[SPARK-43009][SQL] Parameterized sql() with Any constants

### What changes were proposed in this pull request?
In the PR, I propose to change API of parameterized SQL, and replace type of argument values from `string` to `Any` in Scala/Java/Python and `Expression.Literal` in protobuf API. Language API can accept `Any` objects from which it is possible to construct literal expressions.

#### Scala/Java:

```scala
  def sql(sqlText: String, args: Map[String, Any]): DataFrame
```
values of the `args` map are wrapped by the `lit()` function which leaves `Column` as is and creates a literal from other Java/Scala objects (for more details see the `Scala` tab at https://spark.apache.org/docs/latest/sql-ref-datatypes.html).

#### Python:

```python
def sql(self, sqlQuery: str, args: Optional[Dict[str, Any]] = None, **kwargs: Any) -> DataFrame:
```
Similarly to Scala/Java `sql`, Python's `sql()` accepts Python objects as values of the `args` dictionary (see more details about acceptable Python objects at https://spark.apache.org/docs/latest/sql-ref-datatypes.html). `sql()` converts dictionary values to `Column` literal expressions by `lit()`.

#### Protobuf:

```proto
message SqlCommand {
  // (Required) SQL Query.
  string sql = 1;

  // (Optional) A map of parameter names to literal expressions.
  map<string, Expression.Literal> args = 2;
}
```

For example:
```scala
scala> val sqlText = """SELECT s FROM VALUES ('Jeff /*__*/ Green'), ('E\'Twaun Moore') AS t(s) WHERE s = :player_name"""
sqlText: String = SELECT s FROM VALUES ('Jeff /*__*/ Green'), ('E\'Twaun Moore') AS t(s) WHERE s = :player_name

scala> sql(sqlText, args = Map("player_name" -> lit("E'Twaun Moore"))).show(false)
+-------------+
|s            |
+-------------+
|E'Twaun Moore|
+-------------+
```

### Why are the changes needed?
The current implementation the parameterized `sql()` requires arguments as string values parsed to SQL literal expressions that causes the following issues:
1. SQL comments are skipped while parsing, so, some fragments of input might be skipped. For example, `'Europe -- Amsterdam'`. In this case, `-- Amsterdam` is excluded from the input.
2. Special chars in string values must be escaped, for instance `'E\'Twaun Moore'`

### Does this PR introduce _any_ user-facing change?
No since the parameterized SQL feature #38864 hasn't been released yet.

### How was this patch tested?
By running the affected tests:
```
$ build/sbt "test:testOnly *ParametersSuite"
$ python/run-tests --parallelism=1 --testnames 'pyspark.sql.tests.connect.test_connect_basic SparkConnectBasicTests.test_sql_with_args'
$ python/run-tests --parallelism=1 --testnames 'pyspark.sql.session SparkSession.sql'
```

Closes #40623 from MaxGekk/parameterized-sql-any.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>

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

@@ -35,6 +35,7 @@ import org.apache.spark.sql.catalyst.encoders.{AgnosticEncoder, RowEncoder}
 import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.{BoxedLongEncoder, UnboundRowEncoder}
 import org.apache.spark.sql.connect.client.{SparkConnectClient, SparkResult}
 import org.apache.spark.sql.connect.client.util.{Cleaner, ConvertToArrow}
+import org.apache.spark.sql.connect.common.LiteralValueProtoConverter.toLiteralProto
 import org.apache.spark.sql.internal.CatalogImpl
 import org.apache.spark.sql.types.StructType
 
@@ -215,15 +216,16 @@ class SparkSession private[sql] (
    * @param sqlText
    *   A SQL statement with named parameters to execute.
    * @param args
-   *   A map of parameter names to string values that are parsed as SQL literal expressions. For
-   *   example, map keys: "rank", "name", "birthdate"; map values: "1", "'Steven'",
-   *   "DATE'2023-03-21'". The fragments of string values belonged to SQL comments are skipped
-   *   while parsing.
+   *   A map of parameter names to Java/Scala objects that can be converted to SQL literal
+   *   expressions. See <a href="https://spark.apache.org/docs/latest/sql-ref-datatypes.html">
+   *   Supported Data Types</a> for supported value types in Scala/Java. For example, map keys:
+   *   "rank", "name", "birthdate"; map values: 1, "Steven", LocalDate.of(2023, 4, 2). Map value
+   *   can be also a `Column` of literal expression, in that case it is taken as is.
    *
    * @since 3.4.0
    */
   @Experimental
-  def sql(sqlText: String, args: Map[String, String]): DataFrame = {
+  def sql(sqlText: String, args: Map[String, Any]): DataFrame = {
     sql(sqlText, args.asJava)
   }
 
@@ -234,19 +236,24 @@ class SparkSession private[sql] (
    * @param sqlText
    *   A SQL statement with named parameters to execute.
    * @param args
-   *   A map of parameter names to string values that are parsed as SQL literal expressions. For
-   *   example, map keys: "rank", "name", "birthdate"; map values: "1", "'Steven'",
-   *   "DATE'2023-03-21'". The fragments of string values belonged to SQL comments are skipped
-   *   while parsing.
+   *   A map of parameter names to Java/Scala objects that can be converted to SQL literal
+   *   expressions. See <a href="https://spark.apache.org/docs/latest/sql-ref-datatypes.html">
+   *   Supported Data Types</a> for supported value types in Scala/Java. For example, map keys:
+   *   "rank", "name", "birthdate"; map values: 1, "Steven", LocalDate.of(2023, 4, 2). Map value
+   *   can be also a `Column` of literal expression, in that case it is taken as is.
    *
    * @since 3.4.0
    */
   @Experimental
-  def sql(sqlText: String, args: java.util.Map[String, String]): DataFrame = newDataFrame {
+  def sql(sqlText: String, args: java.util.Map[String, Any]): DataFrame = newDataFrame {
     builder =>
       // Send the SQL once to the server and then check the output.
       val cmd = newCommand(b =>
-        b.setSqlCommand(proto.SqlCommand.newBuilder().setSql(sqlText).putAllArgs(args)))
+        b.setSqlCommand(
+          proto.SqlCommand
+            .newBuilder()
+            .setSql(sqlText)
+            .putAllArgs(args.asScala.mapValues(toLiteralProto).toMap.asJava)))
       val plan = proto.Plan.newBuilder().setCommand(cmd)
       val responseIter = client.execute(plan.build())
 

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

@@ -53,11 +53,8 @@ message SqlCommand {
   // (Required) SQL Query.
   string sql = 1;
 
-  // (Optional) A map of parameter names to string values that are parsed as
-  // SQL literal expressions. For example, map keys: "rank", "name", "birthdate";
-  // map values: "1", "'Steven'", "DATE'2023-03-21'". The fragments of string values
-  // belonged to SQL comments are skipped while parsing.
-  map<string, string> args = 2;
+  // (Optional) A map of parameter names to literal expressions.
+  map<string, Expression.Literal> args = 2;
 }
 
 // A command that can create DataFrame global temp view or local temp view.

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

@@ -108,11 +108,8 @@ message SQL {
   // (Required) The SQL query.
   string query = 1;
 
-  // (Optional) A map of parameter names to string values that are parsed as
-  // SQL literal expressions. For example, map keys: "rank", "name", "birthdate";
-  // map values: "1", "'Steven'", "DATE'2023-03-21'". The fragments of string values
-  // belonged to SQL comments are skipped while parsing.
-  map<string, string> args = 2;
+  // (Optional) A map of parameter names to literal expressions.
+  map<string, Expression.Literal> args = 2;
 }
 
 // Relation that reads from a file / table or other data source. Does not have additional

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

@@ -214,11 +214,11 @@ class SparkConnectPlanner(val session: SparkSession) {
   }
 
   private def transformSql(sql: proto.SQL): LogicalPlan = {
-    val args = sql.getArgsMap.asScala.toMap
+    val args = sql.getArgsMap
     val parser = session.sessionState.sqlParser
     val parsedPlan = parser.parsePlan(sql.getQuery)
-    if (args.nonEmpty) {
-      ParameterizedQuery(parsedPlan, args.mapValues(parser.parseExpression).toMap)
+    if (!args.isEmpty) {
+      ParameterizedQuery(parsedPlan, args.asScala.mapValues(transformLiteral).toMap)
     } else {
       parsedPlan
     }
@@ -1690,7 +1690,9 @@ class SparkConnectPlanner(val session: SparkSession) {
       sessionId: String,
       responseObserver: StreamObserver[ExecutePlanResponse]): Unit = {
     // Eagerly execute commands of the provided SQL string.
-    val df = session.sql(getSqlCommand.getSql, getSqlCommand.getArgsMap)
+    val df = session.sql(
+      getSqlCommand.getSql,
+      getSqlCommand.getArgsMap.asScala.mapValues(transformLiteral).toMap)
     // Check if commands have been executed.
     val isCommand = df.queryExecution.commandExecuted.isInstanceOf[CommandResult]
     val rows = df.logicalPlan match {

python/pyspark/sql/connect/plan.py

@@ -945,13 +945,12 @@ def plan(self, session: "SparkConnectClient") -> proto.Relation:
 
 
 class SQL(LogicalPlan):
-    def __init__(self, query: str, args: Optional[Dict[str, str]] = None) -> None:
+    def __init__(self, query: str, args: Optional[Dict[str, Any]] = None) -> None:
         super().__init__(None)
 
         if args is not None:
             for k, v in args.items():
                 assert isinstance(k, str)
-                assert isinstance(v, str)
 
         self._query = query
         self._args = args
@@ -962,7 +961,7 @@ def plan(self, session: "SparkConnectClient") -> proto.Relation:
 
         if self._args is not None and len(self._args) > 0:
             for k, v in self._args.items():
-                plan.sql.args[k] = v
+                plan.sql.args[k].CopyFrom(LiteralExpression._from_value(v).to_plan(session).literal)
 
         return plan
 
@@ -971,7 +970,9 @@ def command(self, session: "SparkConnectClient") -> proto.Command:
         cmd.sql_command.sql = self._query
         if self._args is not None and len(self._args) > 0:
             for k, v in self._args.items():
-                cmd.sql_command.args[k] = v
+                cmd.sql_command.args[k].CopyFrom(
+                    LiteralExpression._from_value(v).to_plan(session).literal
+                )
         return cmd
 
 

python/pyspark/sql/connect/proto/commands_pb2.py

@@ -35,7 +35,7 @@
 
 
 DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(
-    b'\n\x1cspark/connect/commands.proto\x12\rspark.connect\x1a\x19google/protobuf/any.proto\x1a\x1fspark/connect/expressions.proto\x1a\x1dspark/connect/relations.proto"\xe9\x03\n\x07\x43ommand\x12]\n\x11register_function\x18\x01 \x01(\x0b\x32..spark.connect.CommonInlineUserDefinedFunctionH\x00R\x10registerFunction\x12H\n\x0fwrite_operation\x18\x02 \x01(\x0b\x32\x1d.spark.connect.WriteOperationH\x00R\x0ewriteOperation\x12_\n\x15\x63reate_dataframe_view\x18\x03 \x01(\x0b\x32).spark.connect.CreateDataFrameViewCommandH\x00R\x13\x63reateDataframeView\x12O\n\x12write_operation_v2\x18\x04 \x01(\x0b\x32\x1f.spark.connect.WriteOperationV2H\x00R\x10writeOperationV2\x12<\n\x0bsql_command\x18\x05 \x01(\x0b\x32\x19.spark.connect.SqlCommandH\x00R\nsqlCommand\x12\x35\n\textension\x18\xe7\x07 \x01(\x0b\x32\x14.google.protobuf.AnyH\x00R\textensionB\x0e\n\x0c\x63ommand_type"\x90\x01\n\nSqlCommand\x12\x10\n\x03sql\x18\x01 \x01(\tR\x03sql\x12\x37\n\x04\x61rgs\x18\x02 \x03(\x0b\x32#.spark.connect.SqlCommand.ArgsEntryR\x04\x61rgs\x1a\x37\n\tArgsEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01"\x96\x01\n\x1a\x43reateDataFrameViewCommand\x12-\n\x05input\x18\x01 \x01(\x0b\x32\x17.spark.connect.RelationR\x05input\x12\x12\n\x04name\x18\x02 \x01(\tR\x04name\x12\x1b\n\tis_global\x18\x03 \x01(\x08R\x08isGlobal\x12\x18\n\x07replace\x18\x04 \x01(\x08R\x07replace"\x9b\x08\n\x0eWriteOperation\x12-\n\x05input\x18\x01 \x01(\x0b\x32\x17.spark.connect.RelationR\x05input\x12\x1b\n\x06source\x18\x02 \x01(\tH\x01R\x06source\x88\x01\x01\x12\x14\n\x04path\x18\x03 \x01(\tH\x00R\x04path\x12?\n\x05table\x18\x04 \x01(\x0b\x32\'.spark.connect.WriteOperation.SaveTableH\x00R\x05table\x12:\n\x04mode\x18\x05 \x01(\x0e\x32&.spark.connect.WriteOperation.SaveModeR\x04mode\x12*\n\x11sort_column_names\x18\x06 \x03(\tR\x0fsortColumnNames\x12\x31\n\x14partitioning_columns\x18\x07 \x03(\tR\x13partitioningColumns\x12\x43\n\tbucket_by\x18\x08 \x01(\x0b\x32&.spark.connect.WriteOperation.BucketByR\x08\x62ucketBy\x12\x44\n\x07options\x18\t \x03(\x0b\x32*.spark.connect.WriteOperation.OptionsEntryR\x07options\x1a:\n\x0cOptionsEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01\x1a\x82\x02\n\tSaveTable\x12\x1d\n\ntable_name\x18\x01 \x01(\tR\ttableName\x12X\n\x0bsave_method\x18\x02 \x01(\x0e\x32\x37.spark.connect.WriteOperation.SaveTable.TableSaveMethodR\nsaveMethod"|\n\x0fTableSaveMethod\x12!\n\x1dTABLE_SAVE_METHOD_UNSPECIFIED\x10\x00\x12#\n\x1fTABLE_SAVE_METHOD_SAVE_AS_TABLE\x10\x01\x12!\n\x1dTABLE_SAVE_METHOD_INSERT_INTO\x10\x02\x1a[\n\x08\x42ucketBy\x12.\n\x13\x62ucket_column_names\x18\x01 \x03(\tR\x11\x62ucketColumnNames\x12\x1f\n\x0bnum_buckets\x18\x02 \x01(\x05R\nnumBuckets"\x89\x01\n\x08SaveMode\x12\x19\n\x15SAVE_MODE_UNSPECIFIED\x10\x00\x12\x14\n\x10SAVE_MODE_APPEND\x10\x01\x12\x17\n\x13SAVE_MODE_OVERWRITE\x10\x02\x12\x1d\n\x19SAVE_MODE_ERROR_IF_EXISTS\x10\x03\x12\x14\n\x10SAVE_MODE_IGNORE\x10\x04\x42\x0b\n\tsave_typeB\t\n\x07_source"\xad\x06\n\x10WriteOperationV2\x12-\n\x05input\x18\x01 \x01(\x0b\x32\x17.spark.connect.RelationR\x05input\x12\x1d\n\ntable_name\x18\x02 \x01(\tR\ttableName\x12\x1f\n\x08provider\x18\x03 \x01(\tH\x00R\x08provider\x88\x01\x01\x12L\n\x14partitioning_columns\x18\x04 \x03(\x0b\x32\x19.spark.connect.ExpressionR\x13partitioningColumns\x12\x46\n\x07options\x18\x05 \x03(\x0b\x32,.spark.connect.WriteOperationV2.OptionsEntryR\x07options\x12_\n\x10table_properties\x18\x06 \x03(\x0b\x32\x34.spark.connect.WriteOperationV2.TablePropertiesEntryR\x0ftableProperties\x12\x38\n\x04mode\x18\x07 \x01(\x0e\x32$.spark.connect.WriteOperationV2.ModeR\x04mode\x12J\n\x13overwrite_condition\x18\x08 \x01(\x0b\x32\x19.spark.connect.ExpressionR\x12overwriteCondition\x1a:\n\x0cOptionsEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01\x1a\x42\n\x14TablePropertiesEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01"\x9f\x01\n\x04Mode\x12\x14\n\x10MODE_UNSPECIFIED\x10\x00\x12\x0f\n\x0bMODE_CREATE\x10\x01\x12\x12\n\x0eMODE_OVERWRITE\x10\x02\x12\x1d\n\x19MODE_OVERWRITE_PARTITIONS\x10\x03\x12\x0f\n\x0bMODE_APPEND\x10\x04\x12\x10\n\x0cMODE_REPLACE\x10\x05\x12\x1a\n\x16MODE_CREATE_OR_REPLACE\x10\x06\x42\x0b\n\t_providerB"\n\x1eorg.apache.spark.connect.protoP\x01\x62\x06proto3'
+    b'\n\x1cspark/connect/commands.proto\x12\rspark.connect\x1a\x19google/protobuf/any.proto\x1a\x1fspark/connect/expressions.proto\x1a\x1dspark/connect/relations.proto"\xe9\x03\n\x07\x43ommand\x12]\n\x11register_function\x18\x01 \x01(\x0b\x32..spark.connect.CommonInlineUserDefinedFunctionH\x00R\x10registerFunction\x12H\n\x0fwrite_operation\x18\x02 \x01(\x0b\x32\x1d.spark.connect.WriteOperationH\x00R\x0ewriteOperation\x12_\n\x15\x63reate_dataframe_view\x18\x03 \x01(\x0b\x32).spark.connect.CreateDataFrameViewCommandH\x00R\x13\x63reateDataframeView\x12O\n\x12write_operation_v2\x18\x04 \x01(\x0b\x32\x1f.spark.connect.WriteOperationV2H\x00R\x10writeOperationV2\x12<\n\x0bsql_command\x18\x05 \x01(\x0b\x32\x19.spark.connect.SqlCommandH\x00R\nsqlCommand\x12\x35\n\textension\x18\xe7\x07 \x01(\x0b\x32\x14.google.protobuf.AnyH\x00R\textensionB\x0e\n\x0c\x63ommand_type"\xb3\x01\n\nSqlCommand\x12\x10\n\x03sql\x18\x01 \x01(\tR\x03sql\x12\x37\n\x04\x61rgs\x18\x02 \x03(\x0b\x32#.spark.connect.SqlCommand.ArgsEntryR\x04\x61rgs\x1aZ\n\tArgsEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x37\n\x05value\x18\x02 \x01(\x0b\x32!.spark.connect.Expression.LiteralR\x05value:\x02\x38\x01"\x96\x01\n\x1a\x43reateDataFrameViewCommand\x12-\n\x05input\x18\x01 \x01(\x0b\x32\x17.spark.connect.RelationR\x05input\x12\x12\n\x04name\x18\x02 \x01(\tR\x04name\x12\x1b\n\tis_global\x18\x03 \x01(\x08R\x08isGlobal\x12\x18\n\x07replace\x18\x04 \x01(\x08R\x07replace"\x9b\x08\n\x0eWriteOperation\x12-\n\x05input\x18\x01 \x01(\x0b\x32\x17.spark.connect.RelationR\x05input\x12\x1b\n\x06source\x18\x02 \x01(\tH\x01R\x06source\x88\x01\x01\x12\x14\n\x04path\x18\x03 \x01(\tH\x00R\x04path\x12?\n\x05table\x18\x04 \x01(\x0b\x32\'.spark.connect.WriteOperation.SaveTableH\x00R\x05table\x12:\n\x04mode\x18\x05 \x01(\x0e\x32&.spark.connect.WriteOperation.SaveModeR\x04mode\x12*\n\x11sort_column_names\x18\x06 \x03(\tR\x0fsortColumnNames\x12\x31\n\x14partitioning_columns\x18\x07 \x03(\tR\x13partitioningColumns\x12\x43\n\tbucket_by\x18\x08 \x01(\x0b\x32&.spark.connect.WriteOperation.BucketByR\x08\x62ucketBy\x12\x44\n\x07options\x18\t \x03(\x0b\x32*.spark.connect.WriteOperation.OptionsEntryR\x07options\x1a:\n\x0cOptionsEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01\x1a\x82\x02\n\tSaveTable\x12\x1d\n\ntable_name\x18\x01 \x01(\tR\ttableName\x12X\n\x0bsave_method\x18\x02 \x01(\x0e\x32\x37.spark.connect.WriteOperation.SaveTable.TableSaveMethodR\nsaveMethod"|\n\x0fTableSaveMethod\x12!\n\x1dTABLE_SAVE_METHOD_UNSPECIFIED\x10\x00\x12#\n\x1fTABLE_SAVE_METHOD_SAVE_AS_TABLE\x10\x01\x12!\n\x1dTABLE_SAVE_METHOD_INSERT_INTO\x10\x02\x1a[\n\x08\x42ucketBy\x12.\n\x13\x62ucket_column_names\x18\x01 \x03(\tR\x11\x62ucketColumnNames\x12\x1f\n\x0bnum_buckets\x18\x02 \x01(\x05R\nnumBuckets"\x89\x01\n\x08SaveMode\x12\x19\n\x15SAVE_MODE_UNSPECIFIED\x10\x00\x12\x14\n\x10SAVE_MODE_APPEND\x10\x01\x12\x17\n\x13SAVE_MODE_OVERWRITE\x10\x02\x12\x1d\n\x19SAVE_MODE_ERROR_IF_EXISTS\x10\x03\x12\x14\n\x10SAVE_MODE_IGNORE\x10\x04\x42\x0b\n\tsave_typeB\t\n\x07_source"\xad\x06\n\x10WriteOperationV2\x12-\n\x05input\x18\x01 \x01(\x0b\x32\x17.spark.connect.RelationR\x05input\x12\x1d\n\ntable_name\x18\x02 \x01(\tR\ttableName\x12\x1f\n\x08provider\x18\x03 \x01(\tH\x00R\x08provider\x88\x01\x01\x12L\n\x14partitioning_columns\x18\x04 \x03(\x0b\x32\x19.spark.connect.ExpressionR\x13partitioningColumns\x12\x46\n\x07options\x18\x05 \x03(\x0b\x32,.spark.connect.WriteOperationV2.OptionsEntryR\x07options\x12_\n\x10table_properties\x18\x06 \x03(\x0b\x32\x34.spark.connect.WriteOperationV2.TablePropertiesEntryR\x0ftableProperties\x12\x38\n\x04mode\x18\x07 \x01(\x0e\x32$.spark.connect.WriteOperationV2.ModeR\x04mode\x12J\n\x13overwrite_condition\x18\x08 \x01(\x0b\x32\x19.spark.connect.ExpressionR\x12overwriteCondition\x1a:\n\x0cOptionsEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01\x1a\x42\n\x14TablePropertiesEntry\x12\x10\n\x03key\x18\x01 \x01(\tR\x03key\x12\x14\n\x05value\x18\x02 \x01(\tR\x05value:\x02\x38\x01"\x9f\x01\n\x04Mode\x12\x14\n\x10MODE_UNSPECIFIED\x10\x00\x12\x0f\n\x0bMODE_CREATE\x10\x01\x12\x12\n\x0eMODE_OVERWRITE\x10\x02\x12\x1d\n\x19MODE_OVERWRITE_PARTITIONS\x10\x03\x12\x0f\n\x0bMODE_APPEND\x10\x04\x12\x10\n\x0cMODE_REPLACE\x10\x05\x12\x1a\n\x16MODE_CREATE_OR_REPLACE\x10\x06\x42\x0b\n\t_providerB"\n\x1eorg.apache.spark.connect.protoP\x01\x62\x06proto3'
 )
 
 
@@ -187,29 +187,29 @@
     _COMMAND._serialized_start = 139
     _COMMAND._serialized_end = 628
     _SQLCOMMAND._serialized_start = 631
-    _SQLCOMMAND._serialized_end = 775
+    _SQLCOMMAND._serialized_end = 810
     _SQLCOMMAND_ARGSENTRY._serialized_start = 720
-    _SQLCOMMAND_ARGSENTRY._serialized_end = 775
-    _CREATEDATAFRAMEVIEWCOMMAND._serialized_start = 778
-    _CREATEDATAFRAMEVIEWCOMMAND._serialized_end = 928
-    _WRITEOPERATION._serialized_start = 931
-    _WRITEOPERATION._serialized_end = 1982
-    _WRITEOPERATION_OPTIONSENTRY._serialized_start = 1406
-    _WRITEOPERATION_OPTIONSENTRY._serialized_end = 1464
-    _WRITEOPERATION_SAVETABLE._serialized_start = 1467
-    _WRITEOPERATION_SAVETABLE._serialized_end = 1725
-    _WRITEOPERATION_SAVETABLE_TABLESAVEMETHOD._serialized_start = 1601
-    _WRITEOPERATION_SAVETABLE_TABLESAVEMETHOD._serialized_end = 1725
-    _WRITEOPERATION_BUCKETBY._serialized_start = 1727
-    _WRITEOPERATION_BUCKETBY._serialized_end = 1818
-    _WRITEOPERATION_SAVEMODE._serialized_start = 1821
-    _WRITEOPERATION_SAVEMODE._serialized_end = 1958
-    _WRITEOPERATIONV2._serialized_start = 1985
-    _WRITEOPERATIONV2._serialized_end = 2798
-    _WRITEOPERATIONV2_OPTIONSENTRY._serialized_start = 1406
-    _WRITEOPERATIONV2_OPTIONSENTRY._serialized_end = 1464
-    _WRITEOPERATIONV2_TABLEPROPERTIESENTRY._serialized_start = 2557
-    _WRITEOPERATIONV2_TABLEPROPERTIESENTRY._serialized_end = 2623
-    _WRITEOPERATIONV2_MODE._serialized_start = 2626
-    _WRITEOPERATIONV2_MODE._serialized_end = 2785
+    _SQLCOMMAND_ARGSENTRY._serialized_end = 810
+    _CREATEDATAFRAMEVIEWCOMMAND._serialized_start = 813
+    _CREATEDATAFRAMEVIEWCOMMAND._serialized_end = 963
+    _WRITEOPERATION._serialized_start = 966
+    _WRITEOPERATION._serialized_end = 2017
+    _WRITEOPERATION_OPTIONSENTRY._serialized_start = 1441
+    _WRITEOPERATION_OPTIONSENTRY._serialized_end = 1499
+    _WRITEOPERATION_SAVETABLE._serialized_start = 1502
+    _WRITEOPERATION_SAVETABLE._serialized_end = 1760
+    _WRITEOPERATION_SAVETABLE_TABLESAVEMETHOD._serialized_start = 1636
+    _WRITEOPERATION_SAVETABLE_TABLESAVEMETHOD._serialized_end = 1760
+    _WRITEOPERATION_BUCKETBY._serialized_start = 1762
+    _WRITEOPERATION_BUCKETBY._serialized_end = 1853
+    _WRITEOPERATION_SAVEMODE._serialized_start = 1856
+    _WRITEOPERATION_SAVEMODE._serialized_end = 1993
+    _WRITEOPERATIONV2._serialized_start = 2020
+    _WRITEOPERATIONV2._serialized_end = 2833
+    _WRITEOPERATIONV2_OPTIONSENTRY._serialized_start = 1441
+    _WRITEOPERATIONV2_OPTIONSENTRY._serialized_end = 1499
+    _WRITEOPERATIONV2_TABLEPROPERTIESENTRY._serialized_start = 2592
+    _WRITEOPERATIONV2_TABLEPROPERTIESENTRY._serialized_end = 2658
+    _WRITEOPERATIONV2_MODE._serialized_start = 2661
+    _WRITEOPERATIONV2_MODE._serialized_end = 2820
 # @@protoc_insertion_point(module_scope)