使用Spark/Scala，有没有一种方法可以连接复杂的数据结构？

val data = Seq(
  Row("Alice", 25, Row("New York", "USA")),
  Row("Bob", 30, Row("London", "UK"))
)

val schema = StructType(Seq(
  StructField("name", StringType, nullable = false),
  StructField("age", IntegerType, nullable = false),
  StructField("address", StructType(Seq(
    StructField("city", StringType, nullable = false),
    StructField("country", StringType, nullable = false)
  )), nullable = false)
))

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

df.select($"name", $"address.city").show()

val data = Seq(
  Row("Alice", Seq(25, 30)),
  Row("Bob", Seq(30, 35, 40))
)

val schema = StructType(Seq(
  StructField("name", StringType, nullable = false),
  StructField("ages", ArrayType(IntegerType, containsNull = false), nullable = false)
))

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

df.select($"name", $"ages"(0)).show() // 访问第一个元素

import org.apache.spark.sql.functions.explode

df.select($"name", explode($"ages").as("age")).show() // 展开数组

val data = Seq(
  Row("Alice", Map("city" -> "New York", "country" -> "USA")),
  Row("Bob", Map("city" -> "London", "country" -> "UK"))
)

val schema = StructType(Seq(
  StructField("name", StringType, nullable = false),
  StructField("address", MapType(StringType, StringType, valueContainsNull = false), nullable = false)
))

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

df.select($"name", $"address.city").show()