On 03/21/2018 10:14 AM, Henrik Bengtsson wrote:
A few quick comments:
* I don't think the limit was hardened in R 3.4.0; maybe you started to
experience it sound then because more dependent packages started to rely on
more DLLs?
* The limit is OS/platform specific so it's not that R core is unwilling to
fix this - I think they havejust tried to find a safe limit that work
everywhere. Having said this...
* It'll be less restrictive by default in R 3.5.0: from it's NEWS "The
maximum number of DLLs that can be loaded into R e.g. via dyn.load() has
been increased up to 614 when the OS limit on the number of open files
allows"
* R.utils::gcDLLs() will attempt to unregister possibly stray DLLs
remaining after unloading packages. So unloading packages and gcDLLs() may
provide you with a workaround until R 3.5.0 is in place (possibly also even
after).
See https://github.com/HenrikBengtsson/Wishlist-for-R/issues/29 for
"random" notes and references to this problem.
On Wed, Mar 21, 2018, 04:10 Yuan Tian <tianyuan1991...@gmail.com> wrote:
Hello Guys:
I encountered an error like "maximal number of dlls reached...". I am
maintaining ChAMP package now, which integrated many other packages in my
research field. I have not updated this package in past 2 months but
suddenly this error happens.
Currently, I think I know the reason is since R 3.4.X, numbers of DLLs in
default R session was set 100. I have tested that using a newly started R
3.4.4 to install and load ChAMP package, *it works smoothly*, after
loading, I checked DLL loaded with function getLoadedDLLs(), then I see
ChAMP used 95 Dlls. I know it's a lot, but some of them are loaded by
ChAMP's relying packages but itself. *However, ChAMP cannot pass
Bioconductor check, thus I suspect Bioconductor checking system does NOT
start a new R session for each package right? Which means it's not 100 DLLs
allocated for each package?*
ChAMP is passing BiocCheck in release, where R is 3.4.x ?
http://bioconductor.org/checkResults/release/bioc-LATEST/ChAMP/malbec1-checksrc.html
Each package is built and tested in a separate process. Vignettes are
actually built in a single process (by R, not Bioconductor) so multiple
vignettes could load a higher number of DLLs.
Currently, I have told my users to modify R environment to allow their R
session with more DLLs. It works but only on users computer, not
Bioconductor checking system. Thus I think I have to reduce dlls used by
current package right? Like removing some relying packages or function. *My
another question is how many DLLs is allowed by Bioconductor check? I think
it's less than 100. But I don't know I should cut it into 80 or 60 or even
50 dlls used.*
It's really disappointing that I need to modify quite a lot of code, and
even could hurt some key functionality of the package. Thus here I am
seeking your help and suggestions here.
Frankly, I think a package with so many dependencies cannot be
maintained -- a change in any one of those packages could break your
package (e.g., by changing their own dependencies to include additional
DLLs!), and it must be virtually impossible to get sufficient test
coverage to be confident that these problems will be detected before the
package is made available to the user. It is time to consider a more
modular design focusing on essential features.
Martin
Best
Yuan Tian
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