r - 已达到 DLL 的最大数量

Question

我在尝试加载新库时在 R 中遇到此错误。

Installation failed: unable to load shared object 'C:/R/R-3.4.0/library/curl/libs/x64/curl.dll':
  `maximal number of DLLs reached...

与curl无关，可以是任何库。我的 sessionInfo 如下所示:

R version 3.4.0 (2017-04-21)
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=English_United Kingdom.1252 
[2] LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

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

other attached packages:
 [1] M3Drop_1.2.0        numDeriv_2016.8-1   bindrcpp_0.2       
 [4] Seurat_2.0.1        Matrix_1.2-11       cowplot_0.8.0      
 [7] scater_1.4.0        Biobase_2.36.2      BiocGenerics_0.22.0
[10] tidyr_0.6.3         dplyr_0.7.2         ggplot2_2.2.1      
[13] extrafont_0.17     

loaded via a namespace (and not attached):
  [1] shinydashboard_0.6.1       R.utils_2.5.0             
  [3] lme4_1.1-13                RSQLite_2.0               
  [5] AnnotationDbi_1.38.2       htmlwidgets_0.9           
  [7] grid_3.4.0                 trimcluster_0.1-2         
  [9] ranger_0.8.0               BiocParallel_1.10.1       
 [11] Rtsne_0.13                 devtools_1.13.3           
 [13] munsell_0.4.3              codetools_0.2-15          
 [15] ica_1.0-1                  captioner_2.2.3           
 [17] statmod_1.4.30             withr_2.0.0               
 [19] colorspace_1.3-2           knitr_1.16                
 [21] stats4_3.4.0               ROCR_1.0-7                
 [23] robustbase_0.92-7          dtw_1.18-1                
 [25] Rttf2pt1_1.3.4             NMF_0.20.6                
 [27] labeling_0.3               lars_1.2                  
 [29] tximport_1.4.0             bbmle_1.0.19              
 [31] GenomeInfoDbData_0.99.0    mnormt_1.5-5              
 [33] bit64_0.9-7                rhdf5_2.20.0              
 [35] diptest_0.75-7             R6_2.2.2                  
 [37] doParallel_1.0.10          GenomeInfoDb_1.12.2       
 [39] ggbeeswarm_0.6.0           VGAM_1.0-4                
 [41] locfit_1.5-9.1             flexmix_2.3-14            
 [43] bitops_1.0-6               DelayedArray_0.2.7        
 [45] assertthat_0.2.0           SDMTools_1.1-221          
 [47] scales_0.4.1               nnet_7.3-12               
 [49] ggjoy_0.3.0                beeswarm_0.2.3            
 [51] gtable_0.2.0               rlang_0.1.2               
 [53] MatrixModels_0.4-1         genefilter_1.58.1         
 [55] scatterplot3d_0.3-40       splines_3.4.0             
 [57] extrafontdb_1.0            lazyeval_0.2.0            
 [59] ModelMetrics_1.1.0         acepack_1.4.1             
 [61] checkmate_1.8.3            reshape2_1.4.2            
 [63] backports_1.1.0            httpuv_1.3.5              
 [65] Hmisc_4.0-3                caret_6.0-76              
 [67] tools_3.4.0                gridBase_0.4-7            
 [69] gplots_3.0.1               RColorBrewer_1.1-2        
 [71] proxy_0.4-17               Rcpp_0.12.12              
 [73] plyr_1.8.4                 base64enc_0.1-3           
 [75] zlibbioc_1.22.0            purrr_0.2.3               
 [77] RCurl_1.95-4.8             rpart_4.1-11              
 [79] pbapply_1.3-3              viridis_0.4.0             
 [81] S4Vectors_0.14.3           SummarizedExperiment_1.6.3
 [83] cluster_2.0.6              magrittr_1.5              
 [85] data.table_1.10.4          SparseM_1.77              
 [87] mvtnorm_1.0-6              matrixStats_0.52.2        
 [89] mime_0.5                   xtable_1.8-2              
 [91] pbkrtest_0.4-7             XML_3.98-1.9              
 [93] mclust_5.3                 IRanges_2.10.2            
 [95] gridExtra_2.2.1            compiler_3.4.0            
 [97] biomaRt_2.32.1             tibble_1.3.3              
 [99] KernSmooth_2.23-15         minqa_1.2.4               
[101] R.oo_1.21.0                htmltools_0.3.6           
[103] segmented_0.5-2.1          mgcv_1.8-18               
[105] Formula_1.2-2              geneplotter_1.54.0        
[107] tclust_1.2-7               DBI_0.7                   
[109] diffusionMap_1.1-0         MASS_7.3-47               
[111] fpc_2.1-10                 car_2.1-5                 
[113] R.methodsS3_1.7.1          gdata_2.18.0              
[115] bindr_0.1                  igraph_1.1.2              
[117] GenomicRanges_1.28.4       pkgconfig_2.0.1           
[119] sn_1.5-0                   registry_0.3              
[121] foreign_0.8-69             foreach_1.4.3             
[123] annotate_1.54.0            vipor_0.4.5               
[125] rngtools_1.2.4             pkgmaker_0.22             
[127] XVector_0.16.0             stringr_1.2.0             
[129] digest_0.6.12              tsne_0.1-3                
[131] htmlTable_1.9              edgeR_3.18.1              
[133] kernlab_0.9-25             shiny_1.0.4               
[135] gtools_3.5.0               quantreg_5.33             
[137] modeltools_0.2-21          rjson_0.2.15              
[139] nloptr_1.0.4               nlme_3.1-131              
[141] viridisLite_0.2.0          limma_3.32.5              
[143] lattice_0.20-35            httr_1.3.0                
[145] DEoptimR_1.0-8             survival_2.41-3           
[147] glue_1.1.1                 FNN_1.1                   
[149] prabclus_2.2-6             iterators_1.0.8           
[151] bit_1.1-12                 class_7.3-14              
[153] stringi_1.1.5              mixtools_1.1.0            
[155] blob_1.1.0                 DESeq2_1.16.1             
[157] latticeExtra_0.6-28        caTools_1.17.1            
[159] memoise_1.1.0              irlba_2.2.1               
[161] ape_4.1    

我在 Windows 上，我尝试了 Sys.setenv(R_MAX_NUM_DLLS=500)，来自 this question ，但它似乎没有做任何事情。我试图将它添加到 Rprofile.site 文件并重新启动 R，但我仍然收到错误。卸载库或不加载这么多库等都不是解决方案。我看到了将 R_MAX_NUM_DLLS=500 添加到 .Renviron 文件的选项，但我不确定 Windows 是否有这个。

我想知道有没有人有任何见解。

Answer 1

尝试在系统属性中添加新的环境变量。