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feat: add data source for Cloud Spanner (#206)
* feat: add data source for Cloud Spanner * remove dtype conversions * fix spanner tests on Python 3.9 * 2nd try at workaround for iteritems bug * update comment * increase timeout * bump timeout * remove unused constant
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# Copyright 2020 Google LLC | ||
# | ||
# Licensed 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. | ||
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import datetime | ||
import json | ||
import os | ||
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import pytest | ||
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from data_validation import cli_tools, consts, data_validation | ||
from data_validation import __main__ as main | ||
from third_party.ibis.ibis_cloud_spanner.tests import conftest | ||
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SPANNER_CONN_NAME = "spanner-integration-test" | ||
CLI_FIND_TABLES_ARGS = [ | ||
"find-tables", | ||
"--source-conn", | ||
SPANNER_CONN_NAME, | ||
"--target-conn", | ||
SPANNER_CONN_NAME, | ||
] | ||
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# Copy text fixtures from Spanner Ibis client tests, because it's a bit verbose | ||
# to create a Spanner instance and load data to it. Relevant test fixtures can | ||
# be copied here after clients are upstreamed to Ibis. | ||
spanner_client = conftest.spanner_client | ||
instance_id = conftest.instance_id | ||
database_id = conftest.database_id | ||
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@pytest.fixture | ||
def spanner_connection_config(instance_id, database_id): | ||
return { | ||
"source_type": "Spanner", | ||
"project_id": os.environ["PROJECT_ID"], | ||
"instance_id": instance_id, | ||
"database_id": database_id, | ||
} | ||
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@pytest.fixture | ||
def spanner_connection_args(instance_id, database_id): | ||
return [ | ||
"connections", | ||
"add", | ||
"--connection-name", | ||
SPANNER_CONN_NAME, | ||
"Spanner", | ||
"--project-id", | ||
os.environ["PROJECT_ID"], | ||
"--instance-id", | ||
instance_id, | ||
"--database-id", | ||
database_id, | ||
] | ||
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@pytest.fixture | ||
def count_config(spanner_connection_config, database_id): | ||
return { | ||
# Connection Name | ||
consts.CONFIG_SOURCE_CONN: spanner_connection_config, | ||
consts.CONFIG_TARGET_CONN: spanner_connection_config, | ||
# Validation Type | ||
consts.CONFIG_TYPE: "Column", | ||
# Configuration Required Depending on Validator Type | ||
consts.CONFIG_SCHEMA_NAME: database_id, | ||
consts.CONFIG_TABLE_NAME: "functional_alltypes", | ||
consts.CONFIG_GROUPED_COLUMNS: [], | ||
consts.CONFIG_AGGREGATES: [ | ||
{ | ||
consts.CONFIG_TYPE: "count", | ||
consts.CONFIG_SOURCE_COLUMN: None, | ||
consts.CONFIG_TARGET_COLUMN: None, | ||
consts.CONFIG_FIELD_ALIAS: "count", | ||
}, | ||
{ | ||
consts.CONFIG_TYPE: "count", | ||
consts.CONFIG_SOURCE_COLUMN: "string_col", | ||
consts.CONFIG_TARGET_COLUMN: "string_col", | ||
consts.CONFIG_FIELD_ALIAS: "count_string_col", | ||
}, | ||
{ | ||
consts.CONFIG_TYPE: "avg", | ||
consts.CONFIG_SOURCE_COLUMN: "float_col", | ||
consts.CONFIG_TARGET_COLUMN: "float_col", | ||
consts.CONFIG_FIELD_ALIAS: "avg_float_col", | ||
}, | ||
{ | ||
consts.CONFIG_TYPE: "max", | ||
consts.CONFIG_SOURCE_COLUMN: "timestamp_col", | ||
consts.CONFIG_TARGET_COLUMN: "timestamp_col", | ||
consts.CONFIG_FIELD_ALIAS: "max_timestamp_col", | ||
}, | ||
{ | ||
consts.CONFIG_TYPE: "min", | ||
consts.CONFIG_SOURCE_COLUMN: "int_col", | ||
consts.CONFIG_TARGET_COLUMN: "int_col", | ||
consts.CONFIG_FIELD_ALIAS: "min_int_col", | ||
}, | ||
], | ||
} | ||
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@pytest.fixture | ||
def grouped_config(spanner_connection_config, database_id): | ||
return { | ||
# Connection Name | ||
consts.CONFIG_SOURCE_CONN: spanner_connection_config, | ||
consts.CONFIG_TARGET_CONN: spanner_connection_config, | ||
# Validation Type | ||
consts.CONFIG_TYPE: "GroupedColumn", | ||
# Configuration Required Depending on Validator Type | ||
consts.CONFIG_SCHEMA_NAME: database_id, | ||
consts.CONFIG_TABLE_NAME: "functional_alltypes", | ||
consts.CONFIG_AGGREGATES: [ | ||
{ | ||
consts.CONFIG_TYPE: "count", | ||
consts.CONFIG_SOURCE_COLUMN: None, | ||
consts.CONFIG_TARGET_COLUMN: None, | ||
consts.CONFIG_FIELD_ALIAS: "count", | ||
}, | ||
{ | ||
consts.CONFIG_TYPE: "sum", | ||
consts.CONFIG_SOURCE_COLUMN: "float_col", | ||
consts.CONFIG_TARGET_COLUMN: "float_col", | ||
consts.CONFIG_FIELD_ALIAS: "sum_float_col", | ||
}, | ||
], | ||
consts.CONFIG_GROUPED_COLUMNS: [ | ||
{ | ||
consts.CONFIG_FIELD_ALIAS: "timestamp_col", | ||
consts.CONFIG_SOURCE_COLUMN: "timestamp_col", | ||
consts.CONFIG_TARGET_COLUMN: "timestamp_col", | ||
consts.CONFIG_CAST: "date", | ||
}, | ||
], | ||
} | ||
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CLI_CONFIG_FILE = "example_test.yaml" | ||
CLI_RUN_CONFIG_ARGS = ["run-config", "--config-file", CLI_CONFIG_FILE] | ||
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STRING_MATCH_RESULT = '{"schema_name": "pso_data_validator", "table_name": "results", "target_schema_name": "pso_data_validator", "target_table_name": "results"}' | ||
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def test_count_validator(count_config): | ||
validator = data_validation.DataValidation(count_config, verbose=True) | ||
df = validator.execute() | ||
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count_value = df[df["validation_name"] == "count"]["source_agg_value"].values[0] | ||
count_string_value = df[df["validation_name"] == "count_string_col"][ | ||
"source_agg_value" | ||
].values[0] | ||
avg_float_value = df[df["validation_name"] == "avg_float_col"][ | ||
"source_agg_value" | ||
].values[0] | ||
max_timestamp_value = df[df["validation_name"] == "max_timestamp_col"][ | ||
"source_agg_value" | ||
].values[0] | ||
min_int_value = df[df["validation_name"] == "min_int_col"][ | ||
"source_agg_value" | ||
].values[0] | ||
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assert float(count_value) > 0 | ||
assert float(count_string_value) > 0 | ||
assert float(avg_float_value) > 0 | ||
assert datetime.datetime.strptime( | ||
max_timestamp_value, "%Y-%m-%d %H:%M:%S%z", | ||
) > datetime.datetime(1970, 1, 1, tzinfo=datetime.timezone.utc) | ||
assert float(min_int_value) > 0 | ||
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def test_grouped_count_validator(grouped_config): | ||
validator = data_validation.DataValidation(grouped_config, verbose=True) | ||
df = validator.execute() | ||
rows = list(df[df["validation_name"] == "count"].iterrows()) | ||
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# Check that all partitions are unique. | ||
partitions = frozenset(df["group_by_columns"]) | ||
assert len(rows) == len(partitions) | ||
assert len(rows) > 1 | ||
assert df["source_agg_value"].sum() == df["target_agg_value"].sum() | ||
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for _, row in rows: | ||
assert float(row["source_agg_value"]) > 0 | ||
assert row["source_agg_value"] == row["target_agg_value"] | ||
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def test_cli_find_tables(spanner_connection_args, database_id): | ||
_store_spanner_conn(spanner_connection_args) | ||
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parser = cli_tools.configure_arg_parser() | ||
args = parser.parse_args(CLI_FIND_TABLES_ARGS) | ||
tables_json = main.find_tables_using_string_matching(args) | ||
tables = json.loads(tables_json) | ||
assert isinstance(tables_json, str) | ||
assert { | ||
"schema_name": database_id, | ||
"table_name": "array_table", | ||
"target_schema_name": database_id, | ||
"target_table_name": "array_table", | ||
} in tables | ||
assert { | ||
"schema_name": database_id, | ||
"table_name": "functional_alltypes", | ||
"target_schema_name": database_id, | ||
"target_table_name": "functional_alltypes", | ||
} in tables | ||
assert { | ||
"schema_name": database_id, | ||
"table_name": "students_pointer", | ||
"target_schema_name": database_id, | ||
"target_table_name": "students_pointer", | ||
} in tables | ||
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_remove_spanner_conn() | ||
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def _store_spanner_conn(spanner_connection_args): | ||
parser = cli_tools.configure_arg_parser() | ||
mock_args = parser.parse_args(spanner_connection_args) | ||
main.run_connections(mock_args) | ||
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def _remove_spanner_conn(): | ||
file_path = cli_tools._get_connection_file(SPANNER_CONN_NAME) | ||
os.remove(file_path) |
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