如何使用scala在databricks apache中透视列和行？

import org.apache.spark.sql.functions._

// 读取数据
val data = spark.read.format("csv").option("header", "true").load("data.csv")

// 透视列
val pivotColumn = "column_name"
val pivotValues = Seq("value1", "value2", "value3")
val pivotedData = data.groupBy("row_column").pivot(pivotColumn, pivotValues).agg(sum("value"))

// 透视行
val rowColumn = "row_column"
val rowValues = Seq("row_value1", "row_value2", "row_value3")
val rowPivotedData = pivotedData.filter(col(rowColumn).isin(rowValues:_*))

// 显示结果
rowPivotedData.show()