diff --git a/connector/connect/common/src/main/protobuf/spark/connect/relations.proto b/connector/connect/common/src/main/protobuf/spark/connect/relations.proto
index b9f3c01f1ff7a..f49fca079b036 100644
--- a/connector/connect/common/src/main/protobuf/spark/connect/relations.proto
+++ b/connector/connect/common/src/main/protobuf/spark/connect/relations.proto
@@ -66,6 +66,7 @@ message Relation {
     GroupMap group_map = 31;
     CoGroupMap co_group_map = 32;
     WithWatermark with_watermark = 33;
+    ApplyInPandasWithState apply_in_pandas_with_state = 34;
 
     // NA functions
     NAFill fill_na = 90;
@@ -840,6 +841,29 @@ message CoGroupMap {
   CommonInlineUserDefinedFunction func = 5;
 }
 
+message ApplyInPandasWithState {
+  // (Required) Input relation for applyInPandasWithState.
+  Relation input = 1;
+
+  // (Required) Expressions for grouping keys.
+  repeated Expression grouping_expressions = 2;
+
+  // (Required) Input user-defined function.
+  CommonInlineUserDefinedFunction func = 3;
+
+  // (Required) Schema for the output DataFrame.
+  string output_schema = 4;
+
+  // (Required) Schema for the state.
+  string state_schema = 5;
+
+  // (Required) The output mode of the function.
+  string output_mode = 6;
+
+  // (Required) Timeout configuration for groups that do not receive data for a while.
+  string timeout_conf = 7;
+}
+
 // Collect arbitrary (named) metrics from a dataset.
 message CollectMetrics {
   // (Required) The input relation.
diff --git a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
index 89e5397b24f13..f2b03ca05d446 100644
--- a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
+++ b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
@@ -133,6 +133,8 @@ class SparkConnectPlanner(val session: SparkSession) {
         transformGroupMap(rel.getGroupMap)
       case proto.Relation.RelTypeCase.CO_GROUP_MAP =>
         transformCoGroupMap(rel.getCoGroupMap)
+      case proto.Relation.RelTypeCase.APPLY_IN_PANDAS_WITH_STATE =>
+        transformApplyInPandasWithState(rel.getApplyInPandasWithState)
       case proto.Relation.RelTypeCase.COLLECT_METRICS =>
         transformCollectMetrics(rel.getCollectMetrics)
       case proto.Relation.RelTypeCase.PARSE => transformParse(rel.getParse)
@@ -583,6 +585,27 @@ class SparkConnectPlanner(val session: SparkSession) {
     input.flatMapCoGroupsInPandas(other, pythonUdf).logicalPlan
   }
 
+  private def transformApplyInPandasWithState(rel: proto.ApplyInPandasWithState): LogicalPlan = {
+    val pythonUdf = transformPythonUDF(rel.getFunc)
+    val cols =
+      rel.getGroupingExpressionsList.asScala.toSeq.map(expr => Column(transformExpression(expr)))
+
+    val outputSchema = parseSchema(rel.getOutputSchema)
+
+    val stateSchema = parseSchema(rel.getStateSchema)
+
+    Dataset
+      .ofRows(session, transformRelation(rel.getInput))
+      .groupBy(cols: _*)
+      .applyInPandasWithState(
+        pythonUdf,
+        outputSchema,
+        stateSchema,
+        rel.getOutputMode,
+        rel.getTimeoutConf)
+      .logicalPlan
+  }
+
   private def transformWithColumnsRenamed(rel: proto.WithColumnsRenamed): LogicalPlan = {
     Dataset
       .ofRows(session, transformRelation(rel.getInput))
diff --git a/dev/sparktestsupport/modules.py b/dev/sparktestsupport/modules.py
index 4f6f7765a5b71..5df3a536f8f67 100644
--- a/dev/sparktestsupport/modules.py
+++ b/dev/sparktestsupport/modules.py
@@ -778,6 +778,7 @@ def __hash__(self):
         "pyspark.sql.tests.connect.test_parity_pandas_grouped_map",
         "pyspark.sql.tests.connect.test_parity_pandas_cogrouped_map",
         "pyspark.sql.tests.connect.streaming.test_parity_streaming",
+        "pyspark.sql.tests.connect.test_parity_pandas_grouped_map_with_state",
         # ml doctests
         "pyspark.ml.connect.functions",
         # ml unittests
diff --git a/python/pyspark/sql/connect/_typing.py b/python/pyspark/sql/connect/_typing.py
index 6bdde2926cbd8..4c76e37659c07 100644
--- a/python/pyspark/sql/connect/_typing.py
+++ b/python/pyspark/sql/connect/_typing.py
@@ -32,6 +32,7 @@
 
 from pyspark.sql.connect.column import Column
 from pyspark.sql.connect.types import DataType
+from pyspark.sql.streaming.state import GroupState
 
 
 ColumnOrName = Union[Column, str]
@@ -63,6 +64,10 @@
 
 PandasCogroupedMapFunction = Callable[[DataFrameLike, DataFrameLike], DataFrameLike]
 
+PandasGroupedMapFunctionWithState = Callable[
+    [Any, Iterable[DataFrameLike], GroupState], Iterable[DataFrameLike]
+]
+
 
 class UserDefinedFunctionLike(Protocol):
     func: Callable[..., Any]
diff --git a/python/pyspark/sql/connect/group.py b/python/pyspark/sql/connect/group.py
index 8377caac592d3..160b1b49072a5 100644
--- a/python/pyspark/sql/connect/group.py
+++ b/python/pyspark/sql/connect/group.py
@@ -36,6 +36,7 @@
 from pyspark.sql.group import GroupedData as PySparkGroupedData
 from pyspark.sql.pandas.group_ops import PandasCogroupedOps as PySparkPandasCogroupedOps
 from pyspark.sql.types import NumericType
+from pyspark.sql.types import StructType
 
 import pyspark.sql.connect.plan as plan
 from pyspark.sql.connect.column import Column
@@ -47,6 +48,7 @@
         PandasGroupedMapFunction,
         GroupedMapPandasUserDefinedFunction,
         PandasCogroupedMapFunction,
+        PandasGroupedMapFunctionWithState,
     )
     from pyspark.sql.connect.dataframe import DataFrame
     from pyspark.sql.types import StructType
@@ -262,8 +264,48 @@ def applyInPandas(
 
     applyInPandas.__doc__ = PySparkGroupedData.applyInPandas.__doc__
 
-    def applyInPandasWithState(self, *args: Any, **kwargs: Any) -> None:
-        raise NotImplementedError("applyInPandasWithState() is not implemented.")
+    def applyInPandasWithState(
+        self,
+        func: "PandasGroupedMapFunctionWithState",
+        outputStructType: Union[StructType, str],
+        stateStructType: Union[StructType, str],
+        outputMode: str,
+        timeoutConf: str,
+    ) -> "DataFrame":
+        from pyspark.sql.connect.udf import UserDefinedFunction
+        from pyspark.sql.connect.dataframe import DataFrame
+
+        udf_obj = UserDefinedFunction(
+            func,
+            returnType=outputStructType,
+            evalType=PythonEvalType.SQL_GROUPED_MAP_PANDAS_UDF_WITH_STATE,
+        )
+
+        output_schema: str = (
+            outputStructType.json()
+            if isinstance(outputStructType, StructType)
+            else outputStructType
+        )
+
+        state_schema: str = (
+            stateStructType.json() if isinstance(stateStructType, StructType) else stateStructType
+        )
+
+        return DataFrame.withPlan(
+            plan.ApplyInPandasWithState(
+                child=self._df._plan,
+                grouping_cols=self._grouping_cols,
+                function=udf_obj,
+                output_schema=output_schema,
+                state_schema=state_schema,
+                output_mode=outputMode,
+                timeout_conf=timeoutConf,
+                cols=self._df.columns,
+            ),
+            session=self._df._session,
+        )
+
+    applyInPandasWithState.__doc__ = PySparkGroupedData.applyInPandasWithState.__doc__
 
     def cogroup(self, other: "GroupedData") -> "PandasCogroupedOps":
         return PandasCogroupedOps(self, other)
diff --git a/python/pyspark/sql/connect/plan.py b/python/pyspark/sql/connect/plan.py
index 5ae599306ee16..586668864cc9e 100644
--- a/python/pyspark/sql/connect/plan.py
+++ b/python/pyspark/sql/connect/plan.py
@@ -2053,6 +2053,45 @@ def plan(self, session: "SparkConnectClient") -> proto.Relation:
         return plan
 
 
+class ApplyInPandasWithState(LogicalPlan):
+    """Logical plan object for a applyInPandasWithState."""
+
+    def __init__(
+        self,
+        child: Optional["LogicalPlan"],
+        grouping_cols: Sequence[Column],
+        function: "UserDefinedFunction",
+        output_schema: str,
+        state_schema: str,
+        output_mode: str,
+        timeout_conf: str,
+        cols: List[str],
+    ):
+        assert isinstance(grouping_cols, list) and all(isinstance(c, Column) for c in grouping_cols)
+
+        super().__init__(child)
+        self._grouping_cols = grouping_cols
+        self._func = function._build_common_inline_user_defined_function(*cols)
+        self._output_schema = output_schema
+        self._state_schema = state_schema
+        self._output_mode = output_mode
+        self._timeout_conf = timeout_conf
+
+    def plan(self, session: "SparkConnectClient") -> proto.Relation:
+        assert self._child is not None
+        plan = self._create_proto_relation()
+        plan.apply_in_pandas_with_state.input.CopyFrom(self._child.plan(session))
+        plan.apply_in_pandas_with_state.grouping_expressions.extend(
+            [c.to_plan(session) for c in self._grouping_cols]
+        )
+        plan.apply_in_pandas_with_state.func.CopyFrom(self._func.to_plan_udf(session))
+        plan.apply_in_pandas_with_state.output_schema = self._output_schema
+        plan.apply_in_pandas_with_state.state_schema = self._state_schema
+        plan.apply_in_pandas_with_state.output_mode = self._output_mode
+        plan.apply_in_pandas_with_state.timeout_conf = self._timeout_conf
+        return plan
+
+
 class CachedRelation(LogicalPlan):
     def __init__(self, plan: proto.Relation) -> None:
         super(CachedRelation, self).__init__(None)
diff --git a/python/pyspark/sql/connect/proto/relations_pb2.py b/python/pyspark/sql/connect/proto/relations_pb2.py
index c37af023846a7..8229dc18afef6 100644
--- a/python/pyspark/sql/connect/proto/relations_pb2.py
+++ b/python/pyspark/sql/connect/proto/relations_pb2.py
@@ -36,7 +36,7 @@
 
 
 DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(
-    b'\n\x1dspark/connect/relations.proto\x12\rspark.connect\x1a\x19google/protobuf/any.proto\x1a\x1fspark/connect/expressions.proto\x1a\x19spark/connect/types.proto\x1a\x1bspark/connect/catalog.proto"\xf6\x14\n\x08Relation\x12\x35\n\x06\x63ommon\x18\x01 \x01(\x0b\x32\x1d.spark.connect.RelationCommonR\x06\x63ommon\x12)\n\x04read\x18\x02 \x01(\x0b\x32\x13.spark.connect.ReadH\x00R\x04read\x12\x32\n\x07project\x18\x03 \x01(\x0b\x32\x16.spark.connect.ProjectH\x00R\x07project\x12/\n\x06\x66ilter\x18\x04 \x01(\x0b\x32\x15.spark.connect.FilterH\x00R\x06\x66ilter\x12)\n\x04join\x18\x05 \x01(\x0b\x32\x13.spark.connect.JoinH\x00R\x04join\x12\x34\n\x06set_op\x18\x06 \x01(\x0b\x32\x1b.spark.connect.SetOperationH\x00R\x05setOp\x12)\n\x04sort\x18\x07 \x01(\x0b\x32\x13.spark.connect.SortH\x00R\x04sort\x12,\n\x05limit\x18\x08 \x01(\x0b\x32\x14.spark.connect.LimitH\x00R\x05limit\x12\x38\n\taggregate\x18\t \x01(\x0b\x32\x18.spark.connect.AggregateH\x00R\taggregate\x12&\n\x03sql\x18\n 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 )
 
 
@@ -96,6 +96,7 @@
 _MAPPARTITIONS = DESCRIPTOR.message_types_by_name["MapPartitions"]
 _GROUPMAP = DESCRIPTOR.message_types_by_name["GroupMap"]
 _COGROUPMAP = DESCRIPTOR.message_types_by_name["CoGroupMap"]
+_APPLYINPANDASWITHSTATE = DESCRIPTOR.message_types_by_name["ApplyInPandasWithState"]
 _COLLECTMETRICS = DESCRIPTOR.message_types_by_name["CollectMetrics"]
 _PARSE = DESCRIPTOR.message_types_by_name["Parse"]
 _PARSE_OPTIONSENTRY = _PARSE.nested_types_by_name["OptionsEntry"]
@@ -687,6 +688,17 @@
 )
 _sym_db.RegisterMessage(CoGroupMap)
 
+ApplyInPandasWithState = _reflection.GeneratedProtocolMessageType(
+    "ApplyInPandasWithState",
+    (_message.Message,),
+    {
+        "DESCRIPTOR": _APPLYINPANDASWITHSTATE,
+        "__module__": "spark.connect.relations_pb2"
+        # @@protoc_insertion_point(class_scope:spark.connect.ApplyInPandasWithState)
+    },
+)
+_sym_db.RegisterMessage(ApplyInPandasWithState)
+
 CollectMetrics = _reflection.GeneratedProtocolMessageType(
     "CollectMetrics",
     (_message.Message,),
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     _PARSE_OPTIONSENTRY._serialized_options = b"8\001"
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-    _READ_NAMEDTABLE_OPTIONSENTRY._serialized_end = 3492
-    _READ_DATASOURCE._serialized_start = 3495
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+    _STATSUMMARY._serialized_start = 7300
+    _STATSUMMARY._serialized_end = 7392
+    _STATDESCRIBE._serialized_start = 7394
+    _STATDESCRIBE._serialized_end = 7475
+    _STATCROSSTAB._serialized_start = 7477
+    _STATCROSSTAB._serialized_end = 7578
+    _STATCOV._serialized_start = 7580
+    _STATCOV._serialized_end = 7676
+    _STATCORR._serialized_start = 7679
+    _STATCORR._serialized_end = 7816
+    _STATAPPROXQUANTILE._serialized_start = 7819
+    _STATAPPROXQUANTILE._serialized_end = 7983
+    _STATFREQITEMS._serialized_start = 7985
+    _STATFREQITEMS._serialized_end = 8110
+    _STATSAMPLEBY._serialized_start = 8113
+    _STATSAMPLEBY._serialized_end = 8422
+    _STATSAMPLEBY_FRACTION._serialized_start = 8314
+    _STATSAMPLEBY_FRACTION._serialized_end = 8413
+    _NAFILL._serialized_start = 8425
+    _NAFILL._serialized_end = 8559
+    _NADROP._serialized_start = 8562
+    _NADROP._serialized_end = 8696
+    _NAREPLACE._serialized_start = 8699
+    _NAREPLACE._serialized_end = 8995
+    _NAREPLACE_REPLACEMENT._serialized_start = 8854
+    _NAREPLACE_REPLACEMENT._serialized_end = 8995
+    _TODF._serialized_start = 8997
+    _TODF._serialized_end = 9085
+    _WITHCOLUMNSRENAMED._serialized_start = 9088
+    _WITHCOLUMNSRENAMED._serialized_end = 9327
+    _WITHCOLUMNSRENAMED_RENAMECOLUMNSMAPENTRY._serialized_start = 9260
+    _WITHCOLUMNSRENAMED_RENAMECOLUMNSMAPENTRY._serialized_end = 9327
+    _WITHCOLUMNS._serialized_start = 9329
+    _WITHCOLUMNS._serialized_end = 9448
+    _WITHWATERMARK._serialized_start = 9451
+    _WITHWATERMARK._serialized_end = 9585
+    _HINT._serialized_start = 9588
+    _HINT._serialized_end = 9720
+    _UNPIVOT._serialized_start = 9723
+    _UNPIVOT._serialized_end = 10050
+    _UNPIVOT_VALUES._serialized_start = 9980
+    _UNPIVOT_VALUES._serialized_end = 10039
+    _TOSCHEMA._serialized_start = 10052
+    _TOSCHEMA._serialized_end = 10158
+    _REPARTITIONBYEXPRESSION._serialized_start = 10161
+    _REPARTITIONBYEXPRESSION._serialized_end = 10364
+    _MAPPARTITIONS._serialized_start = 10367
+    _MAPPARTITIONS._serialized_end = 10548
+    _GROUPMAP._serialized_start = 10551
+    _GROUPMAP._serialized_end = 10754
+    _COGROUPMAP._serialized_start = 10757
+    _COGROUPMAP._serialized_end = 11109
+    _APPLYINPANDASWITHSTATE._serialized_start = 11112
+    _APPLYINPANDASWITHSTATE._serialized_end = 11469
+    _COLLECTMETRICS._serialized_start = 11472
+    _COLLECTMETRICS._serialized_end = 11608
+    _PARSE._serialized_start = 11611
+    _PARSE._serialized_end = 11999
+    _PARSE_OPTIONSENTRY._serialized_start = 3535
+    _PARSE_OPTIONSENTRY._serialized_end = 3593
+    _PARSE_PARSEFORMAT._serialized_start = 11900
+    _PARSE_PARSEFORMAT._serialized_end = 11988
 # @@protoc_insertion_point(module_scope)
diff --git a/python/pyspark/sql/connect/proto/relations_pb2.pyi b/python/pyspark/sql/connect/proto/relations_pb2.pyi
index 664206c9c9306..14552d1f127be 100644
--- a/python/pyspark/sql/connect/proto/relations_pb2.pyi
+++ b/python/pyspark/sql/connect/proto/relations_pb2.pyi
@@ -95,6 +95,7 @@ class Relation(google.protobuf.message.Message):
     GROUP_MAP_FIELD_NUMBER: builtins.int
     CO_GROUP_MAP_FIELD_NUMBER: builtins.int
     WITH_WATERMARK_FIELD_NUMBER: builtins.int
+    APPLY_IN_PANDAS_WITH_STATE_FIELD_NUMBER: builtins.int
     FILL_NA_FIELD_NUMBER: builtins.int
     DROP_NA_FIELD_NUMBER: builtins.int
     REPLACE_FIELD_NUMBER: builtins.int
@@ -176,6 +177,8 @@ class Relation(google.protobuf.message.Message):
     @property
     def with_watermark(self) -> global___WithWatermark: ...
     @property
+    def apply_in_pandas_with_state(self) -> global___ApplyInPandasWithState: ...
+    @property
     def fill_na(self) -> global___NAFill:
         """NA functions"""
     @property
@@ -245,6 +248,7 @@ class Relation(google.protobuf.message.Message):
         group_map: global___GroupMap | None = ...,
         co_group_map: global___CoGroupMap | None = ...,
         with_watermark: global___WithWatermark | None = ...,
+        apply_in_pandas_with_state: global___ApplyInPandasWithState | None = ...,
         fill_na: global___NAFill | None = ...,
         drop_na: global___NADrop | None = ...,
         replace: global___NAReplace | None = ...,
@@ -265,6 +269,8 @@ class Relation(google.protobuf.message.Message):
         field_name: typing_extensions.Literal[
             "aggregate",
             b"aggregate",
+            "apply_in_pandas_with_state",
+            b"apply_in_pandas_with_state",
             "approx_quantile",
             b"approx_quantile",
             "catalog",
@@ -366,6 +372,8 @@ class Relation(google.protobuf.message.Message):
         field_name: typing_extensions.Literal[
             "aggregate",
             b"aggregate",
+            "apply_in_pandas_with_state",
+            b"apply_in_pandas_with_state",
             "approx_quantile",
             b"approx_quantile",
             "catalog",
@@ -497,6 +505,7 @@ class Relation(google.protobuf.message.Message):
         "group_map",
         "co_group_map",
         "with_watermark",
+        "apply_in_pandas_with_state",
         "fill_na",
         "drop_na",
         "replace",
@@ -2980,6 +2989,77 @@ class CoGroupMap(google.protobuf.message.Message):
 
 global___CoGroupMap = CoGroupMap
 
+class ApplyInPandasWithState(google.protobuf.message.Message):
+    DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+    INPUT_FIELD_NUMBER: builtins.int
+    GROUPING_EXPRESSIONS_FIELD_NUMBER: builtins.int
+    FUNC_FIELD_NUMBER: builtins.int
+    OUTPUT_SCHEMA_FIELD_NUMBER: builtins.int
+    STATE_SCHEMA_FIELD_NUMBER: builtins.int
+    OUTPUT_MODE_FIELD_NUMBER: builtins.int
+    TIMEOUT_CONF_FIELD_NUMBER: builtins.int
+    @property
+    def input(self) -> global___Relation:
+        """(Required) Input relation for applyInPandasWithState."""
+    @property
+    def grouping_expressions(
+        self,
+    ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
+        pyspark.sql.connect.proto.expressions_pb2.Expression
+    ]:
+        """(Required) Expressions for grouping keys."""
+    @property
+    def func(self) -> pyspark.sql.connect.proto.expressions_pb2.CommonInlineUserDefinedFunction:
+        """(Required) Input user-defined function."""
+    output_schema: builtins.str
+    """(Required) Schema for the output DataFrame."""
+    state_schema: builtins.str
+    """(Required) Schema for the state."""
+    output_mode: builtins.str
+    """(Required) The output mode of the function."""
+    timeout_conf: builtins.str
+    """(Required) Timeout configuration for groups that do not receive data for a while."""
+    def __init__(
+        self,
+        *,
+        input: global___Relation | None = ...,
+        grouping_expressions: collections.abc.Iterable[
+            pyspark.sql.connect.proto.expressions_pb2.Expression
+        ]
+        | None = ...,
+        func: pyspark.sql.connect.proto.expressions_pb2.CommonInlineUserDefinedFunction
+        | None = ...,
+        output_schema: builtins.str = ...,
+        state_schema: builtins.str = ...,
+        output_mode: builtins.str = ...,
+        timeout_conf: builtins.str = ...,
+    ) -> None: ...
+    def HasField(
+        self, field_name: typing_extensions.Literal["func", b"func", "input", b"input"]
+    ) -> builtins.bool: ...
+    def ClearField(
+        self,
+        field_name: typing_extensions.Literal[
+            "func",
+            b"func",
+            "grouping_expressions",
+            b"grouping_expressions",
+            "input",
+            b"input",
+            "output_mode",
+            b"output_mode",
+            "output_schema",
+            b"output_schema",
+            "state_schema",
+            b"state_schema",
+            "timeout_conf",
+            b"timeout_conf",
+        ],
+    ) -> None: ...
+
+global___ApplyInPandasWithState = ApplyInPandasWithState
+
 class CollectMetrics(google.protobuf.message.Message):
     """Collect arbitrary (named) metrics from a dataset."""
 
diff --git a/python/pyspark/sql/pandas/group_ops.py b/python/pyspark/sql/pandas/group_ops.py
index 12ceb56c79ff1..857ecd2e58211 100644
--- a/python/pyspark/sql/pandas/group_ops.py
+++ b/python/pyspark/sql/pandas/group_ops.py
@@ -273,6 +273,9 @@ def applyInPandasWithState(
 
         .. versionadded:: 3.4.0
 
+        .. versionchanged:: 3.5.0
+            Supports Spark Connect.
+
         Parameters
         ----------
         func : function
diff --git a/python/pyspark/sql/tests/connect/test_connect_basic.py b/python/pyspark/sql/tests/connect/test_connect_basic.py
index 166a8b23bd716..b1b3a94accff5 100644
--- a/python/pyspark/sql/tests/connect/test_connect_basic.py
+++ b/python/pyspark/sql/tests/connect/test_connect_basic.py
@@ -2928,13 +2928,6 @@ def test_unsupported_functions(self):
             with self.assertRaises(NotImplementedError):
                 getattr(df, f)()
 
-    def test_unsupported_group_functions(self):
-        # SPARK-41927: Disable unsupported functions.
-        cg = self.connect.read.table(self.tbl_name).groupBy("id")
-        for f in ("applyInPandasWithState",):
-            with self.assertRaises(NotImplementedError):
-                getattr(cg, f)()
-
     def test_unsupported_session_functions(self):
         # SPARK-41934: Disable unsupported functions.
 
diff --git a/python/pyspark/sql/tests/connect/test_parity_pandas_grouped_map_with_state.py b/python/pyspark/sql/tests/connect/test_parity_pandas_grouped_map_with_state.py
new file mode 100644
index 0000000000000..685f12a0c8251
--- /dev/null
+++ b/python/pyspark/sql/tests/connect/test_parity_pandas_grouped_map_with_state.py
@@ -0,0 +1,46 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import unittest
+
+from pyspark.sql.tests.pandas.test_pandas_grouped_map_with_state import (
+    GroupedApplyInPandasWithStateTestsMixin,
+)
+from pyspark.testing.connectutils import ReusedConnectTestCase
+
+
+class GroupedApplyInPandasWithStateTests(
+    GroupedApplyInPandasWithStateTestsMixin, ReusedConnectTestCase
+):
+    @unittest.skip("Query manager API will be supported later with SPARK-43032.")
+    def test_apply_in_pandas_with_state_basic(self):
+        super().test_apply_in_pandas_with_state_basic()
+
+    @unittest.skip("Query manager API will be supported later with SPARK-43032.")
+    def test_apply_in_pandas_with_state_python_worker_random_failure(self):
+        super().test_apply_in_pandas_with_state_python_worker_random_failure()
+
+
+if __name__ == "__main__":
+    from pyspark.sql.tests.connect.test_parity_pandas_grouped_map_with_state import *  # noqa: F401
+
+    try:
+        import xmlrunner
+
+        testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
+    except ImportError:
+        testRunner = None
+    unittest.main(testRunner=testRunner, verbosity=2)
diff --git a/python/pyspark/sql/tests/pandas/test_pandas_grouped_map_with_state.py b/python/pyspark/sql/tests/pandas/test_pandas_grouped_map_with_state.py
index 9600d1e344575..a2a6544faa0fd 100644
--- a/python/pyspark/sql/tests/pandas/test_pandas_grouped_map_with_state.py
+++ b/python/pyspark/sql/tests/pandas/test_pandas_grouped_map_with_state.py
@@ -53,7 +53,7 @@
     not have_pandas or not have_pyarrow,
     cast(str, pandas_requirement_message or pyarrow_requirement_message),
 )
-class GroupedApplyInPandasWithStateTests(ReusedSQLTestCase):
+class GroupedApplyInPandasWithStateTestsMixin:
     @classmethod
     def conf(cls):
         cfg = SparkConf()
@@ -236,6 +236,12 @@ def assert_test():
             q.stop()
 
 
+class GroupedApplyInPandasWithStateTests(
+    GroupedApplyInPandasWithStateTestsMixin, ReusedSQLTestCase
+):
+    pass
+
+
 if __name__ == "__main__":
     from pyspark.sql.tests.pandas.test_pandas_grouped_map_with_state import *  # noqa: F401