Killed ERROR: lazy loading failed for package

This is probably related to "Killed" error during installation for many packages
or is a system issue. I thought I would post anyway. There are about ~10 students in a class I am teaching using the free version of RStudio Clould and all are having the following error.

I am having an issue installing ensembldb on RStudio cloud (I do not have this issue on my local R installation). I have tried with and without specifying the lib path.

if (!requireNamespace("BiocManager", quietly = TRUE))
BiocManager::install("ensembldb", lib = "/home/rstudio-user/R/x86_64-pc-linux-gnu-library/4.0")

  • installing source package ‘ensembldb’ ...
    ** using staged installation
    ** R
    ** inst
    ** byte-compile and prepare package for lazy loading
    ERROR: lazy loading failed for package ‘ensembldb’
  • removing ‘/home/rstudio-user/R/x86_64-pc-linux-gnu-library/4.0/ensembldb’

The downloaded source packages are in
Warning message:
In install.packages(...) :
installation of package ‘ensembldb’ had non-zero exit status

sessionInfo( )

R version 4.0.2 (2020-06-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS

Matrix products: default
BLAS: /usr/lib/atlas-base/atlas/
LAPACK: /usr/lib/atlas-base/atlas/


attached base packages:
[1] stats graphics grDevices utils datasets methods
[7] base

loaded via a namespace (and not attached):
[1] BiocManager_1.30.10 compiler_4.0.2 tools_4.0.2

Hi @jeffreyblanchard

I remember this error.
Have you checked whether the package is installed when students reload the session after the crash?
This error was quite frustrating, but I remember that even though the session crashed, the package was actually installed, when I restarted the session.


Thanks for the suggestion. No such luck. I might try subscribing to test out whether it is a constraint on memory in the free version of Cloud.

The free plan is constrained to 1GB RAM memory so this is the most likely explanation, if you have a paid account you could increase your computational resources temporarily and install the problematic package on the "base" project for the workspace, that way all projects created in that workspace would already have it installed.

Some of my students have enjoyed using RStudio Cloud. It has helped alleviate issues with outdated operating systems and limited hard drive/memory. Also helps with github installation.

If I purchase the "Instructor" subscription can I create a workspace with the packages installed that students can access? Do this also increase their individual RAM and project hours?


If you have purchased a paid plan, any students you add to a space owned by the upgraded account will have access to addtional hours and increased memory. Keep in mind that any usage generated by users in the space will be allocated to your account.

Hope that helps