import org.apache.spark.sql.{SparkSession, DataFrame}
import org.apache.spark.sql.functions._

class MyExampleDataPipeline {

  val spark: SparkSession = SparkSession.builder
    .appName("DataFrame Transformation Example")
    .master("local[*]")
    .enableHiveSupport()
    .getOrCreate()

  def main(inputTableName: String, outputTableName: String): Unit = {
    val inputDataFrame: DataFrame = spark.table(inputTableName)

    val transformedDataFrame: DataFrame = inputDataFrame.SOME_TRANSFORMATIONS

    transformedDataFrame.write.mode("overwrite").format("parquet").saveAsTable(outputTableName)
  }
}