[SPARK-55277][SQL] Add protobuf_funcs group for Protobuf SQL functions

Similar to how Avro functions have their own 'avro_funcs' group, Protobuf functions (from_protobuf, to_protobuf) should have their own 'protobuf_funcs' group instead of being grouped under 'misc_funcs'.

This improves consistency with how other format-specific functions are organized and makes the documentation clearer for users.

### What changes were proposed in this pull request?

- Move from_protobuf and to_protobuf from misc_funcs to protobuf_funcs
- Add protobuf_funcs to the groups set in gen-sql-functions-docs.py

### Why are the changes needed?

Consistency with avro_funcs, json_funcs, csv_funcs, xml_funcs groupings.

### Does this PR introduce _any_ user-facing change?

No functional changes. The only difference is in how functions are grouped in documentation.

### How was this patch tested?

Existing tests.

### Was this patch authored or co-authored using generative AI tooling?

Yes, GitHub Copilot was used to assist with this change.

Author: yaooqinn

sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/ExpressionInfo.java

@@ -48,8 +48,8 @@ public class ExpressionInfo {
             "bitwise_funcs", "collection_funcs", "predicate_funcs", "conditional_funcs",
             "conversion_funcs", "csv_funcs", "datetime_funcs", "generator_funcs", "hash_funcs",
             "json_funcs", "lambda_funcs", "map_funcs", "math_funcs", "misc_funcs",
-            "string_funcs", "struct_funcs", "window_funcs", "xml_funcs", "table_funcs",
-            "url_funcs", "variant_funcs", "vector_funcs", "st_funcs"));
+            "protobuf_funcs", "string_funcs", "struct_funcs", "window_funcs", "xml_funcs",
+            "table_funcs", "url_funcs", "variant_funcs", "vector_funcs", "st_funcs"));
 
     private static final Set<String> validSources =
             new HashSet<>(Arrays.asList("built-in", "hive", "python_udf", "scala_udf", "sql_udf",

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/toFromProtobufSqlFunctions.scala

@@ -58,7 +58,7 @@ import org.apache.spark.util.Utils
     To deserialize the data with a compatible and evolved schema, the expected Protobuf schema can be
     set via the corresponding option.
   """,
-  group = "misc_funcs",
+  group = "protobuf_funcs",
   since = "4.0.0"
 )
 // scalastyle:on line.size.limit
@@ -195,7 +195,7 @@ case class FromProtobuf(
       > SELECT _FUNC_(s, 'Person', '/path/to/descriptor.desc', map('emitDefaultValues', 'true')) IS NULL FROM (SELECT NULL AS s);
        [true]
   """,
-  group = "misc_funcs",
+  group = "protobuf_funcs",
   since = "4.0.0"
 )
 // scalastyle:on line.size.limit

sql/core/src/test/scala/org/apache/spark/sql/expressions/ExpressionInfoSuite.scala

@@ -59,8 +59,8 @@ class ExpressionInfoSuite extends SparkFunSuite with SharedSparkSession {
       "agg_funcs", "array_funcs", "avro_funcs", "binary_funcs", "bitwise_funcs", "collection_funcs",
       "predicate_funcs", "conditional_funcs", "conversion_funcs", "csv_funcs", "datetime_funcs",
       "generator_funcs", "hash_funcs", "json_funcs", "lambda_funcs", "map_funcs", "math_funcs",
-      "misc_funcs", "string_funcs", "struct_funcs", "window_funcs", "xml_funcs", "table_funcs",
-      "url_funcs", "variant_funcs", "vector_funcs", "st_funcs").sorted
+      "misc_funcs", "protobuf_funcs", "string_funcs", "struct_funcs", "window_funcs", "xml_funcs",
+      "table_funcs", "url_funcs", "variant_funcs", "vector_funcs", "st_funcs").sorted
     val invalidGroupName = "invalid_group_funcs"
     checkError(
       exception = intercept[SparkIllegalArgumentException] {

sql/gen-sql-functions-docs.py

@@ -36,7 +36,7 @@
     "bitwise_funcs", "conversion_funcs", "csv_funcs",
     "xml_funcs", "lambda_funcs", "collection_funcs",
     "url_funcs", "hash_funcs", "struct_funcs",
-    "table_funcs", "variant_funcs"
+    "table_funcs", "variant_funcs", "protobuf_funcs"
 }