# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import sys import unittest.mock as mock import pytest from pandas import DataFrame from sqlalchemy import column from superset.connectors.sqla.models import TableColumn from superset.db_engine_specs.base import BaseEngineSpec from superset.db_engine_specs.bigquery import BigQueryEngineSpec from superset.errors import ErrorLevel, SupersetError, SupersetErrorType from superset.sql_parse import Table from tests.integration_tests.db_engine_specs.base_tests import TestDbEngineSpec from tests.integration_tests.fixtures.birth_names_dashboard import ( load_birth_names_dashboard_with_slices, load_birth_names_data, ) class TestBigQueryDbEngineSpec(TestDbEngineSpec): def test_bigquery_sqla_column_label(self): """ DB Eng Specs (bigquery): Test column label """ test_cases = { "Col": "Col", "SUM(x)": "SUM_x__5f110", "SUM[x]": "SUM_x__7ebe1", "12345_col": "_12345_col_8d390", } for original, expected in test_cases.items(): actual = BigQueryEngineSpec.make_label_compatible(column(original).name) self.assertEqual(actual, expected) def test_convert_dttm(self): """ DB Eng Specs (bigquery): Test conversion to date time """ dttm = self.get_dttm() test_cases = { "DATE": "CAST('2019-01-02' AS DATE)", "DATETIME": "CAST('2019-01-02T03:04:05.678900' AS DATETIME)", "TIMESTAMP": "CAST('2019-01-02T03:04:05.678900' AS TIMESTAMP)", "TIME": "CAST('03:04:05.678900' AS TIME)", "UNKNOWNTYPE": None, } for target_type, expected in test_cases.items(): actual = BigQueryEngineSpec.convert_dttm(target_type, dttm) self.assertEqual(actual, expected) def test_timegrain_expressions(self): """ DB Eng Specs (bigquery): Test time grain expressions """ col = column("temporal") test_cases = { "DATE": "DATE_TRUNC(temporal, HOUR)", "TIME": "TIME_TRUNC(temporal, HOUR)", "DATETIME": "DATETIME_TRUNC(temporal, HOUR)", "TIMESTAMP": "TIMESTAMP_TRUNC(temporal, HOUR)", } for type_, expected in test_cases.items(): actual = BigQueryEngineSpec.get_timestamp_expr( col=col, pdf=None, time_grain="PT1H", type_=type_ ) self.assertEqual(str(actual), expected) def test_custom_minute_timegrain_expressions(self): """ DB Eng Specs (bigquery): Test time grain expressions """ col = column("temporal") test_cases = { "DATE": "CAST(TIMESTAMP_SECONDS(" "5*60 * DIV(UNIX_SECONDS(CAST(temporal AS TIMESTAMP)), 5*60)" ") AS DATE)", "DATETIME": "CAST(TIMESTAMP_SECONDS(" "5*60 * DIV(UNIX_SECONDS(CAST(temporal AS TIMESTAMP)), 5*60)" ") AS DATETIME)", "TIMESTAMP": "CAST(TIMESTAMP_SECONDS(" "5*60 * DIV(UNIX_SECONDS(CAST(temporal AS TIMESTAMP)), 5*60)" ") AS TIMESTAMP)", } for type_, expected in test_cases.items(): actual = BigQueryEngineSpec.get_timestamp_expr( col=col, pdf=None, time_grain="PT5M", type_=type_ ) assert str(actual) == expected def test_fetch_data(self): """ DB Eng Specs (bigquery): Test fetch data """ # Mock a google.cloud.bigquery.table.Row class Row(object): def __init__(self, value): self._value = value def values(self): return self._value data1 = [(1, "foo")] with mock.patch.object(BaseEngineSpec, "fetch_data", return_value=data1): result = BigQueryEngineSpec.fetch_data(None, 0) self.assertEqual(result, data1) data2 = [Row(1), Row(2)] with mock.patch.object(BaseEngineSpec, "fetch_data", return_value=data2): result = BigQueryEngineSpec.fetch_data(None, 0) self.assertEqual(result, [1, 2]) def test_extra_table_metadata(self): """ DB Eng Specs (bigquery): Test extra table metadata """ database = mock.Mock() # Test no indexes database.get_indexes = mock.MagicMock(return_value=None) result = BigQueryEngineSpec.extra_table_metadata( database, "some_table", "some_schema" ) self.assertEqual(result, {}) index_metadata = [ { "name": "clustering", "column_names": ["c_col1", "c_col2", "c_col3"], }, { "name": "partition", "column_names": ["p_col1", "p_col2", "p_col3"], }, ] expected_result = { "partitions": {"cols": [["p_col1", "p_col2", "p_col3"]]}, "clustering": {"cols": [["c_col1", "c_col2", "c_col3"]]}, } database.get_indexes = mock.MagicMock(return_value=index_metadata) result = BigQueryEngineSpec.extra_table_metadata( database, "some_table", "some_schema" ) self.assertEqual(result, expected_result) def test_normalize_indexes(self): """ DB Eng Specs (bigquery): Test extra table metadata """ indexes = [{"name": "partition", "column_names": [None], "unique": False}] normalized_idx = BigQueryEngineSpec.normalize_indexes(indexes) self.assertEqual(normalized_idx, []) indexes = [{"name": "partition", "column_names": ["dttm"], "unique": False}] normalized_idx = BigQueryEngineSpec.normalize_indexes(indexes) self.assertEqual(normalized_idx, indexes) indexes = [ {"name": "partition", "column_names": ["dttm", None], "unique": False} ] normalized_idx = BigQueryEngineSpec.normalize_indexes(indexes) self.assertEqual( normalized_idx, [{"name": "partition", "column_names": ["dttm"], "unique": False}], ) @mock.patch("superset.db_engine_specs.bigquery.BigQueryEngineSpec.get_engine") def test_df_to_sql(self, mock_get_engine): """ DB Eng Specs (bigquery): Test DataFrame to SQL contract """ # test missing google.oauth2 dependency sys.modules["pandas_gbq"] = mock.MagicMock() df = DataFrame() database = mock.MagicMock() with self.assertRaises(Exception): BigQueryEngineSpec.df_to_sql( database=database, table=Table(table="name", schema="schema"), df=df, to_sql_kwargs={}, ) invalid_kwargs = [ {"name": "some_name"}, {"schema": "some_schema"}, {"con": "some_con"}, {"name": "some_name", "con": "some_con"}, {"name": "some_name", "schema": "some_schema"}, {"con": "some_con", "schema": "some_schema"}, ] # Test check for missing schema. sys.modules["google.oauth2"] = mock.MagicMock() for invalid_kwarg in invalid_kwargs: self.assertRaisesRegex( Exception, "The table schema must be defined", BigQueryEngineSpec.df_to_sql, database=database, table=Table(table="name"), df=df, to_sql_kwargs=invalid_kwarg, ) import pandas_gbq from google.oauth2 import service_account pandas_gbq.to_gbq = mock.Mock() service_account.Credentials.from_service_account_info = mock.MagicMock( return_value="account_info" ) mock_get_engine.return_value.url.host = "google-host" mock_get_engine.return_value.dialect.credentials_info = "secrets" BigQueryEngineSpec.df_to_sql( database=database, table=Table(table="name", schema="schema"), df=df, to_sql_kwargs={"if_exists": "extra_key"}, ) pandas_gbq.to_gbq.assert_called_with( df, project_id="google-host", destination_table="schema.name", credentials="account_info", if_exists="extra_key", ) def test_extract_errors(self): msg = "403 POST https://bigquery.googleapis.com/bigquery/v2/projects/test-keel-310804/jobs?prettyPrint=false: Access Denied: Project User does not have bigquery.jobs.create permission in project profound-keel-310804" result = BigQueryEngineSpec.extract_errors(Exception(msg)) assert result == [ SupersetError( message="We were unable to connect to your database. Please confirm that your service account has the Viewer and Job User roles on the project.", error_type=SupersetErrorType.CONNECTION_DATABASE_PERMISSIONS_ERROR, level=ErrorLevel.ERROR, extra={ "engine_name": "Google BigQuery", "issue_codes": [ { "code": 1017, "message": "", } ], }, ) ] msg = "bigquery error: 404 Not found: Dataset fakeDataset:bogusSchema was not found in location" result = BigQueryEngineSpec.extract_errors(Exception(msg)) assert result == [ SupersetError( message='The schema "bogusSchema" does not exist. A valid schema must be used to run this query.', error_type=SupersetErrorType.SCHEMA_DOES_NOT_EXIST_ERROR, level=ErrorLevel.ERROR, extra={ "engine_name": "Google BigQuery", "issue_codes": [ { "code": 1003, "message": "Issue 1003 - There is a syntax error in the SQL query. Perhaps there was a misspelling or a typo.", }, { "code": 1004, "message": "Issue 1004 - The column was deleted or renamed in the database.", }, ], }, ) ] msg = 'Table name "badtable" missing dataset while no default dataset is set in the request' result = BigQueryEngineSpec.extract_errors(Exception(msg)) assert result == [ SupersetError( message='The table "badtable" does not exist. A valid table must be used to run this query.', error_type=SupersetErrorType.TABLE_DOES_NOT_EXIST_ERROR, level=ErrorLevel.ERROR, extra={ "engine_name": "Google BigQuery", "issue_codes": [ { "code": 1003, "message": "Issue 1003 - There is a syntax error in the SQL query. Perhaps there was a misspelling or a typo.", }, { "code": 1005, "message": "Issue 1005 - The table was deleted or renamed in the database.", }, ], }, ) ] msg = "Unrecognized name: badColumn at [1:8]" result = BigQueryEngineSpec.extract_errors(Exception(msg)) assert result == [ SupersetError( message='We can\'t seem to resolve column "badColumn" at line 1:8.', error_type=SupersetErrorType.COLUMN_DOES_NOT_EXIST_ERROR, level=ErrorLevel.ERROR, extra={ "engine_name": "Google BigQuery", "issue_codes": [ { "code": 1003, "message": "Issue 1003 - There is a syntax error in the SQL query. Perhaps there was a misspelling or a typo.", }, { "code": 1004, "message": "Issue 1004 - The column was deleted or renamed in the database.", }, ], }, ) ] msg = 'Syntax error: Expected end of input but got identifier "fromm"' result = BigQueryEngineSpec.extract_errors(Exception(msg)) assert result == [ SupersetError( message='Please check your query for syntax errors at or near "fromm". Then, try running your query again.', error_type=SupersetErrorType.SYNTAX_ERROR, level=ErrorLevel.ERROR, extra={ "engine_name": "Google BigQuery", "issue_codes": [ { "code": 1030, "message": "Issue 1030 - The query has a syntax error.", } ], }, ) ] @mock.patch("superset.models.core.Database.db_engine_spec", BigQueryEngineSpec) @mock.patch("pybigquery._helpers.create_bigquery_client", mock.Mock) @pytest.mark.usefixtures("load_birth_names_dashboard_with_slices") def test_calculated_column_in_order_by(self): table = self.get_table(name="birth_names") TableColumn( column_name="gender_cc", type="VARCHAR(255)", table=table, expression=""" case when gender=true then "male" else "female" end """, ) table.database.sqlalchemy_uri = "bigquery://" query_obj = { "groupby": ["gender_cc"], "is_timeseries": False, "filter": [], "orderby": [["gender_cc", True]], } sql = table.get_query_str(query_obj) assert "ORDER BY gender_cc ASC" in sql