diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercion.scala
index 3732b2eb0e..b5c7f27ce1 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercion.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercion.scala
@@ -91,7 +91,8 @@ object AnsiTypeCoercion extends TypeCoercionBase {
       ImplicitTypeCasts ::
       DateTimeOperations ::
       WindowFrameCoercion ::
-      StringLiteralCoercion :: Nil) :: Nil
+      StringLiteralCoercion ::
+      GetDateFieldOperations:: Nil) :: Nil
 
   val findTightestCommonType: (DataType, DataType) => Option[DataType] = {
     case (t1, t2) if t1 == t2 => Some(t1)
@@ -289,4 +290,19 @@ object AnsiTypeCoercion extends TypeCoercionBase {
         p.makeCopy(Array(a, newList))
     }
   }
+
+  /**
+   * When getting a date field from a Timestamp column, cast the column as date type.
+   *
+   * This is Spark's hack to make the implementation simple. In the default type coercion rules,
+   * the implicit cast rule does the work. However, The ANSI implicit cast rule doesn't allow
+   * converting Timestamp type as Date type, so we need to have this additional rule
+   * to make sure the date field extraction from Timestamp columns works.
+   */
+  object GetDateFieldOperations extends TypeCoercionRule {
+    override def transform: PartialFunction[Expression, Expression] = {
+      case g: GetDateField if g.child.dataType == TimestampType =>
+        g.withNewChildren(Seq(Cast(g.child, DateType)))
+    }
+  }
 }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleIdCollection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleIdCollection.scala
index 3fe7be03ec..2a05b8533b 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleIdCollection.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleIdCollection.scala
@@ -159,6 +159,7 @@ object RuleIdCollection {
       // In the production code path, the following rules are run in CombinedTypeCoercionRule, and
       // hence we only need to add them for unit testing.
       "org.apache.spark.sql.catalyst.analysis.AnsiTypeCoercion$PromoteStringLiterals" ::
+      "org.apache.spark.sql.catalyst.analysis.AnsiTypeCoercion$GetDateFieldOperations" ::
       "org.apache.spark.sql.catalyst.analysis.DecimalPrecision" ::
       "org.apache.spark.sql.catalyst.analysis.TypeCoercion$BooleanEquality" ::
       "org.apache.spark.sql.catalyst.analysis.TypeCoercionBase$CaseWhenCoercion" ::
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercionSuite.scala
index 03d885cd43..ab8d9d9806 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercionSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnsiTypeCoercionSuite.scala
@@ -1425,4 +1425,14 @@ class AnsiTypeCoercionSuite extends AnalysisTest {
       In(timestampLiteral, Seq(stringLiteral)),
       In(timestampLiteral, Seq(castStringLiteralAsTimestamp)))
   }
+
+  test("SPARK-35937: GetDateFieldOperations") {
+    val ts = Literal(Timestamp.valueOf("2021-01-01 01:30:00"))
+    Seq(
+      DayOfYear, Year, YearOfWeek, Quarter, Month, DayOfMonth, DayOfWeek, WeekDay, WeekOfYear
+    ).foreach { operation =>
+      ruleTest(
+        AnsiTypeCoercion.GetDateFieldOperations, operation(ts), operation(Cast(ts, DateType)))
+    }
+  }
 }
diff --git a/sql/core/src/test/resources/sql-tests/results/postgreSQL/timestamp.sql.out b/sql/core/src/test/resources/sql-tests/results/postgreSQL/timestamp.sql.out
index 9847386d76..5068a37130 100644
--- a/sql/core/src/test/resources/sql-tests/results/postgreSQL/timestamp.sql.out
+++ b/sql/core/src/test/resources/sql-tests/results/postgreSQL/timestamp.sql.out
@@ -256,10 +256,13 @@ SELECT '' AS `54`, d1 as `timestamp`,
     date_part( 'minute', d1) AS `minute`, date_part( 'second', d1) AS `second`
     FROM TIMESTAMP_TBL WHERE d1 BETWEEN '1902-01-01' AND '2038-01-01'
 -- !query schema
-struct<>
+struct<54:string,timestamp:timestamp,year:int,month:int,day:int,hour:int,minute:int,second:decimal(8,6)>
 -- !query output
-org.apache.spark.sql.AnalysisException
-cannot resolve 'year(spark_catalog.default.timestamp_tbl.d1)' due to data type mismatch: argument 1 requires date type, however, 'spark_catalog.default.timestamp_tbl.d1' is of timestamp type.; line 2 pos 4
+	1969-12-31 16:00:00	1969	12	31	16	0	0.000000
+	1997-01-02 00:00:00	1997	1	2	0	0	0.000000
+	1997-01-02 03:04:05	1997	1	2	3	4	5.000000
+	1997-02-10 17:32:01	1997	2	10	17	32	1.000000
+	2001-09-22 18:19:20	2001	9	22	18	19	20.000000
 
 
 -- !query
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 6dbffd7a8b..867738d418 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -4025,6 +4025,14 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
     assert(minuteToSecDF.schema.head.dataType === DayTimeIntervalType(2, 3))
   }
 
+  test("SPARK-35937: Extract date field from timestamp should work in ANSI mode") {
+    withSQLConf(SQLConf.ANSI_ENABLED.key -> "true") {
+      checkAnswer(sql("select extract(year from to_timestamp('2021-01-02 03:04:05'))"), Row(2021))
+      checkAnswer(sql("select extract(month from to_timestamp('2021-01-02 03:04:05'))"), Row(1))
+      checkAnswer(sql("select extract(day from to_timestamp('2021-01-02 03:04:05'))"), Row(2))
+    }
+  }
+
   test("SPARK-35545: split SubqueryExpression's children field into outer attributes and " +
     "join conditions") {
     withView("t") {