#828 Add support for structs and arrays in EBCDIC writer.

spark-cobol/src/main/scala/za/co/absa/cobrix/spark/cobol/utils/SparkUtils.scala

@@ -19,9 +19,10 @@ package za.co.absa.cobrix.spark.cobol.utils
 import com.fasterxml.jackson.databind.ObjectMapper
 import org.apache.hadoop.fs.{FileSystem, Path}
 import org.apache.spark.SparkContext
+import org.apache.spark.sql.expressions.UserDefinedFunction
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types._
-import org.apache.spark.sql.{Column, DataFrame, SparkSession}
+import org.apache.spark.sql.{Column, DataFrame, Row, SparkSession}
 import za.co.absa.cobrix.cobol.internal.Logging
 import za.co.absa.cobrix.spark.cobol.parameters.MetadataFields.MAX_ELEMENTS
 import za.co.absa.cobrix.spark.cobol.utils.impl.HofsWrapper.transform
@@ -550,5 +551,48 @@ object SparkUtils extends Logging {
     fields.toList
   }
 
+  /**
+    * A UDF that receives the entire record as a [[Row]] and returns a
+    * human-readable string representation of its contents.
+    *
+    * Usage (after columns are combined into a struct):
+    * {{{
+    *   df.withColumn("record_dump", printRowUdf(struct(df.columns.map(col): _*)))
+    * }}}
+    */
+  val printRowUdf: UserDefinedFunction = udf { row: Row =>
+    def rowToString(r: Row): String = {
+      val schema = r.schema
+      val fields = schema.fields.zipWithIndex.map { case (field, idx) =>
+        val value = if (r.isNullAt(idx)) {
+          "null"
+        } else {
+          r.get(idx) match {
+            case nestedRow: Row =>
+              s"{${rowToString(nestedRow)}}"
+            case seq: Seq[_] =>
+              val items = seq.map {
+                case nestedRow: Row => s"{${rowToString(nestedRow)}}"
+                case other          => String.valueOf(other)
+              }
+              s"[${items.mkString(", ")}]"
+            case other =>
+              String.valueOf(other)
+          }
+        }
+        s"${field.name}=$value"
+      }
+      fields.mkString(", ")
+    }
+
+    if (row == null) {
+      null
+    } else {
+      val result = rowToString(row)
+      // Side-effect: print to stdout so the content is visible during tests
+      //println(s"[printRowUdf] $result")
+      result
+    }
+  }
 
 }