init

empty

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/Dataset.scala

@@ -2276,7 +2276,13 @@ class Dataset[T] private[sql] (
     sparkSession.newDataFrame { builder =>
       builder.getWithColumnsRenamedBuilder
         .setInput(plan.getRoot)
-        .putAllRenameColumnsMap(colsMap)
+        .addAllRenames(colsMap.asScala.toSeq.map { case (colName, newColName) =>
+          proto.WithColumnsRenamed.Rename
+            .newBuilder()
+            .setColName(colName)
+            .setNewColName(newColName)
+            .build()
+        }.asJava)
     }
   }
 

connector/connect/common/src/main/protobuf/spark/connect/relations.proto

@@ -776,13 +776,23 @@ message WithColumnsRenamed {
   Relation input = 1;
 
 
-  // (Required)
+  // (Optional)
   //
   // Renaming column names of input relation from A to B where A is the map key
   // and B is the map value. This is a no-op if schema doesn't contain any A. It
   // does not require that all input relation column names to present as keys.
   // duplicated B are not allowed.
-  map<string, string> rename_columns_map = 2;
+  map<string, string> rename_columns_map = 2 [deprecated=true];
+
+  repeated Rename renames = 3;
+
+  message Rename {
+    // (Required) The existing column name.
+    string col_name = 1;
+
+    // (Required) The new column name.
+    string new_col_name = 2;
+  }
 }
 
 // Adding columns or replacing the existing columns that have the same names.

connector/connect/common/src/test/resources/query-tests/queries/withColumnRenamed_java_map.json

@@ -11,9 +11,12 @@
         "schema": "struct\u003cid:bigint,a:int,b:double\u003e"
       }
     },
-    "renameColumnsMap": {
-      "b": "bravo",
-      "id": "nid"
-    }
+    "renames": [{
+      "colName": "b",
+      "newColName": "bravo"
+    }, {
+      "colName": "id",
+      "newColName": "nid"
+    }]
   }
 }

connector/connect/common/src/test/resources/query-tests/queries/withColumnRenamed_scala_map.json

@@ -11,9 +11,12 @@
         "schema": "struct\u003cid:bigint,a:int,b:double\u003e"
       }
     },
-    "renameColumnsMap": {
-      "a": "alpha",
-      "b": "beta"
-    }
+    "renames": [{
+      "colName": "a",
+      "newColName": "alpha"
+    }, {
+      "colName": "b",
+      "newColName": "beta"
+    }]
   }
 }

connector/connect/common/src/test/resources/query-tests/queries/withColumnRenamed_single.json

@@ -11,8 +11,9 @@
         "schema": "struct\u003cid:bigint,a:int,b:double\u003e"
       }
     },
-    "renameColumnsMap": {
-      "id": "nid"
-    }
+    "renames": [{
+      "colName": "id",
+      "newColName": "nid"
+    }]
   }
 }

connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala

@@ -981,10 +981,21 @@ class SparkConnectPlanner(
   }
 
   private def transformWithColumnsRenamed(rel: proto.WithColumnsRenamed): LogicalPlan = {
-    Dataset
-      .ofRows(session, transformRelation(rel.getInput))
-      .withColumnsRenamed(rel.getRenameColumnsMapMap)
-      .logicalPlan
+    if (rel.getRenamesCount > 0) {
+      val (colNames, newColNames) = rel.getRenamesList.asScala.toSeq.map { rename =>
+        (rename.getColName, rename.getNewColName)
+      }.unzip
+      Dataset
+        .ofRows(session, transformRelation(rel.getInput))
+        .withColumnsRenamed(colNames, newColNames)
+        .logicalPlan
+    } else {
+      // for backward compatibility
+      Dataset
+        .ofRows(session, transformRelation(rel.getInput))
+        .withColumnsRenamed(rel.getRenameColumnsMapMap)
+        .logicalPlan
+    }
   }
 
   private def transformWithColumns(rel: proto.WithColumns): LogicalPlan = {

python/pyspark/sql/connect/plan.py

@@ -1265,8 +1265,12 @@ def plan(self, session: "SparkConnectClient") -> proto.Relation:
         assert self._child is not None
         plan = self._create_proto_relation()
         plan.with_columns_renamed.input.CopyFrom(self._child.plan(session))
-        for k, v in self._colsMap.items():
-            plan.with_columns_renamed.rename_columns_map[k] = v
+        if len(self._colsMap) > 0:
+            for k, v in self._colsMap.items():
+                rename = proto.WithColumnsRenamed.Rename()
+                rename.col_name = k
+                rename.new_col_name = v
+                plan.with_columns_renamed.renames.append(rename)
         return plan
 
 

python/pyspark/sql/connect/proto/relations_pb2.pyi

@@ -2788,35 +2788,65 @@ class WithColumnsRenamed(google.protobuf.message.Message):
             self, field_name: typing_extensions.Literal["key", b"key", "value", b"value"]
         ) -> None: ...
 
+    class Rename(google.protobuf.message.Message):
+        DESCRIPTOR: google.protobuf.descriptor.Descriptor
+
+        COL_NAME_FIELD_NUMBER: builtins.int
+        NEW_COL_NAME_FIELD_NUMBER: builtins.int
+        col_name: builtins.str
+        """(Required) The existing column name."""
+        new_col_name: builtins.str
+        """(Required) The new column name."""
+        def __init__(
+            self,
+            *,
+            col_name: builtins.str = ...,
+            new_col_name: builtins.str = ...,
+        ) -> None: ...
+        def ClearField(
+            self,
+            field_name: typing_extensions.Literal[
+                "col_name", b"col_name", "new_col_name", b"new_col_name"
+            ],
+        ) -> None: ...
+
     INPUT_FIELD_NUMBER: builtins.int
     RENAME_COLUMNS_MAP_FIELD_NUMBER: builtins.int
+    RENAMES_FIELD_NUMBER: builtins.int
     @property
     def input(self) -> global___Relation:
         """(Required) The input relation."""
     @property
     def rename_columns_map(
         self,
     ) -> google.protobuf.internal.containers.ScalarMap[builtins.str, builtins.str]:
-        """(Required)
+        """(Optional)
 
         Renaming column names of input relation from A to B where A is the map key
         and B is the map value. This is a no-op if schema doesn't contain any A. It
         does not require that all input relation column names to present as keys.
         duplicated B are not allowed.
         """
+    @property
+    def renames(
+        self,
+    ) -> google.protobuf.internal.containers.RepeatedCompositeFieldContainer[
+        global___WithColumnsRenamed.Rename
+    ]: ...
     def __init__(
         self,
         *,
         input: global___Relation | None = ...,
         rename_columns_map: collections.abc.Mapping[builtins.str, builtins.str] | None = ...,
+        renames: collections.abc.Iterable[global___WithColumnsRenamed.Rename] | None = ...,
     ) -> None: ...
     def HasField(
         self, field_name: typing_extensions.Literal["input", b"input"]
     ) -> builtins.bool: ...
     def ClearField(
         self,
         field_name: typing_extensions.Literal[
-            "input", b"input", "rename_columns_map", b"rename_columns_map"
+            "input", b"input", "rename_columns_map", b"rename_columns_map", "renames", b"renames"
         ],
     ) -> None: ...
 

python/pyspark/sql/tests/connect/test_parity_dataframe.py

@@ -77,11 +77,6 @@ def test_to_pandas_from_mixed_dataframe(self):
     def test_toDF_with_string(self):
         super().test_toDF_with_string()
 
-    # TODO(SPARK-46261): Python Client withColumnsRenamed should respect the dict ordering
-    @unittest.skip("Fails in Spark Connect, should enable.")
-    def test_ordering_of_with_columns_renamed(self):
-        super().test_ordering_of_with_columns_renamed()
-
 
 if __name__ == "__main__":
     import unittest

sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala

@@ -2926,7 +2926,7 @@ class Dataset[T] private[sql](
     withColumnsRenamed(colNames, newColNames)
   }
 
-  private def withColumnsRenamed(
+  private[spark] def withColumnsRenamed(
     colNames: Seq[String],
     newColNames: Seq[String]): DataFrame = withOrigin {
     require(colNames.size == newColNames.size,