feat: expose gcf memory param in remote_function

bigframes/functions/remote_function.py

@@ -331,6 +331,7 @@ def create_cloud_function(
         max_instance_count=None,
         is_row_processor=False,
         vpc_connector=None,
+        memory_mib=1024,
     ):
         """Create a cloud function from the given user defined function.
 
@@ -410,7 +411,8 @@ def create_cloud_function(
                 self._cloud_function_docker_repository
             )
             function.service_config = functions_v2.ServiceConfig()
-            function.service_config.available_memory = "1024M"
+            if memory_mib is not None:
+                function.service_config.available_memory = f"{memory_mib}Mi"
             if timeout_seconds is not None:
                 if timeout_seconds > 1200:
                     raise ValueError(
@@ -473,6 +475,7 @@ def provision_bq_remote_function(
         cloud_function_max_instance_count,
         is_row_processor,
         cloud_function_vpc_connector,
+        cloud_function_memory_mib,
     ):
         """Provision a BigQuery remote function."""
         # If reuse of any existing function with the same name (indicated by the
@@ -504,6 +507,7 @@ def provision_bq_remote_function(
                 max_instance_count=cloud_function_max_instance_count,
                 is_row_processor=is_row_processor,
                 vpc_connector=cloud_function_vpc_connector,
+                memory_mib=cloud_function_memory_mib,
             )
         else:
             logger.info(f"Cloud function {cloud_function_name} already exists.")
@@ -667,6 +671,7 @@ def remote_function(
     cloud_function_timeout: Optional[int] = 600,
     cloud_function_max_instances: Optional[int] = None,
     cloud_function_vpc_connector: Optional[str] = None,
+    cloud_function_memory_mib: Optional[int] = 1024,
 ):
     """Decorator to turn a user defined function into a BigQuery remote function.
 
@@ -817,6 +822,15 @@ def remote_function(
             function. This is useful if your code needs access to data or
             service(s) that are on a VPC network. See for more details
             https://cloud.google.com/functions/docs/networking/connecting-vpc.
+        cloud_function_memory_mib (int, Optional):
+            The amounts of memory (in mebibytes) to allocate for the cloud
+            function (2nd gen) created. This also dictates a corresponding
+            amount of allocated CPU for the function. By default a memory of
+            1024 MiB is set for the cloud functions created to support
+            BigQuery DataFrames remote function. If you want to let the
+            default memory of cloud functions be allocated, pass `None`. See
+            for more details
+            https://cloud.google.com/functions/docs/configuring/memory.
     """
     # Some defaults may be used from the session if not provided otherwise
     import bigframes.exceptions as bf_exceptions
@@ -1027,6 +1041,7 @@ def try_delattr(attr):
             cloud_function_max_instance_count=cloud_function_max_instances,
             is_row_processor=is_row_processor,
             cloud_function_vpc_connector=cloud_function_vpc_connector,
+            cloud_function_memory_mib=cloud_function_memory_mib,
         )
 
         # TODO: Move ibis logic to compiler step

bigframes/pandas/__init__.py

@@ -666,6 +666,7 @@ def remote_function(
     cloud_function_timeout: Optional[int] = 600,
     cloud_function_max_instances: Optional[int] = None,
     cloud_function_vpc_connector: Optional[str] = None,
+    cloud_function_memory_mib: Optional[int] = 1024,
 ):
     return global_session.with_default_session(
         bigframes.session.Session.remote_function,
@@ -683,6 +684,7 @@ def remote_function(
         cloud_function_timeout=cloud_function_timeout,
         cloud_function_max_instances=cloud_function_max_instances,
         cloud_function_vpc_connector=cloud_function_vpc_connector,
+        cloud_function_memory_mib=cloud_function_memory_mib,
     )
 
 

bigframes/session/__init__.py

@@ -1537,6 +1537,7 @@ def remote_function(
         cloud_function_timeout: Optional[int] = 600,
         cloud_function_max_instances: Optional[int] = None,
         cloud_function_vpc_connector: Optional[str] = None,
+        cloud_function_memory_mib: Optional[int] = 1024,
     ):
         """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.
@@ -1670,6 +1671,15 @@ def remote_function(
                 function. This is useful if your code needs access to data or
                 service(s) that are on a VPC network. See for more details
                 https://cloud.google.com/functions/docs/networking/connecting-vpc.
+            cloud_function_memory_mib (int, Optional):
+                The amounts of memory (in mebibytes) to allocate for the cloud
+                function (2nd gen) created. This also dictates a corresponding
+                amount of allocated CPU for the function. By default a memory of
+                1024 MiB is set for the cloud functions created to support
+                BigQuery DataFrames remote function. If you want to let the
+                default memory of cloud functions be allocated, pass `None`. See
+                for more details
+                https://cloud.google.com/functions/docs/configuring/memory.
         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
@@ -1695,6 +1705,7 @@ def remote_function(
             cloud_function_timeout=cloud_function_timeout,
             cloud_function_max_instances=cloud_function_max_instances,
             cloud_function_vpc_connector=cloud_function_vpc_connector,
+            cloud_function_memory_mib=cloud_function_memory_mib,
         )
 
     def read_gbq_function(

tests/system/large/test_remote_function.py

@@ -1800,3 +1800,63 @@ def float_parser(row):
         cleanup_remote_function_assets(
             session.bqclient, session.cloudfunctionsclient, float_parser_remote
         )
+
+
+@pytest.mark.parametrize(
+    ("memory_mib_args", "expected_memory"),
+    [
+        pytest.param({}, "1024Mi", id="no-set"),
+        pytest.param({"cloud_function_memory_mib": None}, "256M", id="set-None"),
+        pytest.param({"cloud_function_memory_mib": 128}, "128Mi", id="set-128"),
+        pytest.param({"cloud_function_memory_mib": 1024}, "1024Mi", id="set-1024"),
+        pytest.param({"cloud_function_memory_mib": 4096}, "4096Mi", id="set-4096"),
+        pytest.param({"cloud_function_memory_mib": 32768}, "32768Mi", id="set-32768"),
+    ],
+)
+@pytest.mark.flaky(retries=2, delay=120)
+def test_remote_function_gcf_memory(
+    session, scalars_dfs, memory_mib_args, expected_memory
+):
+    try:
+
+        def square(x: int) -> int:
+            return x * x
+
+        square_remote = session.remote_function(reuse=False, **memory_mib_args)(square)
+
+        # Assert that the GCF is created with the intended memory
+        gcf = session.cloudfunctionsclient.get_function(
+            name=square_remote.bigframes_cloud_function
+        )
+        assert gcf.service_config.available_memory == expected_memory
+
+        scalars_df, scalars_pandas_df = scalars_dfs
+
+        bf_result = scalars_df["int64_too"].apply(square_remote).to_pandas()
+        pd_result = scalars_pandas_df["int64_too"].apply(square)
+
+        pandas.testing.assert_series_equal(bf_result, pd_result, check_dtype=False)
+    finally:
+        # clean up the gcp assets created for the remote function
+        cleanup_remote_function_assets(
+            session.bqclient, session.cloudfunctionsclient, square_remote
+        )
+
+
+@pytest.mark.parametrize(
+    ("memory_mib",),
+    [
+        pytest.param(127, id="127-too-low"),
+        pytest.param(32769, id="set-32769-too-high"),
+    ],
+)
+@pytest.mark.flaky(retries=2, delay=120)
+def test_remote_function_gcf_memory_unsupported(session, memory_mib):
+    with pytest.raises(
+        google.api_core.exceptions.InvalidArgument,
+        match="Invalid value specified for container memory",
+    ):
+
+        @session.remote_function(reuse=False, cloud_function_memory_mib=memory_mib)
+        def square(x: int) -> int:
+            return x * x