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Category: Spark

Spark + R Webinar

Published 2016-04-20 by Kevin Feasel

David Smith points out a recent webinar on combining Microsoft R Server with HDInsight:

As Mario Inchiosa and Roni Burd demonstrate in this recorded webinar, Microsoft R Server can now run within HDInsight Hadoop nodes running on Microsoft Azure. Better yet, the big-data-capable algorithms of ScaleR (pdf) take advantage of the in-memory architecture of Spark, dramatically reducing the time needed to train models on large data. And if your data grows or you just need more power, you can dynamically add nodes to the HDInsight cluster using the Azure portal.

I don’t normally link to webinars (because they tend to violate my “should be viewable in a coffee break” rule of thumb) but I have a soft spot in my heart for these technologies.  If you want to dig into more “mainstream” (off the Microsoft platform) Spark + R fun, check out SparkR.

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HDInsight + Power BI + Spark

Published 2016-02-02 by Kevin Feasel

Reza Rad has a nice walkthrough on integrating several powerful technologies:

Power BI can connect to many data sources as you know, and Spark on Azure HDInsight is one of them. In area of working with Big Data applications you would probably hear names such as Hadoop, HDInsight, Spark, Storm, Data Lake and many other names. Spark and Hadoop are both frameworks to work with big data, they have some differences though. In this post I’ll show you how you can use Power BI (either Power BI Desktop or Power BI website) to connect to a sample of Spark that we built on an Azure HDInsight service. by completing this section you will be able to create simple spark on Azure HDInsight, and run few Python scripts from Jupyter on it to load a sample table into Spark, and finally use Power BI to connect to Spark server, load, and visualize the data.

If you’re totally unfamiliar with Spark but interested in data processing, now’s a good time to start digging into the topic.

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