fix: use data project for destination in to_gbq

pandas_gbq/gbq.py

@@ -549,6 +549,7 @@ def load_data(
         schema=None,
         progress_bar=True,
         api_method: str = "load_parquet",
+        billing_project: Optional[str] = None,
     ):
         from pandas_gbq import load
 
@@ -563,6 +564,7 @@ def load_data(
                 schema=schema,
                 location=self.location,
                 api_method=api_method,
+                billing_project=billing_project,
             )
             if progress_bar and tqdm:
                 chunks = tqdm.tqdm(chunks)
@@ -575,8 +577,8 @@ def load_data(
         except self.http_error as ex:
             self.process_http_error(ex)
 
-    def delete_and_recreate_table(self, dataset_id, table_id, table_schema):
-        table = _Table(self.project_id, dataset_id, credentials=self.credentials)
+    def delete_and_recreate_table(self, project_id, dataset_id, table_id, table_schema):
+        table = _Table(project_id, dataset_id, credentials=self.credentials)
         table.delete(table_id)
         table.create(table_id, table_schema)
 
@@ -1113,7 +1115,9 @@ def to_gbq(
                 "'append' or 'replace' data."
             )
         elif if_exists == "replace":
-            connector.delete_and_recreate_table(dataset_id, table_id, table_schema)
+            connector.delete_and_recreate_table(
+                project_id_table, dataset_id, table_id, table_schema
+            )
         else:
             if not pandas_gbq.schema.schema_is_subset(original_schema, table_schema):
                 raise InvalidSchema(
@@ -1142,6 +1146,7 @@ def to_gbq(
         schema=table_schema,
         progress_bar=progress_bar,
         api_method=api_method,
+        billing_project=project_id,
     )
 
 

pandas_gbq/load.py

@@ -114,6 +114,7 @@ def load_parquet(
     destination_table_ref: bigquery.TableReference,
     location: Optional[str],
     schema: Optional[Dict[str, Any]],
+    billing_project: Optional[str] = None,
 ):
     job_config = bigquery.LoadJobConfig()
     job_config.write_disposition = "WRITE_APPEND"
@@ -126,7 +127,11 @@ def load_parquet(
 
     try:
         client.load_table_from_dataframe(
-            dataframe, destination_table_ref, job_config=job_config, location=location,
+            dataframe,
+            destination_table_ref,
+            job_config=job_config,
+            location=location,
+            project=billing_project,
         ).result()
     except pyarrow.lib.ArrowInvalid as exc:
         raise exceptions.ConversionError(
@@ -162,6 +167,7 @@ def load_csv_from_dataframe(
     location: Optional[str],
     chunksize: Optional[int],
     schema: Optional[Dict[str, Any]],
+    billing_project: Optional[str] = None,
 ):
     bq_schema = None
 
@@ -171,7 +177,11 @@ def load_csv_from_dataframe(
 
     def load_chunk(chunk, job_config):
         client.load_table_from_dataframe(
-            chunk, destination_table_ref, job_config=job_config, location=location,
+            chunk,
+            destination_table_ref,
+            job_config=job_config,
+            location=location,
+            project=billing_project,
         ).result()
 
     return load_csv(dataframe, chunksize, bq_schema, load_chunk)
@@ -184,6 +194,7 @@ def load_csv_from_file(
     location: Optional[str],
     chunksize: Optional[int],
     schema: Optional[Dict[str, Any]],
+    billing_project: Optional[str] = None,
 ):
     """Manually encode a DataFrame to CSV and use the buffer in a load job.
 
@@ -204,6 +215,7 @@ def load_chunk(chunk, job_config):
                 destination_table_ref,
                 job_config=job_config,
                 location=location,
+                project=billing_project,
             ).result()
         finally:
             chunk_buffer.close()
@@ -219,19 +231,39 @@ def load_chunks(
     schema=None,
     location=None,
     api_method="load_parquet",
+    billing_project: Optional[str] = None,
 ):
     if api_method == "load_parquet":
-        load_parquet(client, dataframe, destination_table_ref, location, schema)
+        load_parquet(
+            client,
+            dataframe,
+            destination_table_ref,
+            location,
+            schema,
+            billing_project=billing_project,
+        )
         # TODO: yield progress depending on result() with timeout
         return [0]
     elif api_method == "load_csv":
         if FEATURES.bigquery_has_from_dataframe_with_csv:
             return load_csv_from_dataframe(
-                client, dataframe, destination_table_ref, location, chunksize, schema
+                client,
+                dataframe,
+                destination_table_ref,
+                location,
+                chunksize,
+                schema,
+                billing_project=billing_project,
             )
         else:
             return load_csv_from_file(
-                client, dataframe, destination_table_ref, location, chunksize, schema
+                client,
+                dataframe,
+                destination_table_ref,
+                location,
+                chunksize,
+                schema,
+                billing_project=billing_project,
             )
     else:
         raise ValueError(

tests/unit/test_to_gbq.py

@@ -131,6 +131,46 @@ def test_to_gbq_with_if_exists_replace(mock_bigquery_client):
     assert mock_bigquery_client.create_table.called
 
 
+def test_to_gbq_with_if_exists_replace_cross_project(
+    mock_bigquery_client, expected_load_method
+):
+    mock_bigquery_client.get_table.side_effect = (
+        # Initial check
+        google.cloud.bigquery.Table("data-project.my_dataset.my_table"),
+        # Recreate check
+        google.api_core.exceptions.NotFound("my_table"),
+    )
+    gbq.to_gbq(
+        DataFrame([[1]]),
+        "data-project.my_dataset.my_table",
+        project_id="billing-project",
+        if_exists="replace",
+    )
+    # TODO: We can avoid these API calls by using write disposition in the load
+    # job. See: https://github.com/googleapis/python-bigquery-pandas/issues/118
+    assert mock_bigquery_client.delete_table.called
+    args, _ = mock_bigquery_client.delete_table.call_args
+    table_delete: google.cloud.bigquery.TableReference = args[0]
+    assert table_delete.project == "data-project"
+    assert table_delete.dataset_id == "my_dataset"
+    assert table_delete.table_id == "my_table"
+    assert mock_bigquery_client.create_table.called
+    args, _ = mock_bigquery_client.create_table.call_args
+    table_create: google.cloud.bigquery.TableReference = args[0]
+    assert table_create.project == "data-project"
+    assert table_create.dataset_id == "my_dataset"
+    assert table_create.table_id == "my_table"
+
+    # Check that billing project and destination table is set correctly.
+    expected_load_method.assert_called_once()
+    load_args, load_kwargs = expected_load_method.call_args
+    table_destination = load_args[1]
+    assert table_destination.project == "data-project"
+    assert table_destination.dataset_id == "my_dataset"
+    assert table_destination.table_id == "my_table"
+    assert load_kwargs["project"] == "billing-project"
+
+
 def test_to_gbq_with_if_exists_unknown():
     with pytest.raises(ValueError):
         gbq.to_gbq(