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There are a lot of Scala/Spark kernels for IPython/Jupyter:
Does anybody know wich of them is most compatible with IPython/Jupyter and most comfortable to use with:
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A 'kernel' is a program that runs and introspects the user's code. IPython includes a kernel for Python code, and people have written kernels for several other languages. When IPython starts a kernel, it passes it a connection file. This specifies how to set up communications with the frontend.
spark-kernel (homepage) The Spark Kernel enables remote applications to dynamically interact with Apache Spark. It serves as a remote Spark Shell that uses the IPython message protocol to provide a common entrypoint for applications (including IPython itself).
Jupyter notebook is widely used by almost everyone in the data science community. While it's a tool with extensive support for python-based development of machine learning projects, one can also use it for Scala development as well, using the spylon-kernel.
I can't speak for all of them, but I use Spark Kernel and it works very well for using both Scala and Spark.
I found IScala and Jupyter Scala less stable and less polished. Jupyter Scala always prints every variable value after I execute a cell; I don't want to see this 99% of the time.
Spark Kernel is my favourite. Both for Spark and plain old Scala.
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Spark Kernel has been accepted into Apache Incubator and has moved all development to Apache Toree.
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