How can I create a Spark DataFrame from a nested array of struct element?

Question

I have read a JSON file into Spark. This file has the following structure:

scala> tweetBlob.printSchema
root
 |-- related: struct (nullable = true)
 |             


        

Answer 1

One possible way to handle this is to extract required information from the schema. Lets start with some dummy data:

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


case class Bar(x: Int, y: String)
case class Foo(bar: Bar)

val df = sc.parallelize(Seq(Foo(Bar(1, "first")), Foo(Bar(2, "second")))).toDF

df.printSchema

// root
//  |-- bar: struct (nullable = true)
//  |    |-- x: integer (nullable = false)
//  |    |-- y: string (nullable = true)

and a helper function:

def children(colname: String, df: DataFrame) = {
  val parent = df.schema.fields.filter(_.name == colname).head
  val fields = parent.dataType match {
    case x: StructType => x.fields
    case _ => Array.empty[StructField]
  }
  fields.map(x => col(s"$colname.${x.name}"))
}

Finally the results:

df.select(children("bar", df): _*).printSchema

// root
// |-- x: integer (nullable = true)
// |-- y: string (nullable = true)