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+Taking your .NET for Apache Spark Application to Production
+===
+
+# Table of Contents
+This how-to provides general instructions on how to take your .NET for Apache Spark application to production.
+In this documentation, we will summarize the most commonly asked scenarios when running a .NET for Apache Spark Application.
+You will also learn how to package your application and submit your application with [spark-submit](https://spark.apache.org/docs/latest/submitting-applications.html) and [Apachy Livy](https://livy.incubator.apache.org/).
+- [How to deploy your application when you have a single dependency](#how-to-deploy-your-application-when-you-have-a-single-dependency)
+  - [Scenarios](#scenarios)
+  - [Package your application](#package-your-application)
+  - [Launch your application](#launch-your-application)
+- [How to deploy your application when you have multiple dependencies](#how-to-deploy-your-application-when-you-have-multiple-dependencies)
+  - [Scenarios](#scenarios-1)
+  - [Package your application](#package-your-application-1)
+  - [Launch your application](#launch-your-application-1)
+
+## How to deploy your application when you have a single dependency
+### Scenarios
+#### 1. SparkSession code and business logic in the same Program.cs file
+The `SparkSession` code and business logic (UDFs) are contained in the same `Program.cs` file.
+#### 2. SparkSession code and business logic in the same project, but different .cs files
+The `SparkSession` code and business logic (UDFs) are in different `.cs` files and both contained in the same project (e.g. SparkSession in Program.cs, business logic in BusinessLogic.cs and both are in mySparkApp.csproj).
+
+### Package your application
+Please follow [Get Started](https://github.com/dotnet/spark/#get-started) to build your application.
+
+### Launch your application
+#### 1. Using spark-submit
+Please make sure you have [pre-requisites](https://github.com/dotnet/spark/blob/master/docs/getting-started/windows-instructions.md#pre-requisites) to run the following command.
+```powershell
+%SPARK_HOME%\bin\spark-submit \
+--class org.apache.spark.deploy.dotnet.DotnetRunner \
+--master yarn \
+--deploy-mode cluster \
+--files <some dir>\<dotnet version>\mySparkApp.dll \
+<some dir>\<dotnet version>\microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar \
+dotnet <some dir>\<dotnet version>\mySparkApp.dll <app arg 1> <app arg 2> ... <app arg n>
+or
+
+```
+#### 2. Using Apache Livy
+```shell
+{
+    "file": "adl://<cluster name>.azuredatalakestore.net/<some dir>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar",
+    "className": "org.apache.spark.deploy.dotnet.DotnetRunner",
+    "files": [“adl://<cluster name>.azuredatalakestore.net/<some dir>/mySparkApp.dll" ],
+    "args": ["dotnet","adl://<cluster name>.azuredatalakestore.net/<some dir>/mySparkApp.dll","<app arg 1>","<app arg 2>,"...","<app arg n>"]
+}
+```
+
+## How to deploy your application when you have multiple dependencies
+### Scenarios
+#### 1. SparkSession code in one project that references another project including the business logic
+The `SparkSession` code in one project (e.g. mySparkApp.csproj) and business logic (UDFs) in another project (e.g. businessLogic.csproj).
+#### 2. SparkSession code references a function from a Nuget package that has been installed in the csproj
+The `SparkSession` code references a function from a Nuget package.
+#### 3. SparkSession code references a function from a DLL on the user's machine
+The `SparkSession` code reference business logic (UDFs) on the user's machine (e.g. `SparkSession` code in the mySparkApp.csproj and businessLogic.dll on a different machine).
+#### 4. SparkSession code references functions and business logic from multiple projects/solutions that themselves depend on multiple Nuget packages
+This would be a more complex use case when you have `SparkSession` code reference business logic (UDFs) and functions from Nuget packages in multiple projects and/or solutions.
+
+### Package your application
+Please see detailed steps [here](https://github.com/dotnet/spark/tree/master/deployment#preparing-your-spark-net-app) on how to build, publish and zip your application. After packaging your .NET for Apache Spark application, you will have a zip file (e.g. mySparkApp.zip) which has all the dependencies.
+
+### Launch your application
+#### 1. Using spark-submit
+```shell
+spark-submit \
+--class org.apache.spark.deploy.dotnet.DotnetRunner \
+--master yarn \
+--deploy-mode cluster \
+--conf spark.yarn.appMasterEnv.DOTNET_ASSEMBLY_SEARCH_PATHS=./udfs \
+--conf spark.yarn.appMasterEnv.DOTNET_ASSEMBLY_SEARCH_PATHS=./myLibraries.zip \
+--archives hdfs://<path to your files>/businessLogics.zip#udfs,hdfs://<path to your files>/myLibraries.zip \
+hdfs://<path to jar file>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar \
+hdfs://<path to your files>/mySparkApp.zip mySparkApp <app arg 1> <app arg 2> ... <app arg n>
+```
+#### 2. Using Apache Livy
+```shell
+{
+    "file": "adl://<cluster name>.azuredatalakestore.net/<some dir>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar",
+    "className": "org.apache.spark.deploy.dotnet.DotnetRunner",
+    "conf": {"spark.yarn.appMasterEnv.DOTNET_ASSEMBLY_SEARCH_PATHS": "./udfs, ./myLibraries.zip"},
+    "archives": ["adl://<cluster name>.azuredatalakestore.net/<some dir>/businessLogics.zip#udfs”, "adl://<cluster name>.azuredatalakestore.net/<some dir>/myLibraries.zip”],
+    "args": ["adl://<cluster name>.azuredatalakestore.net/<some dir>/mySparkApp.zip","mySparkApp","<app arg 1>","<app arg 2>,"...","<app arg n>"]
+}
+```