diff --git a/docs/supported_ops.md b/docs/supported_ops.md
index a64f432983e..0feefaec297 100644
--- a/docs/supported_ops.md
+++ b/docs/supported_ops.md
@@ -15230,7 +15230,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15251,7 +15251,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15273,7 +15273,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15294,7 +15294,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15389,7 +15389,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15410,7 +15410,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15432,7 +15432,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
@@ -15453,7 +15453,7 @@ are limited.
 <td><b>NS</b></td>
 <td><b>NS</b></td>
 <td> </td>
-<td><b>NS</b></td>
+<td><em>PS<br/>UTC is only supported TZ for child TIMESTAMP;<br/>unsupported child types BINARY, CALENDAR, ARRAY, STRUCT, UDT</em></td>
 <td><b>NS</b></td>
 </tr>
 <tr>
diff --git a/integration_tests/src/main/python/hash_aggregate_test.py b/integration_tests/src/main/python/hash_aggregate_test.py
index f862a11d996..54e2f913784 100644
--- a/integration_tests/src/main/python/hash_aggregate_test.py
+++ b/integration_tests/src/main/python/hash_aggregate_test.py
@@ -1704,3 +1704,46 @@ def test_groupby_std_variance_partial_replace_fallback(data_gen,
         exist_classes=','.join(exist_clz),
         non_exist_classes=','.join(non_exist_clz),
         conf=local_conf)
+
+#
+# test min max on single level structure
+#
+gens_for_max_min = [byte_gen, short_gen, int_gen, long_gen,
+    FloatGen(no_nans = True), DoubleGen(no_nans = True),
+    string_gen, boolean_gen,
+    date_gen, timestamp_gen,
+    DecimalGen(precision=12, scale=2),
+    DecimalGen(precision=36, scale=5),
+    null_gen]
+@ignore_order(local=True)
+@pytest.mark.parametrize('data_gen',  gens_for_max_min, ids=idfn)
+def test_min_max_for_single_level_struct(data_gen):
+    df_gen = [
+        ('a', StructGen([
+                ('aa', data_gen),
+                ('ab', data_gen)])),
+        ('b', RepeatSeqGen(IntegerGen(), length=20))]
+
+    # test max
+    assert_gpu_and_cpu_are_equal_sql(
+        lambda spark : gen_df(spark, df_gen),
+        "hash_agg_table",
+        'select b, max(a) from hash_agg_table group by b',
+        _no_nans_float_conf)
+    assert_gpu_and_cpu_are_equal_sql(
+        lambda spark : gen_df(spark, df_gen),
+        "hash_agg_table",
+        'select max(a) from hash_agg_table',
+        _no_nans_float_conf)
+
+    # test min
+    assert_gpu_and_cpu_are_equal_sql(
+        lambda spark : gen_df(spark, df_gen, length=1024),
+        "hash_agg_table",
+        'select b, min(a) from hash_agg_table group by b',
+        _no_nans_float_conf)
+    assert_gpu_and_cpu_are_equal_sql(
+        lambda spark : gen_df(spark, df_gen, length=1024),
+        "hash_agg_table",
+        'select min(a) from hash_agg_table',
+        _no_nans_float_conf)
diff --git a/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOverrides.scala b/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOverrides.scala
index 7637686d898..31401832bbb 100644
--- a/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOverrides.scala
+++ b/sql-plugin/src/main/scala/com/nvidia/spark/rapids/GpuOverrides.scala
@@ -2234,14 +2234,27 @@ object GpuOverrides extends Logging {
       }),
     expr[Max](
       "Max aggregate operator",
-      ExprChecks.fullAgg(
-        TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL, TypeSig.orderable,
-        Seq(ParamCheck("input",
-          (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL)
+      ExprChecksImpl(
+        ExprChecks.reductionAndGroupByAgg(
+          // Max supports single level struct, e.g.:  max(struct(string, string))
+          (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL + TypeSig.STRUCT)
+            .nested(TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL),
+          TypeSig.orderable,
+          Seq(ParamCheck("input",
+            (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL + TypeSig.STRUCT)
+              .nested(TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL)
               .withPsNote(TypeEnum.DOUBLE, nanAggPsNote)
               .withPsNote(TypeEnum.FLOAT, nanAggPsNote),
-          TypeSig.orderable))
-      ),
+            TypeSig.orderable))).asInstanceOf[ExprChecksImpl].contexts
+          ++
+          ExprChecks.windowOnly(
+            (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL),
+            TypeSig.orderable,
+            Seq(ParamCheck("input",
+              (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL)
+                .withPsNote(TypeEnum.DOUBLE, nanAggPsNote)
+                .withPsNote(TypeEnum.FLOAT, nanAggPsNote),
+              TypeSig.orderable))).asInstanceOf[ExprChecksImpl].contexts),
       (max, conf, p, r) => new AggExprMeta[Max](max, conf, p, r) {
         override def tagAggForGpu(): Unit = {
           val dataType = max.child.dataType
@@ -2256,14 +2269,27 @@ object GpuOverrides extends Logging {
       }),
     expr[Min](
       "Min aggregate operator",
-      ExprChecks.fullAgg(
-        TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL, TypeSig.orderable,
-        Seq(ParamCheck("input",
-          (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL)
+      ExprChecksImpl(
+        ExprChecks.reductionAndGroupByAgg(
+          // Min supports single level struct, e.g.:  max(struct(string, string))
+          (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL + TypeSig.STRUCT)
+            .nested(TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL),
+          TypeSig.orderable,
+          Seq(ParamCheck("input",
+            (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL + TypeSig.STRUCT)
+              .nested(TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL)
               .withPsNote(TypeEnum.DOUBLE, nanAggPsNote)
               .withPsNote(TypeEnum.FLOAT, nanAggPsNote),
-          TypeSig.orderable))
-      ),
+            TypeSig.orderable))).asInstanceOf[ExprChecksImpl].contexts
+          ++
+          ExprChecks.windowOnly(
+            (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL),
+            TypeSig.orderable,
+            Seq(ParamCheck("input",
+              (TypeSig.commonCudfTypes + TypeSig.DECIMAL_128 + TypeSig.NULL)
+                .withPsNote(TypeEnum.DOUBLE, nanAggPsNote)
+                .withPsNote(TypeEnum.FLOAT, nanAggPsNote),
+              TypeSig.orderable))).asInstanceOf[ExprChecksImpl].contexts),
       (a, conf, p, r) => new AggExprMeta[Min](a, conf, p, r) {
         override def tagAggForGpu(): Unit = {
           val dataType = a.child.dataType