mlr / parallelMap: How to pass libPaths to workers when working with checkpoint?

Question

This is basically the same question as this How to set .libPaths (checkpoint) on workers when running parallel computation in R, but now addressing parallelization of mlr model fits. I understand that I need to use parallelMap with mlr, but how can I make sure that each worker uses the correct .libPaths?

remove.packages("mlr")
remove.packages("rpart")

checkpoint::checkpoint("2018-09-01",
                       scanForPackages = TRUE)

library(mlr)
library(parallelMap)
library(rpart)
parallelStartSocket(2L)

task = makeClassifTask(data = iris, target = "Species")
learner = makeLearner("classif.rpart", minsplit = 7, predict.type = "prob")
mod = resample(learner, task, resampling = cv5)

parallelStop()

Error in parallelLibrary("mlr", master = FALSE, level = "mlr.resample", : Packages could not be loaded on all slaves: mlr.

Session info:

R version 3.5.1 (2018-07-02) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 7 x64 (build 7601) Service Pack 1

Matrix products: default

locale: [1] LC_COLLATE=German_Germany.1252 LC_CTYPE=German_Germany.1252 LC_MONETARY=German_Germany.1252 [4] LC_NUMERIC=C LC_TIME=German_Germany.1252

attached base packages: [1] stats graphics grDevices utils
datasets methods base

other attached packages: [1] rpart_4.1-13 parallelMap_1.3
mlr_2.13 ParamHelpers_1.11

loaded via a namespace (and not attached): [1] Rcpp_0.12.18
pillar_1.3.0 compiler_3.5.1 plyr_1.8.4 bindr_0.1.1
tools_3.5.1 [7] tibble_1.4.2 gtable_0.2.0
checkmate_1.8.5 lattice_0.20-35 pkgconfig_2.0.2 rlang_0.2.2
[13] Matrix_1.2-14 fastmatch_1.1-0 rstudioapi_0.7 yaml_2.2.0 parallel_3.5.1 bindrcpp_0.2.2 [19] dplyr_0.7.6 grid_3.5.1 tidyselect_0.2.4 glue_1.3.0 data.table_1.11.4 R6_2.2.2
[25] XML_3.98-1.16 survival_2.42-3 ggplot2_3.0.0 purrr_0.2.5 magrittr_1.5 backports_1.1.2 [31] scales_1.0.0 BBmisc_1.11 splines_3.5.1 assertthat_0.2.0 checkpoint_0.4.3 colorspace_1.3-2 [37] stringi_1.1.7 lazyeval_0.2.1 munsell_0.5.0
crayon_1.3.4

Answer 1

It works for me if I change the default library path to the checkpoint directory with R_LIBS.

remove.packages("mlr")
remove.packages("rpart")

print(.libPaths())
checkpoint::checkpoint("2018-09-01",
                       scanForPackages = TRUE)
print(.libPaths())
Sys.setenv(R_LIBS = paste(.libPaths()[1], Sys.getenv("R_LIBS"), sep = .Platform$path.sep))

library(mlr)
library(parallelMap)
library(rpart)
parallelStartSocket(2L)

task = makeClassifTask(data = iris, target = "Species")
learner = makeLearner("classif.rpart", minsplit = 7, predict.type = "prob")
mod = resample(learner, task, resampling = cv5)

parallelStop()