I’m currently working on a web app that handles large data sets, and I’m exploring best practices for optimizing data loading and processing speed. I’m considering approaches like pagination, lazy loading, and possibly using a caching layer, but I’d love to hear what’s worked best for others in this case.
All of the above? No honestly, all of those techniques are not necessarily exclusive from one another. You can use pagination and cache pages, you can lazy load where necessary. You really just have to look at the amount of data you have, the type of data, how often you need it to be fresh and how much you need to access at any one time. These various techniques have their strengths and weaknesses. For example, if you have 100K records and are needing to only read 2 at a time, pagination is going to result in a ton of over the wire requests. Maybe not something you want to happen on a very popular website.
Just ask yourself what your project requires and apply the technique that works best in that scenario. Don’t be afraid to mix a few techniques if they fit.
Agreed with @Martyr2 on all points (though if you’ve got 100K records and are only reading 2 at a time, I have questions).
Without knowing the ins-and-outs of the application, data security/synchronicity becomes an issue; for example, is it more efficient to load all of the records, and then handle them locally, or pull them as-needed and use them without the possibility of interception? What data needs to flow out (and presumably, back in) and when.
These sorts of considerations may change your strategy for handling the data.
EDIT: And when my brain wakes up properly, I will realize this post is a month old, and was probably just bumped back to the top by a spammer. And i shall sigh.
You can also look how you can use the database to speed up. Using Materialized views or partitioning.
And one way to speed up by lower the latency. Let the app connect to the database direct via an internal IP address instead for running around the world chasing your server…