R引导时是否有2GB的内存使用限制? [英] Is there a 2GB memory usage limit when R boots?
问题描述
我使用以下代码在.Rprofile中加载一些数据(当我使用Rstudio切换到项目时，这是我的项目文件夹中的R脚本会自动运行).
data_files <- list.files(pattern="\\.(RData|rda)$")
if("data.rda" %in% data_files) {
attach(what="data.rda",
pos = 2)
cat("The file 'data.rda' was attached to the search path under 'file:data.rda'.\n\n")
}
正在加载的数据相对较大:
Type Size PrettySize Rows Columns
individual_viewings_26 data.frame 1547911120 [1] "1.4 Gb" 3685312 63
viewing_statements_all data.table 892316088 [1] "851 Mb" 3431935 38
weights data.frame 373135464 [1] "355.8 Mb" 3331538 14
pet data.table 63926168 [1] "61 Mb" 227384 34
但是我有16 GB，我可以分配它们:
> memory.limit()
[1] 16289
当我的数据不那么大时，我没有任何问题.我最近在data.rda中保存了更多数据帧，并且我的R会话在启动时突然失败(当我切换到Rstudio中的项目并执行.Rprofile时):
Error: cannot allocate vector of size 26.2 Mb
In addition: Warning messages:
1: Reached total allocation of 2047Mb: see help(memory.size)
2: Reached total allocation of 2047Mb: see help(memory.size)
3: Reached total allocation of 2047Mb: see help(memory.size)
4: Reached total allocation of 2047Mb: see help(memory.size)
我怀疑出于某种原因，启动时内存限制设置为2GB?有什么办法可以改变吗?
添加了操作系统和软件版本
> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Edit2:澄清一下，我能够通过运行代码自己加载数据，我有足够的可用内存，并且R进程在日常工作中通常使用高达10GB的内存.问题是，当R启动并执行.Rprofile ...时，显然存在2GB的内存限制.
是的，至少在执行用户配置文件(.Rprofile文件和.First()函数)时，R启动时有2GB的限制.
证明:
Rprofile的内容:
message("Available memory when .Rprofile is sourced: ", memory.limit())
.First <- function() {
message("Available memory when .First() is called: ", memory.limit())
}
启动时输出
Available memory when .Rprofile is sourced: 2047
Available memory when .First() is called: 2047
R开始后
memory.limit的输出
> memory.limit()
[1] 16289
I have the following code for loading some data in my .Rprofile (which is a R script in my project folder running automatically when I switch to the project with Rstudio).
data_files <- list.files(pattern="\\.(RData|rda)$")
if("data.rda" %in% data_files) {
attach(what="data.rda",
pos = 2)
cat("The file 'data.rda' was attached to the search path under 'file:data.rda'.\n\n")
}
The data being loaded is relatively big:
Type Size PrettySize Rows Columns
individual_viewings_26 data.frame 1547911120 [1] "1.4 Gb" 3685312 63
viewing_statements_all data.table 892316088 [1] "851 Mb" 3431935 38
weights data.frame 373135464 [1] "355.8 Mb" 3331538 14
pet data.table 63926168 [1] "61 Mb" 227384 34
But I have 16 GB and I can allocate them:
> memory.limit()
[1] 16289
When my data was not as big, I did not have any issue. I recently saved some more data frames in data.rda and my R session suddenly fails at start-up (when I switch to the project in Rstudio and .Rprofile is executed):
Error: cannot allocate vector of size 26.2 Mb
In addition: Warning messages:
1: Reached total allocation of 2047Mb: see help(memory.size)
2: Reached total allocation of 2047Mb: see help(memory.size)
3: Reached total allocation of 2047Mb: see help(memory.size)
4: Reached total allocation of 2047Mb: see help(memory.size)
I suspect that for some reason, the memory limit is set at 2GB at boot? Any way I can change that?
Edit: Added OS and software version
> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Edit2: Just to clarify, I am able to load the data myself by running the code, I have plenty of available memory and the R process commonly uses up to 10GB during my daily work. The problem is, there is a apparently a 2GB memory limit when R boots and executes the .Rprofile...
Yes, there is a 2GB limit when R starts, at least when the user profile (.Rprofile files and .First() functions) are executed.
Proof:
Content of Rprofile:
message("Available memory when .Rprofile is sourced: ", memory.limit())
.First <- function() {
message("Available memory when .First() is called: ", memory.limit())
}
Output at startup
Available memory when .Rprofile is sourced: 2047
Available memory when .First() is called: 2047
Output of memory.limit once R has started
> memory.limit()
[1] 16289
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