[SPARK-18720][SQL][MINOR] Code Refactoring of withColumn

### What changes were proposed in this pull request?
Our existing withColumn for adding metadata can simply use the existing public withColumn API.

### How was this patch tested?
The existing test cases cover it.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16152 from gatorsmile/withColumnRefactoring.

1 files changed, 1 insertions, 15 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala b/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
index 133f633212..29397b1340 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
@@ -1871,21 +1871,7 @@ class Dataset[T] private[sql](
    * Returns a new Dataset by adding a column with metadata.
    */
   private[spark] def withColumn(colName: String, col: Column, metadata: Metadata): DataFrame = {
-    val resolver = sparkSession.sessionState.analyzer.resolver
-    val output = queryExecution.analyzed.output
-    val shouldReplace = output.exists(f => resolver(f.name, colName))
-    if (shouldReplace) {
-      val columns = output.map { field =>
-        if (resolver(field.name, colName)) {
-          col.as(colName, metadata)
-        } else {
-          Column(field)
-        }
-      }
-      select(columns : _*)
-    } else {
-      select(Column("*"), col.as(colName, metadata))
-    }
+    withColumn(colName, col.as(colName, metadata))
   }
 
   /**