Spark / Scala code no longer working in Spark 3.x-CodePudding

This ran fine under 2.x:

import org.apache.spark.sql.functions._
import org.apache.spark.sql.{Encoder, Encoders}
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions.split
import org.apache.spark.sql.functions.broadcast
import org.apache.spark.sql.functions.{lead, lag}
import spark.implicits._

// Gen example data via DF, can come from files, ordering in those files assumed. I.e. no need to sort.
val df = Seq(
 ("1 February"), ("n"), ("c"), ("b"), 
 ("2 February"), ("hh"), ("www"), ("e"), 
 ("3 February"), ("y"), ("s"), ("j"),
 ("1 March"), ("c"), ("b"), ("x"),
 ("1 March"), ("c"), ("b"), ("x"),
 ("2 March"), ("c"), ("b"), ("x"),
 ("3 March"), ("c"), ("b"), ("x"), ("y"), ("z")
 ).toDF("line")

// Define Case Classes to avoid Row aspects on df --> rdd --> to DF which I always must look up again.
case class X(line: String)
case class Xtra(key: Long, line: String)

// Add the Seq Num using zipWithIndex.
val rdd = df.as[X].rdd.zipWithIndex().map{case (v,k) => (k,v)}
val ds = rdd.toDF("key", "line").as[Xtra]

The last statement returns now under 3.x:

AnalysisException: Cannot up cast line from struct<line:string> to string.
The type path of the target object is:
- field (class: "java.lang.String", name: "line")
- root class: "$linecfabb246f6fc445196875da751b278e883.$read.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.$iw.Xtra"
You can either add an explicit cast to the input data or choose a higher precision type of the field in the target object

I find the message hard to fathom and the reason for the change. I just tested under 2.4.5. and it is fine.

CodePudding user response：

Since line is inferred as a struct, you can change a bit your schemas (case classes):

case class X(line: String)
case class Xtra(key: Long, nested_line: X)

And then get the desired result by using:

val ds = rdd.toDF("key", "nested_line").as[Xtra].select("key", "nested_line.line")