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 4d96b6b0c7ea9..2221b4e39826e 100644
--- a/connector/connect/common/src/main/protobuf/spark/connect/relations.proto
+++ b/connector/connect/common/src/main/protobuf/spark/connect/relations.proto
@@ -122,8 +122,10 @@ message Read {
   }
 
   message DataSource {
-    // (Required) Supported formats include: parquet, orc, text, json, parquet, csv, avro.
-    string format = 1;
+    // (Optional) Supported formats include: parquet, orc, text, json, parquet, csv, avro.
+    //
+    // If not set, the value from SQL conf 'spark.sql.sources.default' will be used.
+    optional string format = 1;
 
     // (Optional) If not set, Spark will infer the schema.
     //
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 cc43c1cace3c9..887379ab80de9 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
@@ -667,12 +667,11 @@ class SparkConnectPlanner(val session: SparkSession) {
         UnresolvedRelation(multipartIdentifier)
 
       case proto.Read.ReadTypeCase.DATA_SOURCE =>
-        if (rel.getDataSource.getFormat == "") {
-          throw InvalidPlanInput("DataSource requires a format")
-        }
         val localMap = CaseInsensitiveMap[String](rel.getDataSource.getOptionsMap.asScala.toMap)
         val reader = session.read
-        reader.format(rel.getDataSource.getFormat)
+        if (rel.getDataSource.hasFormat) {
+          reader.format(rel.getDataSource.getFormat)
+        }
         localMap.foreach { case (key, value) => reader.option(key, value) }
         if (rel.getDataSource.hasSchema && rel.getDataSource.getSchema.nonEmpty) {
 
diff --git a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectPlannerSuite.scala b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectPlannerSuite.scala
index 3e4a0f94ea216..83056c2772977 100644
--- a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectPlannerSuite.scala
+++ b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectPlannerSuite.scala
@@ -332,18 +332,6 @@ class SparkConnectPlannerSuite extends SparkFunSuite with SparkConnectPlanTest {
     assert(res.nodeName == "Aggregate")
   }
 
-  test("Invalid DataSource") {
-    val dataSource = proto.Read.DataSource.newBuilder()
-
-    val e = intercept[InvalidPlanInput](
-      transform(
-        proto.Relation
-          .newBuilder()
-          .setRead(proto.Read.newBuilder().setDataSource(dataSource))
-          .build()))
-    assert(e.getMessage.contains("DataSource requires a format"))
-  }
-
   test("Test invalid deduplicate") {
     val deduplicate = proto.Deduplicate
       .newBuilder()
diff --git a/python/pyspark/sql/connect/plan.py b/python/pyspark/sql/connect/plan.py
index badbb9871ed25..857cca64c6f7c 100644
--- a/python/pyspark/sql/connect/plan.py
+++ b/python/pyspark/sql/connect/plan.py
@@ -255,15 +255,14 @@ class DataSource(LogicalPlan):
 
     def __init__(
         self,
-        format: str,
+        format: Optional[str] = None,
         schema: Optional[str] = None,
         options: Optional[Mapping[str, str]] = None,
         paths: Optional[List[str]] = None,
     ) -> None:
         super().__init__(None)
 
-        assert isinstance(format, str) and format != ""
-
+        assert format is None or isinstance(format, str)
         assert schema is None or isinstance(schema, str)
 
         if options is not None:
@@ -282,7 +281,8 @@ def __init__(
 
     def plan(self, session: "SparkConnectClient") -> proto.Relation:
         plan = self._create_proto_relation()
-        plan.read.data_source.format = self._format
+        if self._format is not None:
+            plan.read.data_source.format = self._format
         if self._schema is not None:
             plan.read.data_source.schema = self._schema
         if self._options is not None and len(self._options) > 0:
diff --git a/python/pyspark/sql/connect/proto/relations_pb2.py b/python/pyspark/sql/connect/proto/relations_pb2.py
index 3afdf61e6811d..c6d9616e44c7a 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"\xb1\x12\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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+    _RANGE._serialized_end = 6190
+    _SUBQUERYALIAS._serialized_start = 6192
+    _SUBQUERYALIAS._serialized_end = 6306
+    _REPARTITION._serialized_start = 6309
+    _REPARTITION._serialized_end = 6451
+    _SHOWSTRING._serialized_start = 6454
+    _SHOWSTRING._serialized_end = 6596
+    _STATSUMMARY._serialized_start = 6598
+    _STATSUMMARY._serialized_end = 6690
+    _STATDESCRIBE._serialized_start = 6692
+    _STATDESCRIBE._serialized_end = 6773
+    _STATCROSSTAB._serialized_start = 6775
+    _STATCROSSTAB._serialized_end = 6876
+    _STATCOV._serialized_start = 6878
+    _STATCOV._serialized_end = 6974
+    _STATCORR._serialized_start = 6977
+    _STATCORR._serialized_end = 7114
+    _STATAPPROXQUANTILE._serialized_start = 7117
+    _STATAPPROXQUANTILE._serialized_end = 7281
+    _STATFREQITEMS._serialized_start = 7283
+    _STATFREQITEMS._serialized_end = 7408
+    _STATSAMPLEBY._serialized_start = 7411
+    _STATSAMPLEBY._serialized_end = 7720
+    _STATSAMPLEBY_FRACTION._serialized_start = 7612
+    _STATSAMPLEBY_FRACTION._serialized_end = 7711
+    _NAFILL._serialized_start = 7723
+    _NAFILL._serialized_end = 7857
+    _NADROP._serialized_start = 7860
+    _NADROP._serialized_end = 7994
+    _NAREPLACE._serialized_start = 7997
+    _NAREPLACE._serialized_end = 8293
+    _NAREPLACE_REPLACEMENT._serialized_start = 8152
+    _NAREPLACE_REPLACEMENT._serialized_end = 8293
+    _TODF._serialized_start = 8295
+    _TODF._serialized_end = 8383
+    _WITHCOLUMNSRENAMED._serialized_start = 8386
+    _WITHCOLUMNSRENAMED._serialized_end = 8625
+    _WITHCOLUMNSRENAMED_RENAMECOLUMNSMAPENTRY._serialized_start = 8558
+    _WITHCOLUMNSRENAMED_RENAMECOLUMNSMAPENTRY._serialized_end = 8625
+    _WITHCOLUMNS._serialized_start = 8627
+    _WITHCOLUMNS._serialized_end = 8746
+    _HINT._serialized_start = 8749
+    _HINT._serialized_end = 8881
+    _UNPIVOT._serialized_start = 8884
+    _UNPIVOT._serialized_end = 9211
+    _UNPIVOT_VALUES._serialized_start = 9141
+    _UNPIVOT_VALUES._serialized_end = 9200
+    _TOSCHEMA._serialized_start = 9213
+    _TOSCHEMA._serialized_end = 9319
+    _REPARTITIONBYEXPRESSION._serialized_start = 9322
+    _REPARTITIONBYEXPRESSION._serialized_end = 9525
+    _FRAMEMAP._serialized_start = 9527
+    _FRAMEMAP._serialized_end = 9652
 # @@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 3f3b9f4c5b026..27fd07a192eab 100644
--- a/python/pyspark/sql/connect/proto/relations_pb2.pyi
+++ b/python/pyspark/sql/connect/proto/relations_pb2.pyi
@@ -602,7 +602,10 @@ class Read(google.protobuf.message.Message):
         OPTIONS_FIELD_NUMBER: builtins.int
         PATHS_FIELD_NUMBER: builtins.int
         format: builtins.str
-        """(Required) Supported formats include: parquet, orc, text, json, parquet, csv, avro."""
+        """(Optional) Supported formats include: parquet, orc, text, json, parquet, csv, avro.
+
+        If not set, the value from SQL conf 'spark.sql.sources.default' will be used.
+        """
         schema: builtins.str
         """(Optional) If not set, Spark will infer the schema.
 
@@ -624,17 +627,29 @@ class Read(google.protobuf.message.Message):
         def __init__(
             self,
             *,
-            format: builtins.str = ...,
+            format: builtins.str | None = ...,
             schema: builtins.str | None = ...,
             options: collections.abc.Mapping[builtins.str, builtins.str] | None = ...,
             paths: collections.abc.Iterable[builtins.str] | None = ...,
         ) -> None: ...
         def HasField(
-            self, field_name: typing_extensions.Literal["_schema", b"_schema", "schema", b"schema"]
+            self,
+            field_name: typing_extensions.Literal[
+                "_format",
+                b"_format",
+                "_schema",
+                b"_schema",
+                "format",
+                b"format",
+                "schema",
+                b"schema",
+            ],
         ) -> builtins.bool: ...
         def ClearField(
             self,
             field_name: typing_extensions.Literal[
+                "_format",
+                b"_format",
                 "_schema",
                 b"_schema",
                 "format",
@@ -647,6 +662,11 @@ class Read(google.protobuf.message.Message):
                 b"schema",
             ],
         ) -> None: ...
+        @typing.overload
+        def WhichOneof(
+            self, oneof_group: typing_extensions.Literal["_format", b"_format"]
+        ) -> typing_extensions.Literal["format"] | None: ...
+        @typing.overload
         def WhichOneof(
             self, oneof_group: typing_extensions.Literal["_schema", b"_schema"]
         ) -> typing_extensions.Literal["schema"] | None: ...
diff --git a/python/pyspark/sql/connect/readwriter.py b/python/pyspark/sql/connect/readwriter.py
index 292e58b3552f8..9c9c79cb6eb4a 100644
--- a/python/pyspark/sql/connect/readwriter.py
+++ b/python/pyspark/sql/connect/readwriter.py
@@ -63,7 +63,7 @@ class DataFrameReader(OptionUtils):
 
     def __init__(self, client: "SparkSession"):
         self._client = client
-        self._format = ""
+        self._format: Optional[str] = None
         self._schema = ""
         self._options: Dict[str, str] = {}
 
diff --git a/python/pyspark/sql/tests/connect/test_parity_readwriter.py b/python/pyspark/sql/tests/connect/test_parity_readwriter.py
index bf77043ef3862..2fa3f79a92fb4 100644
--- a/python/pyspark/sql/tests/connect/test_parity_readwriter.py
+++ b/python/pyspark/sql/tests/connect/test_parity_readwriter.py
@@ -22,15 +22,7 @@
 
 
 class ReadwriterParityTests(ReadwriterTestsMixin, ReusedConnectTestCase):
-    # TODO(SPARK-41834): Implement SparkSession.conf
-    @unittest.skip("Fails in Spark Connect, should enable.")
-    def test_save_and_load(self):
-        super().test_save_and_load()
-
-    # TODO(SPARK-41834): Implement SparkSession.conf
-    @unittest.skip("Fails in Spark Connect, should enable.")
-    def test_save_and_load_builder(self):
-        super().test_save_and_load_builder()
+    pass
 
 
 class ReadwriterV2ParityTests(ReadwriterV2TestsMixin, ReusedConnectTestCase):
diff --git a/python/pyspark/sql/tests/test_readwriter.py b/python/pyspark/sql/tests/test_readwriter.py
index 7f9b5e61051d7..21c66284ace5f 100644
--- a/python/pyspark/sql/tests/test_readwriter.py
+++ b/python/pyspark/sql/tests/test_readwriter.py
@@ -31,75 +31,77 @@ def test_save_and_load(self):
         df = self.df
         tmpPath = tempfile.mkdtemp()
         shutil.rmtree(tmpPath)
-        df.write.json(tmpPath)
-        actual = self.spark.read.json(tmpPath)
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-
-        schema = StructType([StructField("value", StringType(), True)])
-        actual = self.spark.read.json(tmpPath, schema)
-        self.assertEqual(sorted(df.select("value").collect()), sorted(actual.collect()))
-
-        df.write.json(tmpPath, "overwrite")
-        actual = self.spark.read.json(tmpPath)
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-
-        df.write.save(
-            format="json",
-            mode="overwrite",
-            path=tmpPath,
-            noUse="this options will not be used in save.",
-        )
-        actual = self.spark.read.load(
-            format="json", path=tmpPath, noUse="this options will not be used in load."
-        )
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-
-        defaultDataSourceName = self.spark.conf.get(
-            "spark.sql.sources.default", "org.apache.spark.sql.parquet"
-        )
-        self.spark.sql("SET spark.sql.sources.default=org.apache.spark.sql.json")
-        actual = self.spark.read.load(path=tmpPath)
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-        self.spark.sql("SET spark.sql.sources.default=" + defaultDataSourceName)
+        try:
+            df.write.json(tmpPath)
+            actual = self.spark.read.json(tmpPath)
+            self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+
+            schema = StructType([StructField("value", StringType(), True)])
+            actual = self.spark.read.json(tmpPath, schema)
+            self.assertEqual(sorted(df.select("value").collect()), sorted(actual.collect()))
+
+            df.write.json(tmpPath, "overwrite")
+            actual = self.spark.read.json(tmpPath)
+            self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+
+            df.write.save(
+                format="json",
+                mode="overwrite",
+                path=tmpPath,
+                noUse="this options will not be used in save.",
+            )
+            actual = self.spark.read.load(
+                format="json", path=tmpPath, noUse="this options will not be used in load."
+            )
+            self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
 
-        csvpath = os.path.join(tempfile.mkdtemp(), "data")
-        df.write.option("quote", None).format("csv").save(csvpath)
+            try:
+                self.spark.sql("SET spark.sql.sources.default=org.apache.spark.sql.json").collect()
+                actual = self.spark.read.load(path=tmpPath)
+                self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+            finally:
+                self.spark.sql("RESET spark.sql.sources.default").collect()
 
-        shutil.rmtree(tmpPath)
+            csvpath = os.path.join(tempfile.mkdtemp(), "data")
+            df.write.option("quote", None).format("csv").save(csvpath)
+        finally:
+            shutil.rmtree(tmpPath)
 
     def test_save_and_load_builder(self):
         df = self.df
         tmpPath = tempfile.mkdtemp()
         shutil.rmtree(tmpPath)
-        df.write.json(tmpPath)
-        actual = self.spark.read.json(tmpPath)
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-
-        schema = StructType([StructField("value", StringType(), True)])
-        actual = self.spark.read.json(tmpPath, schema)
-        self.assertEqual(sorted(df.select("value").collect()), sorted(actual.collect()))
-
-        df.write.mode("overwrite").json(tmpPath)
-        actual = self.spark.read.json(tmpPath)
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-
-        df.write.mode("overwrite").options(noUse="this options will not be used in save.").option(
-            "noUse", "this option will not be used in save."
-        ).format("json").save(path=tmpPath)
-        actual = self.spark.read.format("json").load(
-            path=tmpPath, noUse="this options will not be used in load."
-        )
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-
-        defaultDataSourceName = self.spark.conf.get(
-            "spark.sql.sources.default", "org.apache.spark.sql.parquet"
-        )
-        self.spark.sql("SET spark.sql.sources.default=org.apache.spark.sql.json")
-        actual = self.spark.read.load(path=tmpPath)
-        self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
-        self.spark.sql("SET spark.sql.sources.default=" + defaultDataSourceName)
-
-        shutil.rmtree(tmpPath)
+        try:
+            df.write.json(tmpPath)
+            actual = self.spark.read.json(tmpPath)
+            self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+
+            schema = StructType([StructField("value", StringType(), True)])
+            actual = self.spark.read.json(tmpPath, schema)
+            self.assertEqual(sorted(df.select("value").collect()), sorted(actual.collect()))
+
+            df.write.mode("overwrite").json(tmpPath)
+            actual = self.spark.read.json(tmpPath)
+            self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+
+            df.write.mode("overwrite").options(
+                noUse="this options will not be used in save."
+            ).option("noUse", "this option will not be used in save.").format("json").save(
+                path=tmpPath
+            )
+            actual = self.spark.read.format("json").load(
+                path=tmpPath, noUse="this options will not be used in load."
+            )
+            self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+
+            try:
+                self.spark.sql("SET spark.sql.sources.default=org.apache.spark.sql.json").collect()
+                actual = self.spark.read.load(path=tmpPath)
+                self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
+            finally:
+                self.spark.sql("RESET spark.sql.sources.default").collect()
+        finally:
+            shutil.rmtree(tmpPath)
 
     def test_bucketed_write(self):
         data = [