similar to: mccollect with NULL in R 3.6

On Thu, May 2, 2019 at 7:24 PM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > On 5/1/19 12:25 AM, Gergely Dar?czi wrote: > > Dear All, > > > > I'm running into issues with calling mccollect on a list containing NULL > > using R 3.6 (this used to work in 3.5.3): > > > > jobs <- lapply( > > list(NULL, 'foobar'), >

On 5/3/19 3:04 PM, Gergely Dar?czi wrote: > On Thu, May 2, 2019 at 7:24 PM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: >> On 5/1/19 12:25 AM, Gergely Dar?czi wrote: >>> Dear All, >>> >>> I'm running into issues with calling mccollect on a list containing NULL >>> using R 3.6 (this used to work in 3.5.3): >>> >>> jobs

On 5/1/19 12:25 AM, Gergely Dar?czi wrote: > Dear All, > > I'm running into issues with calling mccollect on a list containing NULL > using R 3.6 (this used to work in 3.5.3): > > jobs <- lapply( > list(NULL, 'foobar'), > function(x) mcparallel(identity(x))) > mccollect(jobs, wait = FALSE, timeout = 0) > #> Error in names(res) <-

Hi there, I've tried to implement an asynchronous job scheduler using parallel::mcparallel() and parallel::mccollect(..., wait=FALSE). My goal was to send processes to the background, leaving the R session open for interactive use while all jobs store their results on the file system. To keep track of the running jobs I've stored the process ids and written a little helper to not spawn

I stumbled upon the following: f <- parallel::mcparallel(raw(0L)) parallel::mccollect(f) # $`77083` # NULL but f <- parallel::mcparallel(raw(1L)) parallel::mccollect(f) # Error in unserialize(r) : read error traceback() # 2: unserialize(r) # 1: parallel::mccollect(f) (restarting because the above appears to corrupt the R session) f <- parallel::mcparallel(raw(2L))

On Fri, Aug 31, 2018 at 2:51 PM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: [...] > kill(sig=0) is specified by POSIX but indeed as you say there is a race > condition due to PID-reuse. In principle, detecting that a worker > process is still alive cannot be done correctly outside base R. I am not sure why you think so. > At user-level I would probably consider some

Dear All, Since upgrading to 3.6.0, I've been getting a strange error messages from the child process when using mcparallel/mccollect. Before filing a report in the Bugzilla, I want to figure out whether I had been doing something wrong all this time and R 3.6.0 has exposed it, or whether something else is going on. # Background # Ultimately, what I want to do is to be able to set a time

I'd like to importFrom(parallel, mccollect, mcparallel) but on Windows these are not exported because this if(tools:::.OStype() == "unix") { export(mccollect, mcparallel, mc.reset.stream, mcaffinity) } appears at src/library/parallel/NAMESPACE:6 of svn r61857. So should I be doing if (tools:::.OStype() == "unix") { importFrom(parallel, mccollect, mcparallel) }

Dear maintainers of the parallel package, I ran into an issue with the parallel package in R-3.1.0. The following code prints the message "NULL!" quite a lot. library(parallel) for (n in 1:1000) { p <- mcparallel(sqrt(n)) res <- mccollect(p, wait=FALSE, timeout=1000) mccollect(p) if (is.null(res)) cat(n," NULL!\n") } It does not happen in

QUESTION: Is it possible to query number of active jobs running after launching them with parallel::mcparallel()? For example, if I launch 3 jobs using: > library(parallel) > f <- lapply(1:3, FUN=mcparallel) then I can inspect them as: > str(f) List of 3 $ :List of 2 ..$ pid: int 142225 ..$ fd : int [1:2] 8 13 ..- attr(*, "class")= chr [1:3] "parallelJob"

On Fri, Aug 31, 2018 at 3:35 PM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > On 08/31/2018 03:13 PM, G?bor Cs?rdi wrote: > > On Fri, Aug 31, 2018 at 2:51 PM Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > [...] > >> kill(sig=0) is specified by POSIX but indeed as you say there is a race > >> condition due to PID-reuse. In

On 03/25/2015 07:48 PM, Simon Urbanek wrote: > On Mar 25, 2015, at 3:46 PM, Valerie Obenchain <vobencha at fredhutch.org> wrote: > >> Hi Simon, >> >> I'm having trouble with nested parallel workers, specifically, forking inside socket connections. >> > > You simply can't by definition - when you fork *all* the workers share the same connection

Hi Simon, I'm having trouble with nested parallel workers, specifically, forking inside socket connections. When mclapply is called inside a SOCK, PSOCK or FORK worker I get an error in unserialize(). cl <- makeCluster(1, "SOCK") fun = function(i) { library(parallel) mclapply(1:2, sqrt) } Failure occurs after multiple calls to clusterApply: > clusterApply(cl, 1,

Hi, I'd like to test whether a (localhost) PSOCK cluster node is still running or not by its PID, e.g. it may have crashed / core dumped. I'm ok with getting false-positive results due to *another* process with the same PID has since started. I can the PID of each cluster nodes by querying them for their Sys.getpid(), e.g. pids <- parallel::clusterEvalQ(cl, Sys.getpid()) Is there

?mccollect say 'mccollect' returns any results that are available in a list. The results will have the same order as the specified jobs. If there are multiple jobs and a job has a name it will be used to name the result, otherwise its process ID will be used. If none of the specified children are still running, it returns 'NULL'. which does not

On Sat, Jun 8, 2019 at 2:13 PM Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > > On 08/06/2019 7:42 a.m., Gergely Dar?czi wrote: > > Dear All, > > > > I'm using "reg.finalizer" in a function that is to be called in R scripts > > to do some cleanup on success. I have not found a way to run the function > > only if the script run without

hi all, how can i saving R output to docx or Jpeg format? [[alternative HTML version deleted]]

Dear All, I'm using "reg.finalizer" in a function that is to be called in R scripts to do some cleanup on success. I have not found a way to run the function only if the script run without errors, so when the exit code is expected to be 0. What I've tried is checking "geterrmessage()", but unfortunately it's not perfect: if an error was handled with eg

I think recreating tempdir() is ok in an emergency situation, but package code should not be removing tempdir() - it may contain important information. Bill Dunlap TIBCO Software wdunlap tibco.com On Wed, Nov 8, 2017 at 4:55 PM, Henrik Bengtsson <henrik.bengtsson at gmail.com > wrote: > Related to this problem - from R-devel NEWS >

I've been using mclapply and have encountered situations where it gives errors or returns incorrect results. Here's a minimal example, which gives the error on R 2.15.2 on Mac and Linux: library(parallel) f <- function(x) NULL mclapply(1, f, mc.preschedule = FALSE, mc.cores = 1) # Error in sum(sapply(res, inherits, "try-error")) : # invalid 'type' (list) of argument