parallelize distance matrix
You'll have to do clusterExport(cl, c("ll")) before you call parRapply.
Please see ?`parRapply` and pages 10 and 11 of the parallel::parallel
vignette.
HTH,
Vijay.
On Tue, Aug 21, 2018 at 2:54 PM Roman Lu?trik <roman.lustrik at gmail.com>
wrote:
Cross posted on SO: https://stackoverflow.com/questions/51952776/parallelization-apply-to-parrapply On Tue, Aug 21, 2018 at 8:15 PM Ariel Fuentesdi <ariel.fuentesdi at usach.cl> wrote:
Hi, I want to parallelize the calculation of a distance matrix, I've
tried
but I wasn't succesful, this is what I did with a training data. My data set is: ll <- matrix(c(5, 6, 60, 60), ncol=2) And I use the function *spDistsN1* from the library *"sp"* to obtain a distance matrix with *apply*: apply(ll, 1, function(x) spDistsN1(as.matrix(ll), x, longlat = T)) But I want to do it with parallelization, so for that: library(parallel) ncore <- detectCores() cl <- makeCluster(ncore) clusterEvalQ(cl = cl, expr = c(library(sp))) parRapply(cl = cl, x = ll, FUN = function(x) spDistsN1(as.matrix(ll), x, longlat = T)) It shows the following error: *Error in checkForRemoteErrors(val) : 4 nodes produced errors; first
error:
object 'll' not found*
How do I fix it?
Regards,
Ariel Fuentes
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