Apache Spark:通过MutableList (Scala)迭代数据帧的行并创建新的数据帧

import org.apache.spark.sql.{Row, SparkSession}
import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}

val spark = SparkSession.builder()
  .appName("SparkExample")
  .master("local")
  .getOrCreate()

val schema = StructType(Seq(
  StructField("name", StringType, nullable = true),
  StructField("age", IntegerType, nullable = true)
))

val data = MutableList(
  Row("Alice", 25),
  Row("Bob", 30),
  Row("Charlie", 35)
)

val df = spark.createDataFrame(spark.sparkContext.parallelize(data), schema)

val newDF = df.map(row => {
  val name = row.getAs[String]("name")
  val age = row.getAs[Int]("age")
  val newAge = age + 1
  Row(name, newAge)
})

val newSchema = StructType(Seq(
  StructField("name", StringType, nullable = true),
  StructField("newAge", IntegerType, nullable = true)
))

val resultDF = spark.createDataFrame(newDF, newSchema)