Installation on MacMini M2 Apple Silicon

Turribeach

Not really a question but a quick post to say that I am very impressed with how easy it was to setup Dataiku on a MacMini M2 Apple Silicon. Given that Dataiku is not officially supported other than under Linux I was quite surprised to see that Dataiku has developed an application to install and run Dataiku on MacOS in a transparent way. It could not been more easy to install it as it took care of all the other stuff (OpenJDK Java, Python, etc) behind the scenes. There was no need for me to do anything over the command line and it simply started first time without any issues. Furthermore anything I tried so far worked fine, like connecting to Google's BigQuery, Jupyter notebooks, running recipes, using the Dataiku API, creating code environments, etc.

https://www.dataiku.com/product/get-started/mac/

Obviously my experience is a test case of only 1 but I do see constantly on the Dataiku Community how new users are using Dataiku on Windows as well so I suspect there is a similar approach there too. While full support for Windows and MacOS would be the gold standard this is almost as good as that or even better.

I guess that most people using Dataiku on Windows or MacOS would be doing things for themselves or will be testing or even trying things as consultants. All Dataiku employees I have met used MacOS laptops themselves although these were Intel Macs but I presume they may have started to use Apple Silicon Macs too as obviously with Apple having completed the migrtion to Apple Silicon Intel Macs are a thing of the past.

So my congratulations to whoever developed this solution as it seems very well done!

tgb417

@Turribeach

I will +1 all of your comments. I've been using this solution for More than a year now, and things are working well. Thank You Dataiku team.

In addition to all of the current good things. There are two things I would like to be able to do:

• Use the GPU or Neural Network hardware in my Macbook Pro M1 Max Chip for things like Neural Networks. I suspect this is do-able baed on posts like this.
  https://towardsdatascience.com/installing-pytorch-on-apple-m1-chip-with-gpu-acceleration-3351dc44d67c
  But, I have not had the time to work out the details. If anyone has done this successfully. Let's open a thread here to discuss in further detail.
• I wish that more things would run under native M1 rather than run through Rosetta Intel Code Emulation. Although the emulation is remarkable. It sill would be great to see most code running as native M1 code.