.NET for Apache Spark – interactive notebook Docker image

If you are reading this, you are probably aware of my .NET for Apache Spark Docker images that I’ve made available so far. Just recently I’ve added a development image that allows you to easily build .NET for Apache Spark with VS Code in a browser. Today I want to introduce you to the latest member of the family:

The .NET for Apache Spark interactive notebook Docker image.

Jupyter Notebooks

In case you are not aware of what Jupyter Notebooks are, here’s a quick summary quote from the Jupyter project site.

The Jupyter Notebook

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Build .NET for Apache Spark with VS Code in a browser

Build .NET for Apache Spark with VS Code in a browser

My last article explained how you can use .NET for Apache Spark together with Entity Framework to stream data to an SQL Server. There is one caveat though. You have to build Microsoft.Spark.Worker yourself.
This time I’ll show you how you can actually build .NET for Apache Spark with VS Code in a browser yourself, including building and running the C# examples.

Setting up your own development environment to build and test .NET for Apache Spark can be tricky and time-consuming. However, as a regular reader, you are probably aware that I like to use docker … more

.NET for Apache Spark – Stream to SQL Server

In this article I am going to describe how to use .NET for Apache Spark with EntityFrameworkCore to stream data to a Microsoft SQL Server. If you have tried this before, you probably stumbled upon the following exception: Microsoft.Data.SqlClient is not supported on this platform.

So let’s find out, how that can be fixed.

Preparation

If you want to stream to an SQL Server, you obviously need to have access to an SQL Server instance first.

Using docker, it is very easy to fire up a related container. I’ve just named it sqlserver, as … more

NumSharp Cheat Sheet

NumPy to NumSharp Cheat Sheet

Recently, I published a small example project to utilize the htm.core AI algorithm by consuming its REST API via C#. As the API also transfers serialized multi-dimensional NumPy arrays, I was looking for an easy way to get them back into C# objects. I’ve tried out a couple of approaches and finally decided on using the NumSharp library, as I wanted a solution that works on multiple platforms.

I find DataCamps’ Data Science Cheat Sheets very useful and was hoping to find something similar for NumSharp. Well, I didn’t, but obviously that gave me a … more

htm.core and C#

In case you weren’t aware, htm.core now also provides a REST interface to it’s Network API. With this in place, it is possible to utilize the built-in encoders, Spatial Pooler and Temporal Memory from almost any programming language. In this post I briefly want to touch on how to use htm.core and C# together.

Introduction

Before you can start playing around with the REST interface, you will need to have the example REST server running.

To do that, you can either

  • download the source and build it yourself. Once built, the server executable (rest_server) should
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