在Sagemaker Jupyter笔记本实例上安装RODBC或ODBC时出错 [英] Error installing RODBC or ODBC on a Sagemaker Jupyter NoteBook Instance

问题描述

我一直在尝试从Sagemaker Jupyter Notebook实例建立与Teradata的连接.我正在尝试像通过R Studio那样进行操作.但是，当我尝试在实例中安装该软件包时，都会收到非零的退出状态错误.

我尝试安装以下方法:

remotes::install_github() 

或

devtools::install_github()

，还有:

install.packages('odbc', repo="https://cran.rstudio.com/")

我在RODBC上尝试了相同的操作，并且得到了相同的警告或错误.

关于如何解决这个问题的任何想法吗?

谢谢.

更新: 如果我运行以下代码:

devtools::install_github("r-dbi/odbc")`

我收到以下错误(这只是摘录):

Error: Failed to install 'odbc' from GitHub:
  System command error, exit status: 1, stdout + stderr (last 10 lines):
E> ** testing if installed package can be loaded from temporary location
E> Error: package or namespace load failed for ‘odbc’ in dyn.load(file, DLLpath = DLLpath, ...):
E>  unable to load shared object '/tmp/RtmpBuMhbW/Rinst32846cdd20a9/00LOCK-odbc/00new/odbc/libs/odbc.so':
E>   libodbc.so.2: cannot open shared object file: No such file or directory
E> Error: loading failed
E> Execution halted
E> ERROR: loading failed
E> * removing ‘/tmp/RtmpBuMhbW/Rinst32846cdd20a9/odbc’
E>       -----------------------------------
E> ERROR: package installation failed
Traceback:

解决方案

好了，经过数小时的阅读AWS/Sagemaker/Conda/R文档，我得出的结论是，我不知道如何解释这种现象./p>

尽管如此，我还是找到了解决方法！

因此，我们知道如何通过Jupyter终端或直接从.ipynb文件中的单元格安装软件包.但是，如果您尝试像在终端机或Python内核中那样在R内核中运行这些命令，则会遇到错误.

此外，对于某些在终端中甚至在Python内核上安装它的人来说，只需将conda安装在其他环境中即可即可.是的，事实证明您的Jupyter实例上有几个环境.

因此，就像我说的那样，您要使用conda install命令，而不要使用pip，sudo或yum命令.

让您的生活更轻松.如果install.packages()和install_github()不起作用，则下面是在R内核单元上运行以将软件包直接安装到正确环境中所需的代码:

system(command = 'conda install -c r packageName --yes')

示例:

system(command = 'conda install -c r tidyverse --yes')

就是这样.之后，您可以调用library()并照常继续执行R工作流程.

希望对大家有帮助！

I have been trying to establish a connection to Teradata from a Sagemaker Jupyter Notebook instance. I was trying to do it the way I would through R Studio. But when ever I try to install the package in the instance I get an non-zero exit status error.

I have tried installing the following ways:

remotes::install_github() 

or

devtools::install_github()

and also:

install.packages('odbc', repo="https://cran.rstudio.com/")

I tryed the same with RODBC, and I get the same warnings or errors.

Any ideas on how I can get around this problem?

Thanks in advance.

UPDATE: If I run this line of code:

devtools::install_github("r-dbi/odbc")`

I get the following error (This is just an extract):

Error: Failed to install 'odbc' from GitHub:
  System command error, exit status: 1, stdout + stderr (last 10 lines):
E> ** testing if installed package can be loaded from temporary location
E> Error: package or namespace load failed for ‘odbc’ in dyn.load(file, DLLpath = DLLpath, ...):
E>  unable to load shared object '/tmp/RtmpBuMhbW/Rinst32846cdd20a9/00LOCK-odbc/00new/odbc/libs/odbc.so':
E>   libodbc.so.2: cannot open shared object file: No such file or directory
E> Error: loading failed
E> Execution halted
E> ERROR: loading failed
E> * removing ‘/tmp/RtmpBuMhbW/Rinst32846cdd20a9/odbc’
E>       -----------------------------------
E> ERROR: package installation failed
Traceback:

解决方案

Alright, after hours of reading AWS/Sagemaker/Conda/R documentation I arrived at the conclusion that, I don't know how to explain the phenomena.

Nonetheless, I have found a workaround!

So we know how we can install packages through the Jupyter terminal or directly from a cell in the .ipynb file. Nonetheless, if you try to run those commands inside the R kernel just like you would on the terminal or in a Python kernel you would run into an error.

Also, for some people installing it in the terminal, or even on a Python kernel might just make conda install the package on a different environment. Yes, turns out there are a couple of environments on your Jupyter instance.

So, to get to the point, just like I said, you would use a conda install command, not a pip, sudo or yum command.

Make your life easier. Here is the code that you would need to run on your R Kernel cell, to install a package directly to the correct environment if, install.packages() and install_github() didn't work:

system(command = 'conda install -c r packageName --yes')

Example:

system(command = 'conda install -c r tidyverse --yes')

And that's it. After that you can call library() and resume your R workflow as you do.

Hope this helps guys!

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