diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
index 78df89d491ac..fda8dddcefa4 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
@@ -437,12 +437,20 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
    */
   private def fillCol[T](col: StructField, replacement: T): Column = {
     val quotedColName = "`" + col.name + "`"
-    val colValue = col.dataType match {
+    fillCol(col.dataType, col.name, df.col(quotedColName), replacement)
+  }
+
+  /**
+   * Returns a [[Column]] expression that replaces null value in `expr` with `replacement`.
+   * It uses the given `expr` as a column.
+   */
+  private def fillCol[T](dataType: DataType, name: String, expr: Column, replacement: T): Column = {
+    val colValue = dataType match {
       case DoubleType | FloatType =>
-        nanvl(df.col(quotedColName), lit(null)) // nanvl only supports these types
-      case _ => df.col(quotedColName)
+        nanvl(expr, lit(null)) // nanvl only supports these types
+      case _ => expr
     }
-    coalesce(colValue, lit(replacement).cast(col.dataType)).as(col.name)
+    coalesce(colValue, lit(replacement).cast(dataType)).as(name)
   }
 
   /**
@@ -489,6 +497,7 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
     }
 
     val columnEquals = df.sparkSession.sessionState.analyzer.resolver
+
     val projections = df.schema.fields.map { f =>
       val typeMatches = (targetType, f.dataType) match {
         case (NumericType, dt) => dt.isInstanceOf[NumericType]
@@ -499,7 +508,7 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
       }
       // Only fill if the column is part of the cols list.
       if (typeMatches && cols.exists(col => columnEquals(f.name, col))) {
-        fillCol[T](f, value)
+        fillCol(f.dataType, f.name, Column(f.name), value)
       } else {
         df.col(f.name)
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
index 7cf0d25b07fd..7a8f82936a92 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
@@ -349,4 +349,93 @@ class DataFrameNaFunctionsSuite extends QueryTest with SharedSQLContext {
       Row(0, 0L, 0.toShort, 0.toByte, Float.NaN, Double.NaN) ::
       Row(0, 0L, 0.toShort, 0.toByte, Float.NaN, Double.NaN) :: Nil)
   }
+
+  test("SPARK-28897:coalesce error executing dataframe.na.fill " +
+    "with spark.sql.parser.quotedRegexColumnNames true") {
+    val input = createDF()
+
+    val boolInput = Seq[(String, java.lang.Boolean)](
+      ("Bob", false),
+      ("Alice", null),
+      ("Mallory", true),
+      (null, null)
+    ).toDF("name", "spy")
+
+    withSQLConf(SQLConf.SUPPORT_QUOTED_REGEX_COLUMN_NAME.key -> "true") {
+      val fillNumeric = input.na.fill(50.6)
+      checkAnswer(
+        fillNumeric,
+        Row("Bob", 16, 176.5) ::
+          Row("Alice", 50, 164.3) ::
+          Row("David", 60, 50.6) ::
+          Row("Nina", 25, 50.6) ::
+          Row("Amy", 50, 50.6) ::
+          Row(null, 50, 50.6) :: Nil)
+
+      // Make sure the columns are properly named.
+      assert(fillNumeric.columns.toSeq === input.columns.toSeq)
+
+      // string
+      checkAnswer(
+        input.na.fill("unknown").select("name"),
+        Row("Bob") :: Row("Alice") :: Row("David") ::
+          Row("Nina") :: Row("Amy") :: Row("unknown") :: Nil)
+      assert(input.na.fill("unknown").columns.toSeq === input.columns.toSeq)
+
+      // boolean
+      checkAnswer(
+        boolInput.na.fill(true).select("spy"),
+        Row(false) :: Row(true) :: Row(true) :: Row(true) :: Nil)
+      assert(boolInput.na.fill(true).columns.toSeq === boolInput.columns.toSeq)
+
+      // fill double with subset columns
+      checkAnswer(
+        input.na.fill(50.6, "age" :: Nil).select("name", "age"),
+        Row("Bob", 16) ::
+          Row("Alice", 50) ::
+          Row("David", 60) ::
+          Row("Nina", 25) ::
+          Row("Amy", 50) ::
+          Row(null, 50) :: Nil)
+
+      // fill boolean with subset columns
+      checkAnswer(
+        boolInput.na.fill(true, "spy" :: Nil).select("name", "spy"),
+        Row("Bob", false) ::
+          Row("Alice", true) ::
+          Row("Mallory", true) ::
+          Row(null, true) :: Nil)
+
+      // fill string with subset columns
+      checkAnswer(
+        Seq[(String, String)]((null, null)).toDF("col1", "col2").na.fill("test", "col1" :: Nil),
+        Row("test", null))
+
+      checkAnswer(
+        Seq[(Long, Long)]((1, 2), (-1, -2), (9123146099426677101L, 9123146560113991650L))
+          .toDF("a", "b").na.fill(0),
+        Row(1, 2) :: Row(-1, -2) :: Row(9123146099426677101L, 9123146560113991650L) :: Nil
+      )
+
+      checkAnswer(
+        Seq[(java.lang.Long, java.lang.Double)]((null, 3.14), (9123146099426677101L, null),
+          (9123146560113991650L, 1.6), (null, null)).toDF("a", "b").na.fill(0.2),
+        Row(0, 3.14) :: Row(9123146099426677101L, 0.2) :: Row(9123146560113991650L, 1.6)
+          :: Row(0, 0.2) :: Nil
+      )
+
+      checkAnswer(
+        Seq[(java.lang.Long, java.lang.Float)]((null, 3.14f), (9123146099426677101L, null),
+          (9123146560113991650L, 1.6f), (null, null)).toDF("a", "b").na.fill(0.2),
+        Row(0, 3.14f) :: Row(9123146099426677101L, 0.2f) :: Row(9123146560113991650L, 1.6f)
+          :: Row(0, 0.2f) :: Nil
+      )
+
+      checkAnswer(
+        Seq[(java.lang.Long, java.lang.Double)]((null, 1.23), (3L, null), (4L, 3.45))
+          .toDF("a", "b").na.fill(2.34),
+        Row(2, 1.23) :: Row(3, 2.34) :: Row(4, 3.45) :: Nil
+      )
+    }
+  }
 }