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+# User-Defined Functions - C#
+This documentation contains user-defined function (UDF) examples. It shows how to define UDFs and how to use UDFs with Row objects as examples.
+
+## Pre-requisites:
+When you want to execute a C# UDF, Spark needs to understand how to launch the .NET CLR to execute this UDF. Microsoft.Spark.Worker provides a collection of classes to Spark that enable this functionality. Thus, you need to [install the Microsoft.Spark.Worker](https://docs.microsoft.com/en-us/dotnet/spark/tutorials/get-started#5-install-net-for-apache-spark).  
+
+Additionally, [you may need to configure certain environment variables and parameters](https://docs.microsoft.com/en-us/dotnet/spark/how-to-guides/deploy-worker-udf-binaries) to deploy worker and UDF binaries when submitting your Spark app.
+
+## UDF that takes in Row objects
+
+```csharp
+// Create DataFrame which will also be used in the following examples.
+DataFrame df = spark.Range(0, 5).WithColumn("structId", Struct("id"));
+
+// Define UDF that takes in Row objects
+Func<Column, Column> udf1 = Udf<Row, int>(
+    row => row.GetAs<int>(0) + 100);
+
+// Use UDF with DataFrames
+df.Select(udf(df["structId"])).Show();
+```
+
+## UDF that returns Row objects
+Please note that `GenericRow` objects need to be used here.
+
+```csharp
+// Define UDF that returns Row objects
+var schema = new StructType(new[]
+{
+    new StructField("col1", new IntegerType()),
+    new StructField("col2", new StringType())
+});            
+Func<Column, Column> udf2 = Udf<int>(
+    id => new GenericRow(new object[] { 1, "abc" }), schema);
+
+// Use UDF with DataFrames
+df.Select(udf(df["id"])).Show();
+```
+
+## Chained UDF with Row objects
+
+```csharp
+// Chained UDF using udf1 and udf2 defined above.
+df.Select(udf1(udf2(df["id"]))).Show();
+```