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* Copy eng\common from Arcade repo. * Enable Spark to build using dotnet/arcade * Update coverlet version to work around bug in older version. * Fix up test directory lookup for new artifacts location. * Don't use dummy versions for local dev builds. * Fix up official build for new output artifacts location * Rearrange official build - Set official build id parameter - Build nuget package on Build leg - Publish the worker using MSBuild instead of cmd * Ensure only our .nupkg gets signed and copied, and the .nupkg is placed directly in the Packages folder. Clean up official build definition. |
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README.md
.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.
Table of Contents
- Get Started
- Build Status
- Building from Source
- Samples
- Contributing
- Inspiration and Special Thanks
- How to Engage, Contribute and Provide Feedback
- .NET Foundation
- Code of Conduct
- License
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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| Ubuntu | Windows |
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!
| Instructions | ||
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Windows |
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Ubuntu |
Samples
There are two types of samples/apps in the .NET for Apache Spark repo:
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Getting Started - .NET for Apache Spark code focused on simple and minimalistic scenarios. -
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 |
Description |
Scenarios |
Dataframes and SparkSQL |
Simple code snippets to help you get familiarized with the programmability experience of .NET for Apache Spark. |
Basic
C# F#
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Structured Streaming |
Code 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#
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TPC-H Queries |
Code to show you how to author complex queries using .NET for Apache Spark. |
TPC-H Functional
C#
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Contributing
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 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.
License
.NET for Apache Spark is licensed under the MIT license.