone wants to change a value for the whole dataset at once.
I’m wondering how other devs have solved this issue. I heard Google Sheets can handle millions of rows now. How do they do it? What are some good ways to make this work smoothly with so much data?
Here’s a simple example of what I’m working with:
const hot = new Handsontable(container, {
data: hugeDataset,
rowHeaders: true,
colHeaders: true,
height: 'auto',
width: 'auto',
filters: true,
dropdownMenu: true
});
Any ideas on how to make this more efficient?
Having tackled similar challenges, I can tell you it’s not easy, but there are ways to make it work. One approach that yielded good results for me was implementing a custom virtual rendering system. Essentially, I only rendered the visible cells plus a buffer, and swapped them out as the user scrolled. It took some effort to get right, but it dramatically improved performance.
Another trick I found useful was to defer non-essential operations. For instance, I’d postpone calculation-heavy tasks until the user stopped scrolling or typing. This kept the interface feeling snappy even with massive datasets.
As for handling whole-dataset operations, I ended up processing those server-side and pushing updates to the client in batches. It wasn’t perfect, but it was a decent compromise between functionality and performance.
Remember, there’s no silver bullet here. It’s all about finding the right balance for your specific use case.
Optimizing performance in web-based spreadsheets with large datasets can be addressed by implementing strategies that reduce the browser’s workload. For instance, virtual scrolling helps by rendering only the visible rows dynamically so that as you scroll, rows are loaded and unloaded. Fetching data in smaller chunks instead of all at once can significantly reduce startup time and memory demands. Additionally, caching computations and offloading heavy processing to background threads can keep the interface responsive. In my experience, combining these techniques while carefully profiling the application leads to noticeable improvements.
yo, i dealt with this before. try lazy loading chunks of data as user scrolls. also, use Web Workers for heavy lifting - keeps UI smooth. Google Sheets prob uses some crazy optimization tricks. maybe look into IndexedDB for client-side caching? could help with performance. good luck man!