如何在spark dataframe中从多层结构类型创建列？

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

val data = Seq(
  Row(1, Row("Alice", 25, Seq("Java", "Scala"))),
  Row(2, Row("Bob", 30, Seq("Python", "R")))
)

val schema = StructType(Seq(
  StructField("id", IntegerType),
  StructField("info", StructType(Seq(
    StructField("name", StringType),
    StructField("age", IntegerType),
    StructField("languages", ArrayType(StringType))
  )))
))

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

+---+-------------------+
| id|               info|
+---+-------------------+
|  1| [Alice, 25, [Java]]|
|  2|    [Bob, 30, [Python, R]]|
+---+-------------------+

val dfWithColumn = df.withColumn("name", col("info.name"))
  .withColumn("age", col("info.age"))
  .withColumn("languages", col("info.languages"))

dfWithColumn.show()

+---+-------------------+-----+---+---------+
| id|               info| name|age|languages|
+---+-------------------+-----+---+---------+
|  1| [Alice, 25, [Java]]|Alice| 25| [Java]|
|  2|    [Bob, 30, [Python, R]]|  Bob| 30| [Python, R]|
+---+-------------------+-----+---+---------+