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 bbf0ac1dd8..308bb96502 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
@@ -395,10 +395,13 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
 
   private def fillMap(values: Seq[(String, Any)]): DataFrame = {
     // Error handling
-    values.foreach { case (colName, replaceValue) =>
+    val attrToValue = AttributeMap(values.map { case (colName, replaceValue) =>
       // Check column name exists
-      df.resolve(colName)
-
+      val attr = df.resolve(colName) match {
+        case a: Attribute => a
+        case _ => throw new UnsupportedOperationException(
+          s"Nested field ${colName} is not supported.")
+      }
       // Check data type
       replaceValue match {
         case _: jl.Double | _: jl.Float | _: jl.Integer | _: jl.Long | _: jl.Boolean | _: String =>
@@ -406,31 +409,29 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
         case _ => throw new IllegalArgumentException(
           s"Unsupported value type ${replaceValue.getClass.getName} ($replaceValue).")
       }
-    }
+      attr -> replaceValue
+    })
 
-    val columnEquals = df.sparkSession.sessionState.analyzer.resolver
-    val projections = df.schema.fields.map { f =>
-      values.find { case (k, _) => columnEquals(k, f.name) }.map { case (_, v) =>
-        v match {
-          case v: jl.Float => fillCol[Float](f, v)
-          case v: jl.Double => fillCol[Double](f, v)
-          case v: jl.Long => fillCol[Long](f, v)
-          case v: jl.Integer => fillCol[Integer](f, v)
-          case v: jl.Boolean => fillCol[Boolean](f, v.booleanValue())
-          case v: String => fillCol[String](f, v)
-        }
-      }.getOrElse(df.col(f.name))
+    val output = df.queryExecution.analyzed.output
+    val projections = output.map {
+      attr => attrToValue.get(attr).map {
+        case v: jl.Float => fillCol[Float](attr, v)
+        case v: jl.Double => fillCol[Double](attr, v)
+        case v: jl.Long => fillCol[Long](attr, v)
+        case v: jl.Integer => fillCol[Integer](attr, v)
+        case v: jl.Boolean => fillCol[Boolean](attr, v.booleanValue())
+        case v: String => fillCol[String](attr, v)
+      }.getOrElse(Column(attr))
     }
     df.select(projections : _*)
   }
 
   /**
-   * Returns a [[Column]] expression that replaces null value in `col` with `replacement`.
-   * It selects a column based on its name.
+   * Returns a [[Column]] expression that replaces null value in column defined by `attr`
+   * with `replacement`.
    */
-  private def fillCol[T](col: StructField, replacement: T): Column = {
-    val quotedColName = "`" + col.name + "`"
-    fillCol(col.dataType, col.name, df.col(quotedColName), replacement)
+  private def fillCol[T](attr: Attribute, replacement: T): Column = {
+    fillCol(attr.dataType, attr.name, Column(attr), replacement)
   }
 
   /**
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 091877f7ca..23c2349f89 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
@@ -460,4 +460,29 @@ class DataFrameNaFunctionsSuite extends QueryTest with SharedSparkSession {
       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-34417 - test fillMap() for column with a dot in the name") {
+    val na = "n/a"
+    checkAnswer(
+      Seq(("abc", 23L), ("def", 44L), (null, 0L)).toDF("ColWith.Dot", "Col")
+        .na.fill(Map("`ColWith.Dot`" -> na)),
+      Row("abc", 23) :: Row("def", 44L) :: Row(na, 0L) :: Nil)
+  }
+
+  test("SPARK-34417 - test fillMap() for qualified-column with a dot in the name") {
+    val na = "n/a"
+    checkAnswer(
+      Seq(("abc", 23L), ("def", 44L), (null, 0L)).toDF("ColWith.Dot", "Col").as("testDF")
+        .na.fill(Map("testDF.`ColWith.Dot`" -> na)),
+      Row("abc", 23) :: Row("def", 44L) :: Row(na, 0L) :: Nil)
+  }
+
+  test("SPARK-34417 - test fillMap() for column without a dot in the name" +
+    " and dataframe with another column having a dot in the name") {
+    val na = "n/a"
+    checkAnswer(
+      Seq(("abc", 23L), ("def", 44L), (null, 0L)).toDF("Col", "ColWith.Dot")
+        .na.fill(Map("Col" -> na)),
+      Row("abc", 23) :: Row("def", 44L) :: Row(na, 0L) :: Nil)
+  }
 }