feat: Support BYOSA in remote_function

bigframes/functions/remote_function.py

@@ -129,6 +129,7 @@ def __init__(
         bq_connection_client,
         bq_connection_id,
         cloud_resource_manager_client,
+        cloud_function_service_account,
     ):
         self._gcp_project_id = gcp_project_id
         self._cloud_function_region = cloud_function_region
@@ -140,6 +141,7 @@ def __init__(
         self._bq_connection_manager = clients.BqConnectionManager(
             bq_connection_client, cloud_resource_manager_client
         )
+        self._cloud_function_service_account = cloud_function_service_account
 
     def create_bq_remote_function(
         self, input_args, input_types, output_type, endpoint, bq_function_name
@@ -384,6 +386,9 @@ def create_cloud_function(self, def_, cf_name, package_requirements=None):
             function.service_config = functions_v2.ServiceConfig()
             function.service_config.available_memory = "1024M"
             function.service_config.timeout_seconds = 600
+            function.service_config.service_account_email = (
+                self._cloud_function_service_account
+            )
             create_function_request.function = function
 
             # Create the cloud function and wait for it to be ready to use
@@ -591,6 +596,7 @@ def remote_function(
     reuse: bool = True,
     name: Optional[str] = None,
     packages: Optional[Sequence[str]] = None,
+    cloud_function_service_account: Optional[str] = None,
 ):
     """Decorator to turn a user defined function into a BigQuery remote function.
 
@@ -646,12 +652,12 @@ def remote_function(
             Client to use for BigQuery operations. If this param is not provided
             then bigquery client from the session would be used.
         bigquery_connection_client (google.cloud.bigquery_connection_v1.ConnectionServiceClient, Optional):
-            Client to use for cloud functions operations. If this param is not
-            provided then functions client from the session would be used.
-        cloud_functions_client (google.cloud.functions_v2.FunctionServiceClient, Optional):
             Client to use for BigQuery connection operations. If this param is
             not provided then bigquery connection client from the session would
             be used.
+        cloud_functions_client (google.cloud.functions_v2.FunctionServiceClient, Optional):
+            Client to use for cloud functions operations. If this param is not
+            provided then the functions client from the session would be used.
         resource_manager_client (google.cloud.resourcemanager_v3.ProjectsClient, Optional):
             Client to use for cloud resource management operations, e.g. for
             getting and setting IAM roles on cloud resources. If this param is
@@ -686,7 +692,13 @@ def remote_function(
             Explicit name of the external package dependencies. Each dependency
             is added to the `requirements.txt` as is, and can be of the form
             supported in https://pip.pypa.io/en/stable/reference/requirements-file-format/.
-
+        cloud_function_service_account (str, Optional):
+            Service account to use for the cloud functions. If not provided then
+            the default service account would be used. See
+            https://cloud.google.com/functions/docs/securing/function-identity
+            for more details. Please make sure the service account has the
+            necessary IAM permissions configured as described in
+            https://cloud.google.com/functions/docs/reference/iam/roles#additional-configuration.
     """
     import bigframes.pandas as bpd
 
@@ -787,6 +799,7 @@ def wrapper(f):
             bigquery_connection_client,
             bq_connection_id,
             resource_manager_client,
+            cloud_function_service_account,
         )
 
         rf_name, cf_name = remote_function_client.provision_bq_remote_function(

bigframes/pandas/__init__.py

@@ -615,6 +615,7 @@ def remote_function(
     reuse: bool = True,
     name: Optional[str] = None,
     packages: Optional[Sequence[str]] = None,
+    cloud_function_service_account: Optional[str] = None,
 ):
     return global_session.with_default_session(
         bigframes.session.Session.remote_function,
@@ -625,6 +626,7 @@ def remote_function(
         reuse=reuse,
         name=name,
         packages=packages,
+        cloud_function_service_account=cloud_function_service_account,
     )
 
 

bigframes/session/__init__.py

@@ -1337,6 +1337,7 @@ def remote_function(
         reuse: bool = True,
         name: Optional[str] = None,
         packages: Optional[Sequence[str]] = None,
+        cloud_function_service_account: Optional[str] = None,
     ):
         """Decorator to turn a user defined function into a BigQuery remote function. Check out
         the code samples at: https://cloud.google.com/bigquery/docs/remote-functions#bigquery-dataframes.
@@ -1410,6 +1411,13 @@ def remote_function(
                 Explicit name of the external package dependencies. Each dependency
                 is added to the `requirements.txt` as is, and can be of the form
                 supported in https://pip.pypa.io/en/stable/reference/requirements-file-format/.
+            cloud_function_service_account (str, Optional):
+                Service account to use for the cloud functions. If not provided
+                then the default service account would be used. See
+                https://cloud.google.com/functions/docs/securing/function-identity
+                for more details. Please make sure the service account has the
+                necessary IAM permissions configured as described in
+                https://cloud.google.com/functions/docs/reference/iam/roles#additional-configuration.
         Returns:
             callable: A remote function object pointing to the cloud assets created
             in the background to support the remote execution. The cloud assets can be
@@ -1428,6 +1436,7 @@ def remote_function(
             reuse=reuse,
             name=name,
             packages=packages,
+            cloud_function_service_account=cloud_function_service_account,
         )
 
     def read_gbq_function(

tests/system/large/test_remote_function.py

@@ -1279,3 +1279,46 @@ def square(x):
         cleanup_remote_function_assets(
             session.bqclient, session.cloudfunctionsclient, square
         )
+
+
+@pytest.mark.skip("This requires additional project config.")
+def test_remote_function_via_session_custom_sa(scalars_dfs):
+    # Set these values to run the test locally
+    # TODO(shobs): Automate and enable this test
+    PROJECT = ""
+    GCF_SERVICE_ACCOUNT = ""
+
+    rf_session = bigframes.Session(context=bigframes.BigQueryOptions(project=PROJECT))
+
+    try:
+
+        @rf_session.remote_function(
+            [int], int, reuse=False, cloud_function_service_account=GCF_SERVICE_ACCOUNT
+        )
+        def square_num(x):
+            if x is None:
+                return x
+            return x * x
+
+        scalars_df, scalars_pandas_df = scalars_dfs
+
+        bf_int64_col = scalars_df["int64_col"]
+        bf_result_col = bf_int64_col.apply(square_num)
+        bf_result = bf_int64_col.to_frame().assign(result=bf_result_col).to_pandas()
+
+        pd_int64_col = scalars_pandas_df["int64_col"]
+        pd_result_col = pd_int64_col.apply(lambda x: x if x is None else x * x)
+        pd_result = pd_int64_col.to_frame().assign(result=pd_result_col)
+
+        assert_pandas_df_equal(bf_result, pd_result, check_dtype=False)
+
+        # Assert that the GCF is created with the intended SA
+        gcf = rf_session.cloudfunctionsclient.get_function(
+            name=square_num.bigframes_cloud_function
+        )
+        assert gcf.service_config.service_account_email == GCF_SERVICE_ACCOUNT
+    finally:
+        # clean up the gcp assets created for the remote function
+        cleanup_remote_function_assets(
+            rf_session.bqclient, rf_session.cloudfunctionsclient, square_num
+        )