Dear all,
I got an issue trying to parse excel files in parallel using XLConnect, the
process hangs forever.
Martin Studer, the maintainer of XLConnect kindly investigated the issue,
identified rJava as a possible cause of the problem:
This does not work (hangs):
library(parallel)
require(rJava)
.jinit()
res <- mclapply(1:2, function(i) {
J("java.lang.Runtime")$getRuntime()$gc()
1
}, mc.cores = 2)
but this works:
library(parallel)
res <- mclapply(1:2, function(i) {
require(rJava)
.jinit()
J("java.lang.Runtime")$getRuntime()$gc()
1
}, mc.cores = 2)
To cite Martin, it seems to work with mclapply when the JVM process is
initialized after forking.
Is this a bug or a limitation of rJava ?
Or is there a good practice for rJava clients to avoid this problem ?
Best,
Karl
P.S.
> sessionInfo()
R version 3.0.1 (2013-05-16)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=C LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] tools_3.0.1
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