fix: create session dataset for remote functions only when needed

bigframes/remote_function.py

@@ -202,10 +202,22 @@ def create_bq_remote_function(
             OPTIONS (
               endpoint = "{endpoint}"
             )"""
+
         logger.info(f"Creating BQ remote function: {create_function_ddl}")
+
+        # Make sure the dataset exists
+        dataset = bigquery.Dataset(
+            bigquery.DatasetReference.from_string(
+                self._bq_dataset, default_project=self._gcp_project_id
+            )
+        )
+        dataset.location = self._bq_location
+        self._bq_client.create_dataset(dataset, exists_ok=True)
+
         # TODO: Use session._start_query() so we get progress bar
         query_job = self._bq_client.query(create_function_ddl)  # Make an API request.
         query_job.result()  # Wait for the job to complete.
+
         logger.info(f"Created remote function {query_job.ddl_target_routine}")
 
     def get_cloud_function_fully_qualified_parent(self):
@@ -465,17 +477,22 @@ def get_remote_function_specs(self, remote_function_name):
         routines = self._bq_client.list_routines(
             f"{self._gcp_project_id}.{self._bq_dataset}"
         )
-        for routine in routines:
-            if routine.reference.routine_id == remote_function_name:
-                # TODO(shobs): Use first class properties when they are available
-                # https://github.com/googleapis/python-bigquery/issues/1552
-                rf_options = routine._properties.get("remoteFunctionOptions")
-                if rf_options:
-                    http_endpoint = rf_options.get("endpoint")
-                    bq_connection = rf_options.get("connection")
-                    if bq_connection:
-                        bq_connection = os.path.basename(bq_connection)
-                break
+        try:
+            for routine in routines:
+                if routine.reference.routine_id == remote_function_name:
+                    # TODO(shobs): Use first class properties when they are available
+                    # https://github.com/googleapis/python-bigquery/issues/1552
+                    rf_options = routine._properties.get("remoteFunctionOptions")
+                    if rf_options:
+                        http_endpoint = rf_options.get("endpoint")
+                        bq_connection = rf_options.get("connection")
+                        if bq_connection:
+                            bq_connection = os.path.basename(bq_connection)
+                    break
+        except google.api_core.exceptions.NotFound:
+            # The dataset might not exist, in which case the http_endpoint doesn't, either.
+            # Note: list_routines doesn't make an API request until we iterate on the response object.
+            pass
         return (http_endpoint, bq_connection)
 
 

bigframes/session.py

@@ -381,17 +381,12 @@ def _create_and_bind_bq_session(self):
             ]
         )
 
-        # Dataset for storing BQML models and remote functions, which don't yet
+        # Dataset for storing remote functions, which don't yet
         # support proper session temporary storage yet
         self._session_dataset = bigquery.Dataset(
             f"{self.bqclient.project}.bigframes_temp_{self._location.lower().replace('-', '_')}"
         )
         self._session_dataset.location = self._location
-        self._session_dataset.default_table_expiration_ms = 24 * 60 * 60 * 1000
-
-        # TODO: handle case when the dataset does not exist and the user does
-        # not have permission to create one (bigquery.datasets.create IAM)
-        self.bqclient.create_dataset(self._session_dataset, exists_ok=True)
 
     def close(self):
         """Terminated the BQ session, otherwises the session will be terminated automatically after

tests/system/conftest.py

@@ -134,15 +134,28 @@ def cleanup_datasets(bigquery_client: bigquery.Client) -> None:
             )
 
 
+def get_dataset_id(project_id: str):
+    "Get a fully qualified dataset id belonging to the given project."
+    dataset_id = f"{project_id}.{prefixer.create_prefix()}_dataset_id"
+    return dataset_id
+
+
 @pytest.fixture(scope="session")
 def dataset_id(bigquery_client: bigquery.Client):
     """Create (and cleanup) a temporary dataset."""
-    project_id = bigquery_client.project
-    dataset_id = f"{project_id}.{prefixer.create_prefix()}_dataset_id"
-    dataset = bigquery.Dataset(dataset_id)
-    bigquery_client.create_dataset(dataset)
+    dataset_id = get_dataset_id(bigquery_client.project)
+    bigquery_client.create_dataset(dataset_id)
+    yield dataset_id
+    bigquery_client.delete_dataset(dataset_id, delete_contents=True)
+
+
+@pytest.fixture
+def dataset_id_not_created(bigquery_client: bigquery.Client):
+    """Return a temporary dataset object without creating it, and clean it up
+    after it has been used."""
+    dataset_id = get_dataset_id(bigquery_client.project)
     yield dataset_id
-    bigquery_client.delete_dataset(dataset, delete_contents=True)
+    bigquery_client.delete_dataset(dataset_id, delete_contents=True)
 
 
 @pytest.fixture(scope="session")

tests/system/large/test_remote_function.py

@@ -408,6 +408,49 @@ def add_one(x):
         )
 
 
+@pytest.mark.flaky(retries=2, delay=120)
+def test_remote_function_explicit_dataset_not_created(
+    session, scalars_dfs, dataset_id_not_created, bq_cf_connection, functions_client
+):
+    try:
+
+        @session.remote_function(
+            [int],
+            int,
+            dataset_id_not_created,
+            bq_cf_connection,
+            reuse=False,
+        )
+        def square(x):
+            return x * x
+
+        scalars_df, scalars_pandas_df = scalars_dfs
+
+        bf_int64_col = scalars_df["int64_col"]
+        bf_int64_col_filter = bf_int64_col.notnull()
+        bf_int64_col_filtered = bf_int64_col[bf_int64_col_filter]
+        bf_result_col = bf_int64_col_filtered.apply(square)
+        bf_result = (
+            bf_int64_col_filtered.to_frame().assign(result=bf_result_col).to_pandas()
+        )
+
+        pd_int64_col = scalars_pandas_df["int64_col"]
+        pd_int64_col_filter = pd_int64_col.notnull()
+        pd_int64_col_filtered = pd_int64_col[pd_int64_col_filter]
+        pd_result_col = pd_int64_col_filtered.apply(lambda x: x * x)
+        # TODO(shobs): Figure why pandas .apply() changes the dtype, i.e.
+        # pd_int64_col_filtered.dtype is Int64Dtype()
+        # pd_int64_col_filtered.apply(lambda x: x * x).dtype is int64.
+        # For this test let's force the pandas dtype to be same as bigframes' dtype.
+        pd_result_col = pd_result_col.astype(pandas.Int64Dtype())
+        pd_result = pd_int64_col_filtered.to_frame().assign(result=pd_result_col)
+
+        assert_pandas_df_equal_ignore_ordering(bf_result, pd_result)
+    finally:
+        # clean up the gcp assets created for the remote function
+        cleanup_remote_function_assets(session.bqclient, functions_client, square)
+
+
 @pytest.mark.flaky(retries=2, delay=120)
 def test_remote_udf_referring_outside_var(
     session, scalars_dfs, dataset_id, bq_cf_connection, functions_client

tests/system/small/test_session.py

@@ -894,11 +894,6 @@ def test_session_id(session):
     # TODO(chelsealin): Verify the session id can be binded with a load job.
 
 
-def test_session_dataset_exists_and_configured(session: bigframes.Session):
-    dataset = session.bqclient.get_dataset(session._session_dataset_id)
-    assert dataset.default_table_expiration_ms == 24 * 60 * 60 * 1000
-
-
 @pytest.mark.flaky(retries=2)
 def test_to_close_session():
     session = bigframes.Session()