Hey everyone! I’m struggling with a common problem across my projects. How do you handle loading big chunks of data without killing performance?
I work with various tech stacks (C#, Java, Android, WinForms) and often deal with massive datasets. For instance, I’ve got a database with 2 million records. When a user applies filters, it might return 100k results, which is way too much to display at once.
I’m considering a lazy loading approach in a RESTful environment. Should I load just 200 items initially, then fetch more as needed? I’m also wondering how to keep track of what the user has already seen.
This issue is similar when searching for images on mobile devices. Loading 10k images at once would overwhelm the network, so perhaps displaying 20 at a time as the user scrolls would be more efficient.
I’ve tried loading the entire dataset on the server and sending only the needed parts, but this proved inefficient with many simultaneous users. Any advice on managing this load efficiently on the backend, database, and client side?
hey nova, have u tried a virtual list? it renders only visible items, boosting performance. pair that with server-side pagination. for mobile, def use lazy loading - about 20-30 imgs at a time. also, optimize ur queries and ensure proper indexing. good luck!
have u considered using pagination? it could help manage those big datasets without overwhelming the system. maybe combine it with caching for frequently accessed data? curious about your thoughts on implementing something like infinite scrolling too. what challenges have u faced with that approach?
Pagination is a solid start, but for truly massive datasets, consider implementing virtual scrolling. This technique only renders visible items, drastically reducing memory usage and improving performance. I’ve successfully used it with Angular’s CDK virtual scroll for web applications and RecyclerView for Android.
On the backend, query optimization is crucial. Ensure your database indexes are properly set up for your most common queries. If you’re dealing with complex aggregations, consider pre-computing some results and storing them in a separate table or cache.
For tracking what users have seen, you could maintain a lightweight client-side data structure (like a Set) with unique identifiers of viewed items. This approach has worked well in my projects without adding significant overhead.