If binary packages are unavailable for your OS (e.g., Linux with custom R), R compiles from source, which is CPU-intensive.
Solution:
A common mistake is using the default base R without optimization. Here’s how to install or reinstall R correctly for heavy data tasks. sexart juniper ren slow down 26022025 r install
✅ Did you reinstall R with optimized BLAS?
✅ Are you using data.table::fread() instead of read.csv()?
✅ For video files, is the av package installed?
✅ Have you avoided loops with for() and used vectorized code?
✅ Is your working directory free of gigantic hidden temp files?
✅ Did you update all packages (update.packages(ask=FALSE))? If binary packages are unavailable for your OS (e
If after all this R still slows down, consider: Linux with custom R)