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Spark.NET Training

Do you want to learn how to process large streams of data in near real time? Do you want to create machine learning models in the least amount of time and cost? Confused about best practices to perform ETL on your data warehouse? Do you want to leverage Spark features on .NET platform? Cazton can help you and your team create highly performant big data solutions and machine learning models.

Microsoft recently released Spark.NET, which is currently available as a Nuget package that runs not only on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework, but also on major cloud platforms. High- level Spark APIs that cover different features of Spark including Spark SQL, DataFrames, Streaming and MLLib are exposed for .NET developers. Applications written in C# or F# on .NET platform can easily integrate and leverage these features to create revolutionary big data solutions on premise or on cloud.

We are happy to announce that we have been part of the Spark.NET project for a while and Microsoft recently open sourced it. Our CEO of Cazton, Chander Dhall, is an eight-time awarded Microsoft Most Valuable Professional and was fortunate to be a part of the project where he had access to the source code before the release.

Cazton has a team of experts who are highly skilled in Big Data technologies like Hadoop, Kafka, Spark, Spark.NET and many other technologies. We officially offer Spark.NET training services as well. Our Spark.NET trainers have years of real world experience using Spark, .NET, .NET Core and many other Big Data technologies. Our training covers everything you may want to know about Spark and Spark.NET from beginner to advanced level. We start off by understanding the basics of Spark and move towards developing and deploying Spark.NET applications on premise as well as on cloud and also look at the best practices and principles followed for creating Spark.NET solutions.

The following topics will be covered in detail:

  • What is Apache Spark?
  • Spark vs Hadoop
  • Learn Spark programming basics with RDDs
  • Using RDDs: Caching, Persistence, and Output
  • Understanding MapReduce
  • Advanced Spark Programming
  • Quick look at Spark APIs including: SparkSQL, DataFrames, Streaming, MLLib
  • Getting started with Spark.NET
  • Creating a Spark.NET application on .NET Core platform from scratch.
  • Debugging and troubleshooting development issues
  • Deploying Spark.NET application on premise/cloud platform
  • Learning best practices and common principles

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