reduce diff

Signed-off-by: varun-edachali-dbx <varun.edachali@databricks.com>

Author: varun-edachali-dbx

src/databricks/sql/backend/sea/queue.py

@@ -72,6 +72,7 @@ def build_queue(
             return JsonQueue(result_data.data)
         elif manifest.format == ResultFormat.ARROW_STREAM.value:
             if result_data.attachment is not None:
+                # direct results from Hybrid disposition
                 arrow_file = (
                     ResultSetDownloadHandler._decompress_data(result_data.attachment)
                     if lz4_compressed

src/databricks/sql/backend/sea/utils/filters.py

@@ -53,7 +53,7 @@ def _filter_sea_result_set(
         # Reuse the command_id from the original result set
         command_id = result_set.command_id
 
-        # Create an ExecuteResponse with the filtered data
+        # Create an ExecuteResponse for the filtered data
         execute_response = ExecuteResponse(
             command_id=command_id,
             status=result_set.status,

src/databricks/sql/result_set.py

@@ -55,7 +55,7 @@ def __init__(
 
         Parameters:
             :param connection: The parent connection that was used to execute this command
-            :param backend: The backend specialised backend client to be invoked in the fetch phase
+            :param backend: The specialised backend client to be invoked in the fetch phase
             :param arraysize: The max number of rows to fetch at a time (PEP-249)
             :param buffer_size_bytes: The size (in bytes) of the internal buffer + max fetch
             :param command_id: The command ID
@@ -334,7 +334,7 @@ def fetchmany_arrow(self, size: int) -> "pyarrow.Table":
             n_remaining_rows -= partial_results.num_rows
             self._next_row_index += partial_results.num_rows
 
-        return pyarrow.concat_tables(partial_result_chunks)
+        return pyarrow.concat_tables(partial_result_chunks, use_threads=True)
 
     def fetchmany_columnar(self, size: int):
         """
@@ -385,7 +385,7 @@ def fetchall_arrow(self) -> "pyarrow.Table":
                 for name, col in zip(results.column_names, results.column_table)
             }
             return pyarrow.Table.from_pydict(data)
-        return pyarrow.concat_tables(partial_result_chunks)
+        return pyarrow.concat_tables(partial_result_chunks, use_threads=True)
 
     def fetchall_columnar(self):
         """Fetch all (remaining) rows of a query result, returning them as a Columnar table."""