Spark 2.1 :如何在DataFrameWriter partitionBy中提供多个列

import org.apache.spark.sql.SparkSession

val spark = SparkSession.builder()
  .appName("Spark 2.1 PartitionBy Example")
  .master("local")
  .getOrCreate()

// 创建一个示例DataFrame
val data = Seq(
  ("Alice", "Sales", 5000),
  ("Bob", "IT", 3000),
  ("Charlie", "Marketing", 2000),
  ("David", "Sales", 4000),
  ("Eva", "IT", 6000)
)
val df = spark.createDataFrame(data).toDF("Name", "Department", "Salary")

// 将数据按照Name和Department两列进行分区存储
df.write
  .partitionBy("Name", "Department")
  .csv("path/to/output")

path/to/output/Name=Alice/Department=Sales/part-00000.csv
path/to/output/Name=Bob/Department=IT/part-00000.csv
path/to/output/Name=Charlie/Department=Marketing/part-00000.csv
path/to/output/Name=David/Department=Sales/part-00000.csv
path/to/output/Name=Eva/Department=IT/part-00000.csv