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https://issues.apache.org/jira/browse/SPARK-27006?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Terry Kim updated SPARK-27006:
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Priority: Major (was: Minor)
> SPIP: .NET bindings for Apache Spark
> ------------------------------------
>
> Key: SPARK-27006
> URL: https://issues.apache.org/jira/browse/SPARK-27006
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.0.0
> Reporter: Terry Kim
> Priority: Major
> Original Estimate: 4,032h
> Remaining Estimate: 4,032h
>
> h4. Background and Motivation:
> Apache Spark provides programming language support for Scala/Java (native),
> and extensions for Python and R. While a variety of other language extensions
> are possible to include in Apache Spark, .NET would bring one of the largest
> developer community to the table. Presently, no good Big Data solution exists
> for .NET developers in open source. This SPIP aims at discussing how we can
> bring Apache Spark goodness to the .NET development platform.
> .NET is a free, cross-platform, open source developer platform for building
> many different types of applications. With .NET, you can use multiple
> languages, editors, and libraries to build for web, mobile, desktop, gaming,
> and IoT types of applications. Even with .NET serving millions of developers,
> there is no good Big Data solution that exists today, which this SPIP aims to
> address.
> The .NET developer community is one of the largest programming language
> communities in the world. Its flagship programming language C# is listed as
> one of the most popular programming languages in a variety of articles and
> statistics:
> * Most popular Technologies on Stack Overflow:
> [https://insights.stackoverflow.com/survey/2018/#most-popular-technologies|https://insights.stackoverflow.com/survey/2018/]
>
> * Most popular languages on GitHub 2018:
> [https://www.businessinsider.com/the-10-most-popular-programming-languages-according-to-github-2018-10#2-java-9|https://www.businessinsider.com/the-10-most-popular-programming-languages-according-to-github-2018-10]
>
> * 1M+ new developers last 1 year
> * Second most demanded technology on LinkedIn
> * Top 30 High velocity OSS projects on GitHub
> Including a C# language extension in Apache Spark will enable millions of
> .NET developers to author Big Data applications in their preferred
> programming language, developer environment, and tooling support. We aim to
> promote the .NET bindings for Spark through engagements with the Spark
> community (e.g., we are scheduled to present an early prototype at the SF
> Spark Summit 2019) and the .NET developer community (e.g., similar
> presentations will be held at .NET developer conferences this year). As
> such, we believe that our efforts will help grow the Spark community by
> making it accessible to the millions of .NET developers.
> Furthermore, our early discussions with some large .NET development teams got
> an enthusiastic reception.
> We recognize that earlier attempts at this goal (specifically Mobius
> [https://github.com/Microsoft/Mobius]) were unsuccessful primarily due to the
> lack of communication with the Spark community. Therefore, another goal of
> this proposal is to not only develop .NET bindings for Spark in open source,
> but also continuously seek feedback from the Spark community via posted
> Jira’s (like this one) and the Spark developer mailing list. Our hope is that
> through these engagements, we can build a community of developers that are
> eager to contribute to this effort or want to leverage the resulting .NET
> bindings for Spark in their respective Big Data applications.
> h4. Target Personas:
> .NET developers looking to build big data solutions.
> h4. Goals:
> Our primary goal is to help grow Apache Spark by making it accessible to the
> large .NET developer base and ecosystem. We will also look for opportunities
> to generalize the interop layers for Spark for adding other language
> extensions in the future. [SPARK-26257](
> https://issues.apache.org/jira/browse/SPARK-26257) proposes such a
> generalized interop layer, which we hope to address over the course of this
> project.
> Another important goal for us is to not only enable Spark as an application
> solution for .NET developers, but also opening the door for .NET developers
> to make contributions to Apache Spark itself.
> Lastly, we aim to develop a .NET extension in the open, while continually
> engaging with the Spark community for feedback on designs and code. We will
> welcome PRs from the Spark community throughout this project and aim to grow
> a community of developers that want to contribute to this project.
> h4. Non-Goals:
> This proposal is focused on adding .NET bindings to Apache Spark, and leave
> any performance related tasks for future work. Further, we aim to provide
> support only at the Dataframe level.
> h4. Proposed API Changes:
> This work mostly involves introducing new .NET binding APIs. For example, we
> would introduce .NET UDF related classes such as DotnetUDF,
> UserDefinedDotnetFunction, etc., along with classes responsible for running
> .NET UDFs such as DotnetRunner, DotnetWorkerFactory, etc.
> This work should have minimal impact on existing Spark APIs. However, in
> order to provide a clean solution, we foresee the possibility of introducing
> .NET specific hooks in the Dataset API for collecting data in the driver
> program, for example.
> We also will be introducing Catalyst rules that will plan the physical
> operator (that we will introduce) for the DotnetUDF expression in the logical
> plan.
> On the C# side, similar to existing language extensions, we will introduce
> proxy artifacts that mimic the SparkSession, Dataframe, and other APIs
> related to Spark SQL e.g., column, functions native to Spark SQL, etc.
> We will also look into augmenting the existing spark-submit and spark-shell
> scripts with the ability to recognize a .NET environment.
> h4. Optional Design Sketch:
> Our design will largely follow the design of Python Spark support, including
> how worker orchestration is performed (i.e., two-process solution, IPC
> communication). As such, we will introduce “Runners” specific to executing
> Dotnet driver and UDF workers.
> h4. Optional Rejected Designs:
> The clear alternative is the status quo; developers that want to leverage
> Apache Spark do so through one of the existing supported languages i.e.,
> Scala/Java, Python, or R. This has some costly consequences, such as:
> * Learning a new programming language and development environment.
> * Integrating with existing .NET technologies through complex interop.
> * Migrating legacy code and library dependencies to a supported language.
> Another alternative is that third-party languages should only interact with
> Spark via pure-SQL; possibly via REST. However, this does not enable UDFs or
> UDAFs written in C#; a key desideratum in this effort, which most notably
> takes the form of legacy code/UDFs that would need to be ported to a
> supported language e.g., Scala. This exercise is extremely cumbersome and not
> always feasible due to the code no longer being available i.e., only the
> compiled library exists. As mentioned earlier, the .NET developer community
> is one of the largest in the world, and as such there exist many instances of
> legacy code (e.g., machine learning routines) that would be difficult to port
> without the existing .NET library dependencies.
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