I am creating a shiny app with large input data - around 6 Mio. observations. The app is used for interactive analysis. In each tab I have maybe 5 plots - a total of max. 15 plots. I have used plotly, b/c at some point it was faster than ggplot. However, I also have quite a lot of filters for my data and depending on the analyses, so a lot of rendering is going on.
At this point I'm only working with 10% of the data and am already having performance issues. I will have to use 100% of the data at some point.
I have two stacked bar plots and than that mostly histograms. I have looked into possibilities to increase performance and have stumbled onto toWebGL() and partial_bundle() but I'm not quite sure how they work and how I would apply them to my plots.
Any feedback and help is welcome regarding performance. If needed I can also provide a reprex.
Edit: I was thinking if conditional filters would work, so not all filters are available at a time. Has anyone had any experience with that?