Get elements of type structure of row by name in SPARK SCALA

Question

In a DataFrame object in Apache Spark (I'm using the Scala interface), if I'm iterating over its Row objects, is there any way to extract structure values by name?

I am using the below code to extract by name but I am facing problem on how to read the struct value .

If values had been of type string then we could have done this:

 val resultDF=joinedDF.rdd.map{row=> 
      val id=row.getAs[Long]("id")
      val values=row.getAs[String]("slotSize")
      val feilds=row.getAs[String](values)
      (id,values,feilds)
      }.toDF("id","values","feilds")

But in my case values has the below schema

v1: struct (nullable = true)
     |    |-- level1: string (nullable = true)
     |    |-- level2: string (nullable = true)
     |    |-- level3: string (nullable = true)
     |    |-- level4: string (nullable = true)
     |    |-- level5: string (nullable = true)

What shall I replace this line with to make the code work given that value has the above structure.

  row.getAs[String](values)

Answer 1

You can access the struct elements my first extracting another Row (structs are modeled as another Row in spark) from the toplevel Row like this:

Scala Implementation

val level1 = row.getAs[Row]("struct").getAs[String]("level1")

Java Implementation

 String level1 = f.<Row>getAs("struct).getAs("level1").toString();