Royce  Reinger

Royce Reinger


Spark: .NET for Apache® Spark™


.NET for Apache® Spark™

.NET for Apache Spark provides high performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data.

.NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer.

.NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks.

Note: We currently have a Spark Project Improvement Proposal JIRA at SPIP: .NET bindings for Apache Spark to work with the community towards getting .NET support by default into Apache Spark. We highly encourage you to participate in the discussion.

Get Started

These instructions will show you how to run a .NET for Apache Spark app using .NET Core.

Build Status

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 Build Status

Building from Source

Building from source is very easy and the whole process (from cloning to being able to run your app) should take less than 15 minutes!

Windows iconWindows
Ubuntu iconUbuntu



There are two types of samples/apps in the .NET for Apache Spark repo:

Icon Getting Started - .NET for Apache Spark code focused on simple and minimalistic scenarios.

Icon End-End apps/scenarios - Real world examples of industry standard benchmarks, usecases and business applications implemented using .NET for Apache Spark.

We welcome contributions to both categories!

Analytics Scenario



Dataframes and SparkSQLSimple code snippets to help you get familiarized with the programmability experience of .NET for Apache Spark.Basic     C#     F#   Getting started icon
Structured StreamingCode snippets to show you how to utilize Apache Spark's Structured Streaming (2.3.1, 2.3.2, 2.4.1, Latest)

Word Count     C#    F#    Getting started icon

Windowed Word Count    C#    F#    Getting started icon

Word Count on data from Kafka    C#    F#     Getting started icon

TPC-H Queries

Code to show you how to author complex queries using .NET for Apache Spark.

TPC-H Functional     C#    End-to-end app icon

TPC-H SparkSQL     C#    End-to-end app icon


We welcome contributions! Please review our contribution guide.

Inspiration and Special Thanks

This project would not have been possible without the outstanding work from the following communities:

  • Apache Spark: Unified Analytics Engine for Big Data, the underlying backend execution engine for .NET for Apache Spark
  • Mobius: C# and F# language binding and extensions to Apache Spark, a pre-cursor project to .NET for Apache Spark from the same Microsoft group.
  • PySpark: Python bindings for Apache Spark, one of the implementations .NET for Apache Spark derives inspiration from.
  • sparkR: one of the implementations .NET for Apache Spark derives inspiration from.
  • Apache Arrow: A cross-language development platform for in-memory data. This library provides .NET for Apache Spark with efficient ways to transfer column major data between the JVM and .NET CLR.
  • Pyrolite - Java and .NET interface to Python's pickle and Pyro protocols. This library provides .NET for Apache Spark with efficient ways to transfer row major data between the JVM and .NET CLR.
  • Databricks: Unified analytics platform. Many thanks to all the suggestions from them towards making .NET for Apache Spark run on Azure and AWS Databricks.

How to Engage, Contribute and Provide Feedback

The .NET for Apache Spark team encourages contributions, both issues and PRs. The first step is finding an existing issue you want to contribute to or if you cannot find any, open an issue.


.NET for Apache Spark is an open source project under the .NET Foundation and does not come with Microsoft Support unless otherwise noted by the specific product. For issues with or questions about .NET for Apache Spark, please create an issue. The community is active and is monitoring submissions.

.NET Foundation

The .NET for Apache Spark project is part of the .NET Foundation.

Code of Conduct

This project has adopted the code of conduct defined by the Contributor Covenant to clarify expected behavior in our community. For more information, see the .NET Foundation Code of Conduct.

Supported Apache Spark

Apache Spark.NET for Apache Spark

*2.4.2 is not supported.


.NET for Apache Spark releases are available here and NuGet packages are available here.

Download Details:

Author: Dotnet
Source Code: 
License: MIT license

#machinelearning #microsoft #emr #streaming #spark #csharp 

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Buddha Community

Spark: .NET for Apache® Spark™
Einar  Hintz

Einar Hintz


jQuery Ajax CRUD in ASP.NET Core MVC with Modal Popup

In this article, we’ll discuss how to use jQuery Ajax for ASP.NET Core MVC CRUD Operations using Bootstrap Modal. With jQuery Ajax, we can make HTTP request to controller action methods without reloading the entire page, like a single page application.

To demonstrate CRUD operations – insert, update, delete and retrieve, the project will be dealing with details of a normal bank transaction. GitHub repository for this demo project :

Sub-topics discussed :

  • Form design for insert and update operation.
  • Display forms in modal popup dialog.
  • Form post using jQuery Ajax.
  • Implement MVC CRUD operations with jQuery Ajax.
  • Loading spinner in .NET Core MVC.
  • Prevent direct access to MVC action method.

Create ASP.NET Core MVC Project

In Visual Studio 2019, Go to File > New > Project (Ctrl + Shift + N).

From new project window, Select Asp.Net Core Web Application_._

Image showing how to create ASP.NET Core Web API project in Visual Studio.

Once you provide the project name and location. Select Web Application(Model-View-Controller) and uncheck HTTPS Configuration. Above steps will create a brand new ASP.NET Core MVC project.

Showing project template selection for .NET Core MVC.

Setup a Database

Let’s create a database for this application using Entity Framework Core. For that we’ve to install corresponding NuGet Packages. Right click on project from solution explorer, select Manage NuGet Packages_,_ From browse tab, install following 3 packages.

Showing list of NuGet Packages for Entity Framework Core

Now let’s define DB model class file – /Models/TransactionModel.cs.

public class TransactionModel
    public int TransactionId { get; set; }

    [Column(TypeName ="nvarchar(12)")]
    [DisplayName("Account Number")]
    [Required(ErrorMessage ="This Field is required.")]
    [MaxLength(12,ErrorMessage ="Maximum 12 characters only")]
    public string AccountNumber { get; set; }

    [Column(TypeName ="nvarchar(100)")]
    [DisplayName("Beneficiary Name")]
    [Required(ErrorMessage = "This Field is required.")]
    public string BeneficiaryName { get; set; }

    [Column(TypeName ="nvarchar(100)")]
    [DisplayName("Bank Name")]
    [Required(ErrorMessage = "This Field is required.")]
    public string BankName { get; set; }

    [Column(TypeName ="nvarchar(11)")]
    [DisplayName("SWIFT Code")]
    [Required(ErrorMessage = "This Field is required.")]
    public string SWIFTCode { get; set; }

    [Required(ErrorMessage = "This Field is required.")]
    public int Amount { get; set; }

    [DisplayFormat(DataFormatString = "{0:MM/dd/yyyy}")]
    public DateTime Date { get; set; }


Here we’ve defined model properties for the transaction with proper validation. Now let’s define  DbContextclass for EF Core. core article core #add loading spinner in core core crud without reloading core jquery ajax form core modal dialog core mvc crud using jquery ajax core mvc with jquery and ajax core popup window #bootstrap modal popup in core mvc. bootstrap modal popup in core #delete and viewall in core #jquery ajax - insert #jquery ajax form post #modal popup dialog in core #no direct access action method #update #validation in modal popup

Edureka Fan

Edureka Fan


What is Apache Spark? | Apache Spark Python | Spark Training

This Edureka “What is Apache Spark?” video will help you to understand the Architecture of Spark in depth. It includes an example where we Understand what is Python and Apache Spark.

#big-data #apache-spark #developer #apache #spark

Big Plans for Big Data and .NET for Spark | .NET Blog

The .NET for Apache Spark team is approaching a major milestone as we plan to reach version 1.0 later this year. We want to provide the best possible experience for working with big data from .NET. We’re looking into how you work with big data and .NET for Spark to help us prioritize the right features, scenarios, and solutions for upcoming releases. You can help! core #apache #big data #spark for .net #data science

Gunjan  Khaitan

Gunjan Khaitan


Apache Spark Tutorial For Beginners - Apache Spark Full Course

This full course video on Apache Spark will help you learn the basics of Big Data, what Apache Spark is, and the architecture of Apache Spark. Then, you will understand how to install Apache Spark on Windows and Ubuntu. You will look at the important components of Spark, such as Spark Streaming, Spark MLlib, and Spark SQL. Finally, you will get an idea about implement Spark with Python in PySpark tutorial and look at some of the important Apache Spark interview questions. Now, let’s get started and learn Apache Spark in detail.

Below topics are explained in this Apache Spark Full Course:

  1. Animated Video 01:15
  2. History of Spark 06:48
  3. What is Spark 07:28
  4. Hadoop vs spark 08:32
  5. Components of Apache Spark 14:14
  6. Spark Architecture 33:26
  7. Applications of Spark 40:05
  8. Spark Use Case 42:08
  9. Running a Spark Application 44:08
  10. Apache Spark insallation on Windows 01:01:03
  11. Apache Spark insallation on Ubuntu 01:31:54
  12. What is Spark Streaming 01:49:31
  13. Spark Streaming data sources 01:50:39
  14. Features of Spark Streaming 01:52:19
  15. Working of Spark Streaming 01:52:53
  16. Discretized Streams 01:54:03
  17. caching/persistence 02:02:17
  18. checkpointing in spark streaming 02:04:34
  19. Demo on Spark Streaming 02:18:27
  20. What is Spark MLlib 02:47:29
  21. What is Machine Learning 02:49:14
  22. Machine Learning Algorithms 02:51:38
  23. Spark MLlib Tools 02:53:01
  24. Spark MLlib Data Types 02:56:42
  25. Machine Learning Pipelines 03:09:05
  26. Spark MLlib Demo 03:18:38
  27. What is Spark SQL 04:01:40
  28. Spark SQL Features 04:03:52
  29. Spark SQL Architecture 04:07:43
  30. Spark SQL Data Frame 04:09:59
  31. Spark SQL Data Source 04:11:55
  32. Spark SQL Demo 04:23:00
  33. What is PySpark 04:52:03
  34. PySpark Features 04:58:02
  35. PySpark with Python and Scala 04:58:54
  36. PySpark Contents 05:00:35
  37. PySpark Subpackages 05:40:10
  38. Companies using PySpark 05:41:16
  39. PySpark Demo 05:41:49
  40. Spark Interview Questions 05:50:43

#bigdata #apache #spark #apache-spark

Anil  Sakhiya

Anil Sakhiya


Apache Spark For Beginners In 3 Hours | Apache Spark Training

In this Apache Spark For Beginners, we will have an overview of Spark in Big Data. We will start with an introduction to Apache Spark Programming. Then we will move to know the Spark History. Moreover, we will learn why Spark is needed and covers everything that an individual needed to master its skill in this field. In this Apache Spark tutorial, you will not only learn Spark from the basics but also through this Apache Spark tutorial, you will get to know the Spark architecture and its components such as Spark Core, Spark Programming, Spark SQL, Spark Streaming, and much more.

This “Spark Tutorial” will help you to comprehensively learn all the concepts of Apache Spark. Apache Spark has a bright future. Many companies have recognized the power of Spark and quickly started worked on it. The primary importance of Apache Spark in the Big data industry is because of its in-memory data processing. Spark can also handle many analytics challenges because of its low-latency in-memory data processing capability.

Spark’s shell provides you a simple way to learn the API, as well as a powerful tool to analyze data interactively. It is available in either Scala (which runs on the Java VM and is thus a good way to use existing Java libraries) or Python

This Spark tutorial will comprise of the following topics:

  • 00:00:00 - Introduction
  • 00:00:52 - Spark Fundamentals
  • 00:23:11 - Spark Architecture
  • 01:01:08 - Spark Demo

#apache-spark #apache #spark #big-data #developer