RAM usage when using python/R views

Hi there,

I was not able to find any details on RAM/disc usage for images coming out from python/R views… There is clear settings (https://www.knime.com/faq#q18) for tables and I would like to know whether the rules are applied on images as well or there is another setting for them that I just can not see :slight_smile: .

Thank you in advance!


Hi @weiclav,

Images for R and Python Views are saved as image files into a temporary directory. Once you save and close a workflow with such nodes, the images are stored in the workflow directory in your workspace and they are deleted from the temporary directory.

In addition to that, the image will be kept in memory after execution. The Memory Policy that you are referring to only applies to data tables.


Hi Stefan,

thank you for yor response!

So when I open any workflow, every single image in that workflow is loaded into RAM and this can not be changed, correct? Or does this RAM usage (in parallel to the temp folder) apply only to new, not saved nodes producing images?

Thank you again!