Update .NET 6 to .NET 8, .NET Framework 4.6.1 -> .NET Framework 4.8, dependencies.

Author: grazy27

.gitignore

@@ -372,4 +372,8 @@ hs_err_pid*
 .ionide/
 
 # Mac dev
-.DS_Store
+.DS_Store
+
+# Scala intermideate build files
+**/.bloop/
+**/.metals/

README.md

@@ -8,7 +8,7 @@
 
 .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 6, or Windows using .NET Framework. It also runs on all major cloud providers including [Azure HDInsight Spark](deployment/README.md#azure-hdinsight-spark), [Amazon EMR Spark](deployment/README.md#amazon-emr-spark), [AWS](deployment/README.md#databricks) & [Azure](deployment/README.md#databricks) Databricks.
+.NET for Apache Spark runs on Windows, Linux, and macOS using .NET 8, or Windows using .NET Framework. It also runs on all major cloud providers including [Azure HDInsight Spark](deployment/README.md#azure-hdinsight-spark), [Amazon EMR Spark](deployment/README.md#amazon-emr-spark), [AWS](deployment/README.md#databricks) & [Azure](deployment/README.md#databricks) Databricks.
 
 **Note**: We currently have a Spark Project Improvement Proposal JIRA at [SPIP: .NET bindings for Apache Spark](https://issues.apache.org/jira/browse/SPARK-27006) to work with the community towards getting .NET support by default into Apache Spark. We highly encourage you to participate in the discussion. 
 
@@ -40,7 +40,7 @@
     <tbody align="center">
         <tr>
             <td>2.4*</td>
-            <td rowspan=4><a href="/dotnet/spark/releases/tag/v2.1.1">v2.1.1</a></td>
+            <td rowspan=5><a href="/dotnet/spark/releases/tag/v2.1.1">v2.1.1</a></td>
         </tr>
         <tr>
             <td>3.0</td>
@@ -50,6 +50,9 @@
         </tr>
         <tr>
             <td>3.2</td>
+        </tr>        
+        <tr>
+            <td>3.5</td>
         </tr>
     </tbody>
 </table>
@@ -61,7 +64,7 @@
 .NET for Apache Spark releases are available [here](https://github.com/dotnet/spark/releases) and NuGet packages are available [here](https://www.nuget.org/packages/Microsoft.Spark).
 
 ## Get Started
-These instructions will show you how to run a .NET for Apache Spark app using .NET 6.
+These instructions will show you how to run a .NET for Apache Spark app using .NET 8.
 - [Windows Instructions](docs/getting-started/windows-instructions.md)
 - [Ubuntu Instructions](docs/getting-started/ubuntu-instructions.md)
 - [MacOs Instructions](docs/getting-started/macos-instructions.md)

azure-pipelines-e2e-tests-template.yml

@@ -58,10 +58,10 @@ stages:
               mvn -version
 
         - task: UseDotNet@2
-          displayName: 'Use .NET 6 sdk'
+          displayName: 'Use .NET 8 sdk'
           inputs:
             packageType: sdk
-            version: 6.x
+            version: 8.x
             installationPath: $(Agent.ToolsDirectory)/dotnet
 
         - task: DownloadBuildArtifacts@0
@@ -71,7 +71,7 @@ stages:
             downloadPath: $(Build.ArtifactStagingDirectory)
 
         - pwsh: |
-            $framework = "net6.0"
+            $framework = "net8.0"
 
             if ($env:AGENT_OS -eq 'Windows_NT') {
               $runtimeIdentifier = "win-x64"

benchmark/README.md

@@ -60,7 +60,7 @@ TPCH timing results is written to stdout in the following form: `TPCH_Result,<la
     <true for sql tests, false for functional tests>
     ```
 
-    **Note**: Ensure that you build the worker and application with .NET 6 in order to run hardware acceleration queries.
+    **Note**: Ensure that you build the worker and application with .NET 8 in order to run hardware acceleration queries.
 
 ## Python
 1. Upload [run_python_benchmark.sh](run_python_benchmark.sh) and all [python tpch benchmark](python/) files to the cluster.

benchmark/csharp/Tpch/Tpch.csproj

@@ -2,8 +2,8 @@
 
   <PropertyGroup>
     <OutputType>Exe</OutputType>
-    <TargetFrameworks>net461;net6.0</TargetFrameworks>
-    <TargetFrameworks Condition="'$(OS)' != 'Windows_NT'">net6.0</TargetFrameworks>
+    <TargetFrameworks>net48;net8.0</TargetFrameworks>
+    <TargetFrameworks Condition="'$(OS)' != 'Windows_NT'">net8.0</TargetFrameworks>
     <RootNamespace>Tpch</RootNamespace>
     <AssemblyName>Tpch</AssemblyName>
   </PropertyGroup>
@@ -16,7 +16,7 @@
   </ItemGroup>
 
   <Choose>
-    <When Condition="'$(TargetFramework)' == 'net6.0'">
+    <When Condition="'$(TargetFramework)' == 'net8.0'">
       <PropertyGroup>
         <AllowUnsafeBlocks>true</AllowUnsafeBlocks>
       </PropertyGroup>

deployment/README.md

@@ -63,7 +63,7 @@ Microsoft.Spark.Worker is a backend component that lives on the individual worke
 ## Azure HDInsight Spark
 [Azure HDInsight Spark](https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-overview) is the Microsoft implementation of Apache Spark in the cloud that allows users to launch and configure Spark clusters in Azure. You can use HDInsight Spark clusters to process your data stored in Azure (e.g., [Azure Storage](https://azure.microsoft.com/en-us/services/storage/) and [Azure Data Lake Storage](https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction)).
 
-> **Note:** Azure HDInsight Spark is Linux-based. Therefore, if you are interested in deploying your app to Azure HDInsight Spark, make sure your app is .NET Standard compatible and that you use [.NET 6 compiler](https://dotnet.microsoft.com/download) to compile your app.
+> **Note:** Azure HDInsight Spark is Linux-based. Therefore, if you are interested in deploying your app to Azure HDInsight Spark, make sure your app is .NET Standard compatible and that you use [.NET 8 compiler](https://dotnet.microsoft.com/download) to compile your app.
 
 ### Deploy Microsoft.Spark.Worker
 *Note that this step is required only once*
@@ -115,7 +115,7 @@ EOF
 ## Amazon EMR Spark
 [Amazon EMR](https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-what-is-emr.html) is a managed cluster platform that simplifies running big data frameworks on AWS.
 
-> **Note:** AWS EMR Spark is Linux-based. Therefore, if you are interested in deploying your app to AWS EMR Spark, make sure your app is .NET Standard compatible and that you use [.NET 6 compiler](https://dotnet.microsoft.com/download) to compile your app.
+> **Note:** AWS EMR Spark is Linux-based. Therefore, if you are interested in deploying your app to AWS EMR Spark, make sure your app is .NET Standard compatible and that you use [.NET 8 compiler](https://dotnet.microsoft.com/download) to compile your app.
 
 ### Deploy Microsoft.Spark.Worker
 *Note that this step is only required at cluster creation*
@@ -160,7 +160,7 @@ foo@bar:~$ aws emr add-steps \
 ## Databricks
 [Databricks](http://databricks.com) is a platform that provides cloud-based big data processing using Apache Spark.
 
-> **Note:** [Azure](https://azure.microsoft.com/en-us/services/databricks/) and [AWS](https://databricks.com/aws) Databricks is Linux-based. Therefore, if you are interested in deploying your app to Databricks, make sure your app is .NET Standard compatible and that you use [.NET 6 compiler](https://dotnet.microsoft.com/download) to compile your app.
+> **Note:** [Azure](https://azure.microsoft.com/en-us/services/databricks/) and [AWS](https://databricks.com/aws) Databricks is Linux-based. Therefore, if you are interested in deploying your app to Databricks, make sure your app is .NET Standard compatible and that you use [.NET 8 compiler](https://dotnet.microsoft.com/download) to compile your app.
 
 Databricks allows you to submit Spark .NET apps to an existing active cluster or create a new cluster everytime you launch a job. This requires the **Microsoft.Spark.Worker** to be installed **first** before you submit a Spark .NET app.
 

docs/building/ubuntu-instructions.md

@@ -6,7 +6,7 @@ Building Spark .NET on Ubuntu 18.04
 - [Pre-requisites](#pre-requisites)
 - [Building](#building)
   - [Building Spark .NET Scala Extensions Layer](#building-spark-net-scala-extensions-layer)
-  - [Building .NET Sample Applications using .NET Core CLI](#building-net-sample-applications-using-net-core-cli)
+  - [Building .NET Sample Applications using .NET 8 CLI](#building-net-sample-applications-using-net-8-cli)
 - [Run Samples](#run-samples)
 
 # Open Issues:
@@ -16,7 +16,7 @@ Building Spark .NET on Ubuntu 18.04
 
 If you already have all the pre-requisites, skip to the [build](ubuntu-instructions.md#building) steps below.
 
-  1. Download and install **[.NET 6 SDK](https://dotnet.microsoft.com/en-us/download/dotnet/6.0)** - installing the SDK will add the `dotnet` toolchain to your path.
+  1. Download and install **[.NET 8 SDK](https://dotnet.microsoft.com/en-us/download/dotnet/6.0)** - installing the SDK will add the `dotnet` toolchain to your path.
   2. Install **[OpenJDK 8](https://openjdk.java.net/install/)** 
      - You can use the following command:
        ```bash
@@ -110,65 +110,66 @@ Let us now build the Spark .NET Scala extension layer. This is easy to do:
 
 ```
 cd src/scala
-mvn clean package 
+mvn clean package
 ```
 You should see JARs created for the supported Spark versions:
 * `microsoft-spark-2-3/target/microsoft-spark-2-3_2.11-<version>.jar`
 * `microsoft-spark-2-4/target/microsoft-spark-2-4_2.11-<version>.jar`
 * `microsoft-spark-3-0/target/microsoft-spark-3-0_2.12-<version>.jar`
+* `microsoft-spark-3-0/target/microsoft-spark-3-5_2.12-<version>.jar`
 
-## Building .NET Sample Applications using .NET 6 CLI
+## Building .NET Sample Applications using .NET 8 CLI
 
   1. Build the Worker
       ```bash
       cd ~/dotnet.spark/src/csharp/Microsoft.Spark.Worker/
-      dotnet publish -f net6.0 -r linux-x64
+      dotnet publish -f net8.0 -r linux-x64
       ```
       <details>
       <summary>&#x1F4D9; Click to see sample console output</summary>
 
       ```bash
-      user@machine:/home/user/dotnet.spark/src/csharp/Microsoft.Spark.Worker$ dotnet publish -f net6.0 -r linux-x64
+      user@machine:/home/user/dotnet.spark/src/csharp/Microsoft.Spark.Worker$ dotnet publish -f net8.0 -r linux-x64
       Microsoft (R) Build Engine version 16.0.462+g62fb89029d for .NET Core
       Copyright (C) Microsoft Corporation. All rights reserved.
       
         Restore completed in 36.03 ms for /home/user/dotnet.spark/src/csharp/Microsoft.Spark.Worker/Microsoft.Spark.Worker.csproj.
         Restore completed in 35.94 ms for /home/user/dotnet.spark/src/csharp/Microsoft.Spark/Microsoft.Spark.csproj.
         Microsoft.Spark -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark/Debug/netstandard2.0/Microsoft.Spark.dll
-        Microsoft.Spark.Worker -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.Worker/Debug/net6.0/linux-x64/Microsoft.Spark.Worker.dll
-        Microsoft.Spark.Worker -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.Worker/Debug/net6.0/linux-x64/publish/
+        Microsoft.Spark.Worker -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.Worker/Debug/net8.0/linux-x64/Microsoft.Spark.Worker.dll
+        Microsoft.Spark.Worker -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.Worker/Debug/net8.0/linux-x64/publish/
       ```
 
       </details>
 
   2. Build the Samples
       ```bash
       cd ~/dotnet.spark/examples/Microsoft.Spark.CSharp.Examples/
-      dotnet publish -f net6.0 -r linux-x64
+      dotnet publish -f net8.0 -r linux-x64
       ```
       <details>
       <summary>&#x1F4D9; Click to see sample console output</summary>
 
       ```bash
-      user@machine:/home/user/dotnet.spark/examples/Microsoft.Spark.CSharp.Examples$ dotnet publish -f net6.0 -r linux-x64
+      user@machine:/home/user/dotnet.spark/examples/Microsoft.Spark.CSharp.Examples$ dotnet publish -f net8.0 -r linux-x64
       Microsoft (R) Build Engine version 16.0.462+g62fb89029d for .NET Core
       Copyright (C) Microsoft Corporation. All rights reserved.
 
         Restore completed in 37.11 ms for /home/user/dotnet.spark/src/csharp/Microsoft.Spark/Microsoft.Spark.csproj.
         Restore completed in 281.63 ms for /home/user/dotnet.spark/examples/Microsoft.Spark.CSharp.Examples/Microsoft.Spark.CSharp.Examples.csproj.
         Microsoft.Spark -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark/Debug/netstandard2.0/Microsoft.Spark.dll
-        Microsoft.Spark.CSharp.Examples -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.CSharp.Examples/Debug/net6.0/linux-x64/Microsoft.Spark.CSharp.Examples.dll
-        Microsoft.Spark.CSharp.Examples -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.CSharp.Examples/Debug/net6.0/linux-x64/publish/
+        Microsoft.Spark.CSharp.Examples -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.CSharp.Examples/Debug/net8.0/linux-x64/Microsoft.Spark.CSharp.Examples.dll
+        Microsoft.Spark.CSharp.Examples -> /home/user/dotnet.spark/artifacts/bin/Microsoft.Spark.CSharp.Examples/Debug/net8.0/linux-x64/publish/
       ```
 
      </details>
 
 # Run Samples
 
-Once you build the samples, you can use `spark-submit` to submit your .NET 6 apps. Make sure you have followed the [pre-requisites](#pre-requisites) section and installed Apache Spark.
+Once you build the samples, you can use `spark-submit` to submit your .NET 8 apps. Make sure you have followed the [pre-requisites](#pre-requisites) section and installed Apache Spark.
 
-  1. Set the `DOTNET_WORKER_DIR` or `PATH` environment variable to include the path where the `Microsoft.Spark.Worker` binary has been generated (e.g., `~/dotnet.spark/artifacts/bin/Microsoft.Spark.Worker/Debug/net6.0/linux-x64/publish`)
-  2. Open a terminal and go to the directory where your app binary has been generated (e.g., `~/dotnet.spark/artifacts/bin/Microsoft.Spark.CSharp.Examples/Debug/net6.0/linux-x64/publish`)
+  1. Set the `DOTNET_WORKER_DIR` or `PATH` environment variable to include the path where the `Microsoft.Spark.Worker` binary has been generated (e.g., `~/dotnet.spark/artifacts/bin/Microsoft.Spark.Worker/Debug/net8.0/linux-x64/publish`)
+  2. Open a terminal and go to the directory where your app binary has been generated (e.g., `~/dotnet.spark/artifacts/bin/Microsoft.Spark.CSharp.Examples/Debug/net8.0/linux-x64/publish`)
   3. Running your app follows the basic structure:
      ```bash
      spark-submit \