如何获得对Google Cloud中AI Platform R 3.6笔记本实例中库文件夹的写访问权 [英] How to get write access to the library folder in AI Platform R 3.6 notebook instance in Google Cloud

问题描述

我无法在Google Cloud的AI平台的JupyterLab中安装R软件包. 我是我工作的项目的所有者. 我创建了一个新的R 3.6实例，并将其权限设置为默认的Compute Engine默认服务帐户.

I am having trouble installing R packages in JupyterLab in AI Platform on Google Cloud. I am the owner of the project I work in. I have created a new R 3.6 instance with the permission set to the default Compute Engine default service account.

问题是，即使我是项目所有者，由于某种原因，我也没有对保存软件包的文件夹的写访问权，因此应该对项目中的所有内容都具有写访问权.

The issue is that I for some reason do not have write access for the folder where packages are saved even though I am project owner and therefore should have write access to everything in the project.

这是我尝试过的内容以及收到的错误消息:

Here is what I have tried and the error message I get:

install.packages("RCurl", repos='http://cran.us.r-project.org')

这是我收到的错误消息:

And this is the error message I get:

Warning message in install.packages("RCurl", repos = "http://cran.us.r-project.org"):
"'lib = "/opt/conda/lib/R/library"' is not writable"
Error in install.packages("RCurl", repos = "http://cran.us.r-project.org"): unable to install packages
Traceback:

1. install.packages("RCurl", repos = "http://cran.us.r-project.org")
2. stop("unable to install packages")

我尝试同时设置repos参数和不设置参数.

I have tried with both setting the repos argument and not setting it.

推荐答案

通过设计，默认的jupyter用户没有root访问权限，因为您应该

By design the default jupyter user does not have the root access because you are supposed to install packages locally. For example (be aware that you can replace /tmp with a local directory): install.packages("leaflet", lib="/tmp")

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