如何将内存中的数据帧的增量部分拆分为R

我有一个大数据集（

dat1

）

运行一段时间后，我得到以下结果：

Error: cannot allocate vector of size 1.8 Mb in R

错误：无法分配大小为2.0 Mb的向量

> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=Hebrew_Israel.1255  LC_CTYPE=Hebrew_Israel.1255    LC_MONETARY=Hebrew_Israel.1255
[4] LC_NUMERIC=C                   LC_TIME=Hebrew_Israel.1255    

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

other attached packages:
 [1] dplyr_0.5.0            rpart_4.1-10           partykit_1.1-1         plyr_1.8.4             caret_6.0-76          
 [6] ggplot2_2.2.1          lattice_0.20-34        data.table_1.10.4      arulesSequences_0.2-17 arules_1.5-0          
[11] Matrix_1.2-7.1        

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.11       RWeka_0.4-34       visNetwork_1.0.3   assertthat_0.2.0   digest_0.6.12      foreach_1.4.3     
 [7] R6_2.2.1           MatrixModels_0.4-1 stats4_3.3.2       RWekajars_3.9.1-3  rlang_0.1.1        lazyeval_0.2.0    
[13] curl_2.6           SparseM_1.77       rstudioapi_0.6     minqa_1.2.4        car_2.1-4          nloptr_1.0.4      
[19] DiagrammeR_0.9.0   splines_3.3.2      lme4_1.1-13        stringr_1.2.0      htmlwidgets_0.8    igraph_1.0.1      
[25] munsell_0.4.3      influenceR_0.1.0   rgexf_0.15.3       mgcv_1.8-15        htmltools_0.3.6    nnet_7.3-12       
[31] tibble_1.3.3       gridExtra_2.2.1    codetools_0.2-15   XML_3.98-1.7       viridisLite_0.2.0  MASS_7.3-45       
[37] ModelMetrics_1.1.0 nlme_3.1-128       jsonlite_1.5       gtable_0.2.0       DBI_0.6-1          magrittr_1.5      
[43] RMOAjars_1.0       scales_0.4.1       stringi_1.1.5      reshape2_1.4.2     viridis_0.4.0      RMOA_1.1          
[49] brew_1.0-6         Formula_1.2-1      data.tree_0.7.0    RColorBrewer_1.1-2 iterators_1.0.8    tools_3.3.2       
[55] Rook_1.1-1         survival_2.39-5    pbkrtest_0.4-7     parallel_3.3.2     colorspace_1.3-2   rJava_0.9-9       
[61] quantreg_5.33 

---

这似乎很奇怪。。。1.8MB并没有那么大。例如，

a
d@Joseph Wood，只需添加一个数据集，您就可以用更小的数据集生成您想要的内容。例如，首先尝试使用
mtcars
数据集。
e<-list()
e[[1]]<-d[[1]]
for (i in 1:997 ) {e[[i+1]]<-bind_rows(e[[i]],d[[i+1]])}

Error: cannot allocate vector of size 1.8 Mb in R

> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=Hebrew_Israel.1255  LC_CTYPE=Hebrew_Israel.1255    LC_MONETARY=Hebrew_Israel.1255
[4] LC_NUMERIC=C                   LC_TIME=Hebrew_Israel.1255    

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

other attached packages:
 [1] dplyr_0.5.0            rpart_4.1-10           partykit_1.1-1         plyr_1.8.4             caret_6.0-76          
 [6] ggplot2_2.2.1          lattice_0.20-34        data.table_1.10.4      arulesSequences_0.2-17 arules_1.5-0          
[11] Matrix_1.2-7.1        

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.11       RWeka_0.4-34       visNetwork_1.0.3   assertthat_0.2.0   digest_0.6.12      foreach_1.4.3     
 [7] R6_2.2.1           MatrixModels_0.4-1 stats4_3.3.2       RWekajars_3.9.1-3  rlang_0.1.1        lazyeval_0.2.0    
[13] curl_2.6           SparseM_1.77       rstudioapi_0.6     minqa_1.2.4        car_2.1-4          nloptr_1.0.4      
[19] DiagrammeR_0.9.0   splines_3.3.2      lme4_1.1-13        stringr_1.2.0      htmlwidgets_0.8    igraph_1.0.1      
[25] munsell_0.4.3      influenceR_0.1.0   rgexf_0.15.3       mgcv_1.8-15        htmltools_0.3.6    nnet_7.3-12       
[31] tibble_1.3.3       gridExtra_2.2.1    codetools_0.2-15   XML_3.98-1.7       viridisLite_0.2.0  MASS_7.3-45       
[37] ModelMetrics_1.1.0 nlme_3.1-128       jsonlite_1.5       gtable_0.2.0       DBI_0.6-1          magrittr_1.5      
[43] RMOAjars_1.0       scales_0.4.1       stringi_1.1.5      reshape2_1.4.2     viridis_0.4.0      RMOA_1.1          
[49] brew_1.0-6         Formula_1.2-1      data.tree_0.7.0    RColorBrewer_1.1-2 iterators_1.0.8    tools_3.3.2       
[55] Rook_1.1-1         survival_2.39-5    pbkrtest_0.4-7     parallel_3.3.2     colorspace_1.3-2   rJava_0.9-9       
[61] quantreg_5.33