If these are easy changes, maybe someone will incorporate them. You'll
make the argument stronger for doing that if you can explain why it's
better to do that than to keep them in parallely.
Duncan Murdoch
On 07/11/2020 1:39 p.m., Henrik Bengtsson wrote:
FWIW, there are indeed a few low hanging bug fixes in 'parallelly'
that should be easy to incorporate into 'parallel' without adding
extra maintenance. For example, in parallel::makePSOCKcluster(), it
is not possible to disable SSH option '-l USER' so that it can be set
in ~/.ssh/config. The remote user name will be the user name of your
local machine and if you try to set user=NULL, you'll end up with an
invalid SSH call. The current behavior means that you are forced to
specify the remote user name in your R code. All that it takes is to
fix this is to update:
cmd <- paste(rshcmd, "-l", user, machine, cmd)
to something like:
cmd <- paste(rshcmd, if (length(user) == 1L) paste("-l", user), machine, cmd)
This is one example of what I've patched in
parallelly::makeClusterPSOCK() over the years. Another is the use of
reverse tunneling in SSH - that completely avoids the need to know and
specify your public IP and reconfiguring the firewalls from the remote
server back to your local machine so that the worker can connect back
to your local machine. Not many users have the permission to
reconfigure firewalls and it's also extremely tedious. Reverse SSH
tunneling is super simply; all you need to to is something like:
rshopts <- c(sprintf("-R %d:%s:%d", rscript_port, master, port), rshopts)
/Henrik
On Fri, Nov 6, 2020 at 4:37 PM Duncan Murdoch <murdoch.dun...@gmail.com> wrote:
On 06/11/2020 4:47 p.m., Balamuta, James Joseph wrote:
Hi all,
Henrik Bengtsson has done some fantastic work with {future} and, more
importantly, greatly improved constructing and deconstructing a parallelized
environment within R. It was with great joy that I saw Henrik slowly split off
some functionality of {future} into {parallelly} package. Reading over the
package’s README, he states:
The functions and features added to this package are written to be backward
compatible with the parallel package, such that they may be incorporated there
later.
The parallelly package comes with an open invitation for the R Core Team to
adopt all or parts of its code into the parallel package.
https://github.com/HenrikBengtsson/parallelly
I’m wondering what the appropriate process would be to slowly merge some
functions from {parallelly} into the base R {parallel} package. Should this be
done with targeted issues on Bugzilla for different fields Henrik has
identified? Or would an omnibus patch bringing in all suggested modifications
be preferred? Or is it best to discuss via the list-serv appropriate
contributions?
One way is to convince R Core that incorporating this into the parallel
package would
- make less work for them, or
- add a lot to R that couldn't happen if it was a contributed package.
The fact that it's good isn't a good reason to put it into a base
package, which would largely mean transferring Henrik's workload to R
Core. There are lots of good packages, and their maintainers should
continue to maintain them.
Duncan Murdoch
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