Currently I'm running the latest version of DSS on MacOSX environment. I just came to notice, after months of using them, I discovered that it consumed large portion of my hard drive. You see, I'm running an older MacBook Air model which came with 250GB of storage. When I had it setup for the first time, I did the partition, so that I could have the first one, as where my OSX's residing (also DSS sits here), while the remaining would be for storage purposes, divided evenly.
Now here comes the situation, my system partition currently running out of space, while the other relatively still could hold much larger space. My question, would it be okay (as in it won't break anything or any DSS functionalities), if I just moved directly the dss_home directory, from my home partition to my data partition?
Good news, this is fairly simple and documented.
The hardest part is capturing any Python Environments you've created. You can skip the whole UIF thing for Mac. 🙂
Just want to add up a minor observation from migrating the dss_home folder on MacOS this way.
- If you boot-up the DSS instance from the command-line interface, everything remain intact and nothing has changed, like nothing ever happened (projects, dashboard, wiki, comments), everything relatively the same as they were prior the migration.
- But, if you boot-up from the shortcut icons from the Application folder, there's seem to be glitches, since a lot of my projects and dashboard gone missing.
But that's okay, I don't mind booting-up from the command line. 🙂
I'm glad it worked.
The mac app of DSS is very good to test DSS and to explore around.
If you are going to use it extensively it's probably better to switch to the tar version, that you can grab from the download website, like this one for example.
This will allow you more flexibility, especially when it comes to upgrade DSS. It doesn't come with an app shortcut, however.
Careful not to download the linux version.
Architect @ Dataiku
Hi @Omar, thanks for the quick updates. Been using it not for long actually, but fell in love with the software ever since. And to my surprise, it has consumed over then 30GB of my hard drive space, but it was worth-it. Since nowadays I got better understanding of what Dataiku capable of delivering, and it gave me better overview of what Machine Learning it's all about. 😊
Thank you for your feedback @gerryleonugroho !