I am running an MMM with data on weekly basis once I run OutputCollect() function I get this error message.
"Error in filter():
ℹ In argument: .data$solID == sid.
Caused by error:
! vector memory limit of 16.0 Gb reached, see mem.maxVSize()
Run rlang::last_trace() to see where the error occurred."
Overall the export takes long to calculate the response curves. Am runnung 8 trials with 2k iterations.
I also tried running outputcollect for the best model Id only to reduce the load but it still runs the whole function. Here is my output collect script.
OutputCollect <- robyn_outputs(
- InputCollect = InputCollect,
- OutputModels = OutputModels,
- select_model = best_id, # <- nur diese Lösung
- export = FALSE, # keine Massen-Exports
- pareto_fronts = 1,
- pareto_min = 1,
- plot_folder = NULL,
- cores = 1
- )
I have also used these settings for better performance, I think it does help performance but still doesn't solve the isse.
Sys.setenv(OMP_NUM_THREADS="1", VECLIB_MAXIMUM_THREADS="1")
options(device = "pdf"); pdf(NULL)
Any tips would be highly appreciated. Thanks!
+++++++++
session Info:
R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.5
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/Fortaleza
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ISOweek_0.6-2 googlesheets4_1.1.2 Robyn_3.12.1 reticulate_1.44.0
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 generics_0.1.4 tidyr_1.3.1 prophet_1.0 xml2_1.4.1
[6] shape_1.4.6.1 stringi_1.8.7 lattice_0.22-6 digest_0.6.37 magrittr_2.0.4
[11] pROC_1.19.0.1 grid_4.4.1 timechange_0.3.0 RColorBrewer_1.1-3 iterators_1.0.14
[16] cellranger_1.1.0 foreach_1.5.2 doParallel_1.0.17 jsonlite_2.0.0 glmnet_4.1-10
[21] Matrix_1.7-0 zip_2.3.3 survival_3.6-4 googledrive_2.1.1 httr_1.4.7
[26] rvest_1.0.5 rpart.plot_3.1.3 purrr_1.2.0 doRNG_1.8.6.2 scales_1.4.0
[31] codetools_0.2-20 cli_3.6.5 rlang_1.1.6 splines_4.4.1 withr_3.0.2
[36] yaml_2.3.10 tools_4.4.1 parallel_4.4.1 gargle_1.6.0 nloptr_2.2.1
[41] dplyr_1.1.4 ggplot2_4.0.0 rngtools_1.5.2 curl_7.0.0 png_0.1-8
[46] vctrs_0.6.5 lares_5.3.2 R6_2.6.1 rpart_4.1.23 ggridges_0.5.7
[51] lifecycle_1.0.4 lubridate_1.9.4 stringr_1.6.0 fs_1.6.6 pkgconfig_2.0.3
[56] ggcorrplot_0.1.4.1 RcppParallel_5.1.11-1 pillar_1.11.1 openxlsx_4.2.8.1 gtable_0.3.6
[61] glue_1.8.0 Rcpp_1.1.0 tibble_3.3.0 tidyselect_1.2.1 farver_2.1.2
[66] patchwork_1.3.2 compiler_4.4.1 S7_0.2.0 askpass_1.2.1 openssl_2.3.4
I am running an MMM with data on weekly basis once I run OutputCollect() function I get this error message.
"Error in
filter():ℹ In argument:
.data$solID == sid.Caused by error:
! vector memory limit of 16.0 Gb reached, see mem.maxVSize()
Run
rlang::last_trace()to see where the error occurred."Overall the export takes long to calculate the response curves. Am runnung 8 trials with 2k iterations.
I also tried running outputcollect for the best model Id only to reduce the load but it still runs the whole function. Here is my output collect script.
I have also used these settings for better performance, I think it does help performance but still doesn't solve the isse.
Sys.setenv(OMP_NUM_THREADS="1", VECLIB_MAXIMUM_THREADS="1")
options(device = "pdf"); pdf(NULL)
Any tips would be highly appreciated. Thanks!
+++++++++
session Info:
R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.5
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/Fortaleza
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ISOweek_0.6-2 googlesheets4_1.1.2 Robyn_3.12.1 reticulate_1.44.0
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 generics_0.1.4 tidyr_1.3.1 prophet_1.0 xml2_1.4.1
[6] shape_1.4.6.1 stringi_1.8.7 lattice_0.22-6 digest_0.6.37 magrittr_2.0.4
[11] pROC_1.19.0.1 grid_4.4.1 timechange_0.3.0 RColorBrewer_1.1-3 iterators_1.0.14
[16] cellranger_1.1.0 foreach_1.5.2 doParallel_1.0.17 jsonlite_2.0.0 glmnet_4.1-10
[21] Matrix_1.7-0 zip_2.3.3 survival_3.6-4 googledrive_2.1.1 httr_1.4.7
[26] rvest_1.0.5 rpart.plot_3.1.3 purrr_1.2.0 doRNG_1.8.6.2 scales_1.4.0
[31] codetools_0.2-20 cli_3.6.5 rlang_1.1.6 splines_4.4.1 withr_3.0.2
[36] yaml_2.3.10 tools_4.4.1 parallel_4.4.1 gargle_1.6.0 nloptr_2.2.1
[41] dplyr_1.1.4 ggplot2_4.0.0 rngtools_1.5.2 curl_7.0.0 png_0.1-8
[46] vctrs_0.6.5 lares_5.3.2 R6_2.6.1 rpart_4.1.23 ggridges_0.5.7
[51] lifecycle_1.0.4 lubridate_1.9.4 stringr_1.6.0 fs_1.6.6 pkgconfig_2.0.3
[56] ggcorrplot_0.1.4.1 RcppParallel_5.1.11-1 pillar_1.11.1 openxlsx_4.2.8.1 gtable_0.3.6
[61] glue_1.8.0 Rcpp_1.1.0 tibble_3.3.0 tidyselect_1.2.1 farver_2.1.2
[66] patchwork_1.3.2 compiler_4.4.1 S7_0.2.0 askpass_1.2.1 openssl_2.3.4