Passing group of rows to a UDF in .NET

Is it possible to pass a group of rows together, instead of each row individually, to a UDF? Assuming that I am able to, I want to run custom code inside MyFunction which writes to the database after performing some manipulation.

Below is what I have implemented for passing each row individually.

static void Main(string[] args)
{     
    spark.Udf().Register<Row, int>("MyUDF", (text) => MyFunction(text));
    spark.Read()
        .Option("header", true)
        .Schema(schema)
        .Csv(@"C:myfile.csv")
        .CreateOrReplaceTempView("Tweets");

    var sqlDf = spark.Sql("SELECT  MyUDF(Struct(*)) as c12  FROM Tweets");
}

public static int MyFunction(Row text)
{
    //Process data complex logic
}

What I am trying to achieve is that there is already an ETL job written in C# which has loads of transformation logic after which it saves to destination database. It takes a huge collection of object and performs this transformation. How can I parallelize this using spark?