[GitHub] [spark] maropu commented on a change in pull request #30372: [SPARK-33172][SQL] Adding support for UserDefinedType for Spark SQL Code generator

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maropu commented on a change in pull request #30372:
URL: https://github.com/apache/spark/pull/30372#discussion_r524941488



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
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@@ -1734,15 +1734,17 @@ object CodeGenerator extends Logging {
    * Returns the specialized code to access a value from a column vector for a given `DataType`.
    */
   def getValueFromVector(vector: String, dataType: DataType, rowId: String): String = {
-    if (dataType.isInstanceOf[StructType]) {
-      // `ColumnVector.getStruct` is different from `InternalRow.getStruct`, it only takes an
-      // `ordinal` parameter.
-      s"$vector.getStruct($rowId)"
-    } else {
-      getValue(vector, dataType, rowId)
+    dataType match {
+      case udt: UserDefinedType[_] => getValueFromVector(vector, udt.sqlType, rowId)

Review comment:
       Does this issue only happens when using `spark-bigquery-with-dependencies`? In the current spark codebase, it seems dataType cannot be an user-defined type in this method.




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