feat: run BQ queries as single statement (#11904)

* feat: run BQ queries as single statement

* Update deps

* Fix lint

* Update superset/sql_lab.py

Co-authored-by: Ville Brofeldt <33317356+villebro@users.noreply.github.com>

Co-authored-by: Ville Brofeldt <33317356+villebro@users.noreply.github.com>

setup.py

@@ -106,7 +106,11 @@ setup(
     ],
     extras_require={
         "athena": ["pyathena>=1.10.8,<1.11"],
-        "bigquery": ["pandas_gbq>=0.10.0", "pybigquery>=0.4.10"],
+        "bigquery": [
+            "pandas_gbq>=0.10.0",
+            "pybigquery>=0.4.10",
+            "google-cloud-bigquery>=2.4.0",
+        ],
         "clickhouse": ["clickhouse-sqlalchemy>= 0.1.4, <0.2"],
         "cockroachdb": ["cockroachdb>=0.3.5, <0.4"],
         "cors": ["flask-cors>=2.0.0"],

superset/db_engine_specs/base.py

@@ -156,6 +156,7 @@ class BaseEngineSpec:  # pylint: disable=too-many-public-methods
     arraysize = 0
     max_column_name_length = 0
     try_remove_schema_from_table_name = True  # pylint: disable=invalid-name
+    run_multiple_statements_as_one = False
 
     # default matching patterns for identifying column types
     db_column_types: Dict[utils.DbColumnType, Tuple[Pattern[Any], ...]] = {
@@ -454,7 +455,7 @@ class BaseEngineSpec:  # pylint: disable=too-many-public-methods
 
     @staticmethod
     def csv_to_df(**kwargs: Any) -> pd.DataFrame:
-        """ Read csv into Pandas DataFrame
+        """Read csv into Pandas DataFrame
         :param kwargs: params to be passed to DataFrame.read_csv
         :return: Pandas DataFrame containing data from csv
         """
@@ -466,7 +467,7 @@ class BaseEngineSpec:  # pylint: disable=too-many-public-methods
 
     @classmethod
     def df_to_sql(cls, df: pd.DataFrame, **kwargs: Any) -> None:
-        """ Upload data from a Pandas DataFrame to a database. For
+        """Upload data from a Pandas DataFrame to a database. For
         regular engines this calls the DataFrame.to_sql() method. Can be
         overridden for engines that don't work well with to_sql(), e.g.
         BigQuery.

superset/db_engine_specs/bigquery.py

@@ -39,6 +39,10 @@ class BigQueryEngineSpec(BaseEngineSpec):
     engine_name = "Google BigQuery"
     max_column_name_length = 128
 
+    # BigQuery doesn't maintain context when running multiple statements in the
+    # same cursor, so we need to run all statements at once
+    run_multiple_statements_as_one = True
+
     """
     https://www.python.org/dev/peps/pep-0249/#arraysize
     raw_connections bypass the pybigquery query execution context and deal with

superset/sql_lab.py

@@ -296,7 +296,7 @@ def _serialize_and_expand_data(
     return (data, selected_columns, all_columns, expanded_columns)
 
 
-def execute_sql_statements(  # pylint: disable=too-many-arguments, too-many-locals, too-many-statements
+def execute_sql_statements(  # pylint: disable=too-many-arguments, too-many-locals, too-many-statements, too-many-branches
     query_id: int,
     rendered_query: str,
     return_results: bool,
@@ -322,9 +322,15 @@ def execute_sql_statements(  # pylint: disable=too-many-arguments, too-many-loca
         raise SqlLabException("Results backend isn't configured.")
 
     # Breaking down into multiple statements
-    parsed_query = ParsedQuery(rendered_query)
-    statements = parsed_query.get_statements()
-    logger.info("Query %s: Executing %i statement(s)", str(query_id), len(statements))
+    if not db_engine_spec.run_multiple_statements_as_one:
+        parsed_query = ParsedQuery(rendered_query)
+        statements = parsed_query.get_statements()
+        logger.info(
+            "Query %s: Executing %i statement(s)", str(query_id), len(statements)
+        )
+    else:
+        statements = [rendered_query]
+        logger.info("Query %s: Executing query as a single statement", str(query_id))
 
     logger.info("Query %s: Set query to 'running'", str(query_id))
     query.status = QueryStatus.RUNNING