viirya commented on a change in pull request #29587:
URL: https://github.com/apache/spark/pull/29587#discussion_r504796446



##########
File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveUnion.scala
##########
@@ -17,29 +17,190 @@
 
 package org.apache.spark.sql.catalyst.analysis
 
+import scala.collection.mutable
+
 import org.apache.spark.sql.AnalysisException
-import org.apache.spark.sql.catalyst.expressions.{Alias, Literal}
+import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.optimizer.CombineUnions
 import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project, 
Union}
 import org.apache.spark.sql.catalyst.rules.Rule
 import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.types._
 import org.apache.spark.sql.util.SchemaUtils
+import org.apache.spark.unsafe.types.UTF8String
 
 /**
  * Resolves different children of Union to a common set of columns.
  */
 object ResolveUnion extends Rule[LogicalPlan] {
-  private def unionTwoSides(
+  /**
+   * This method sorts recursively columns in a struct expression based on 
column names.
+   */
+  private def sortStructFields(expr: Expression): Expression = {
+    val existingExprs = 
expr.dataType.asInstanceOf[StructType].fieldNames.zipWithIndex.map {
+      case (name, i) =>
+        val fieldExpr = GetStructField(KnownNotNull(expr), i)
+        if (fieldExpr.dataType.isInstanceOf[StructType]) {
+          (name, sortStructFields(fieldExpr))
+        } else {
+          (name, fieldExpr)
+        }
+    }.sortBy(_._1).flatMap(pair => Seq(Literal(pair._1), pair._2))
+
+    val newExpr = CreateNamedStruct(existingExprs)
+    if (expr.nullable) {
+      If(IsNull(expr), Literal(null, newExpr.dataType), newExpr)
+    } else {
+      newExpr
+    }
+  }
+
+  /**
+   * Assumes input expressions are field expression of `CreateNamedStruct`. 
This method
+   * sorts the expressions based on field names.
+   */
+  private def sortFieldExprs(fieldExprs: Seq[Expression]): Seq[Expression] = {
+    fieldExprs.grouped(2).map { e =>
+      Seq(e.head, e.last)
+    }.toSeq.sortBy { pair =>
+      assert(pair.head.isInstanceOf[Literal])
+      pair.head.eval().asInstanceOf[UTF8String].toString
+    }.flatten
+  }
+
+  /**
+   * This helper method sorts fields in a `UpdateFields` expression by field 
name.
+   */
+  private def sortStructFieldsInWithFields(expr: Expression): Expression = 
expr transformUp {
+    case u: UpdateFields if u.resolved =>
+      u.evalExpr match {
+        case i @ If(IsNull(_), _, CreateNamedStruct(fieldExprs)) =>
+          val sorted = sortFieldExprs(fieldExprs)
+          val newStruct = CreateNamedStruct(sorted)
+          i.copy(trueValue = Literal(null, newStruct.dataType), falseValue = 
newStruct)
+        case CreateNamedStruct(fieldExprs) =>
+          val sorted = sortFieldExprs(fieldExprs)
+          val newStruct = CreateNamedStruct(sorted)
+          newStruct
+        case other =>
+          throw new AnalysisException(s"`UpdateFields` has incorrect eval 
expression: $other. " +
+            "Please file a bug report with this error message, stack trace, 
and the query.")
+      }
+  }
+
+  def simplifyWithFields(expr: Expression): Expression = {
+    expr.transformUp {
+      case UpdateFields(UpdateFields(struct, fieldOps1), fieldOps2) =>

Review comment:
       Yea. Without optimizing the expressions, we cannot scale up well for 
deeply nested schema, e.g. the added test `SPARK-32376: Make unionByName 
null-filling behavior work with struct columns - deep expr`. in 
`DataFrameSetOperationsSuite`.




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