Exploding nested Struct in Spark dataframe

Question

I'm working through the an example. The schema for the dataframe looks like:

> parquetDF.printSchema
root
|-- department: struct (nullable = true)
|    |-- id: string (nullable = true)
|    |-- name: string (nullable = true)
|-- employees: array (nullable = true)
|    |-- element: struct (containsNull = true)
|    |    |-- firstName: string (nullable = true)
|    |    |-- lastName: string (nullable = true)
|    |    |-- email: string (nullable = true)
|    |    |-- salary: integer (nullable = true)

In the example, they show how to explode the employees column into 4 additional columns:

val explodeDF = parquetDF.explode($"employees") {
case Row(employee: Seq[Row]) => employee.map{ employee =>
  val firstName = employee(0).asInstanceOf[String]
  val lastName = employee(1).asInstanceOf[String]
  val email = employee(2).asInstanceOf[String]
  val salary = employee(3).asInstanceOf[Int]
  Employee(firstName, lastName, email, salary)
 }
}.cache()
display(explodeDF)

How would I do something similar with the department column (i.e. add two additional columns to the dataframe called "id" and "name")? The methods aren't exactly the same, and I can only figure out how to create a brand new data frame using:

val explodeDF = parquetDF.select("department.id","department.name")
display(explodeDF)

If I try:

val explodeDF = parquetDF.explode($"department") {
  case Row(dept: Seq[String]) => dept.map{dept =>
  val id = dept(0)
  val name = dept(1)
  }
}.cache()
display(explodeDF)

I get the warning and error:

<console>:38: warning: non-variable type argument String in type pattern Seq[String] is unchecked since it is eliminated by erasure
            case Row(dept: Seq[String]) => dept.map{dept =>
                           ^
<console>:37: error: inferred type arguments [Unit] do not conform to    method explode's type parameter bounds [A <: Product]
  val explodeDF = parquetDF.explode($"department") ............
                                   ^

Answer 1

You could use something like that:

var explodeDF = explodeDF.withColumn("id",                                  explodeDF("department.id"))

explodeDeptDF = explodeDeptDF.withColumn("name",                            explodeDeptDF("department.name"))