Call Julia lang in Notebooks inside Dataiku ?

[Florent]

I have Julia installed on my CentOS 7 server with Dataiku. Is there a smart way to open notebooks with IJulia inside Dataiku ?



Regards,

Florent

[kldehoff]

Perhaps a bit late on this post, but there is a somewhat hack-ish way to load the Julia kernel inside Dataiku.  Please note that I have only accomplished this on a single-user setup, although it is likely to work similarly for a multi-user setup.

1. Make sure Julia is installed and on the current (Dataiku) user path.
2. Create and run a new shell recipe (output to an empty folder if required) with the following contents:

   julia -E 'using Pkg; Pkg.add("IJulia")'

   This will install the IJulia package and add the IJulia kernel to Dataiku's list of kernels when run
3. Start a new Jupyter notebook (any kernel will do)
4. Change the kernel to "Julia x.y.z" (x.y.z is the installed version)

In addition, it is possible using the PyCall and DataFrames packages to load Dataiku data into Julia.  It may be possible to save it back in a similar fashion, but I have not attempted this yet.

For loading Dataiku datasets, the following template should work, but requires the PyCall.jl, Pandas.jl, and DataFrames.jl packages to be installed.

#this forces PyCall to reference the built-in python environment for Dataiku
ENV["PYTHON"] = "/data/dataiku/bin/python"
Pkg.build("PyCall")

using PyCall, Pandas, DataFrames

#load Dataiku Python libraries
dataiku = pyimport("dataiku")
pd = pyimport("pandas")

#load the dataset into both a Pandas dataframe and a Julia Dataframes dataframe
mydataset = dataiku.Dataset("test")
pd_df = Pandas.DataFrame(mydataset.get_dataframe())
jl_df = DataFrames.DataFrame(df)

#test the load
Pandas.head(pd_df)
DataFrames.head(jl_df)

[CoreyS]

It's never too late! Thank you for your contribution.