IceS2 e7c9d6aa7f
FIXES 15215: Implement initial Multithreading approach for the Metadata Ingestion on Databases (#15130)
* Implement Initial MultiThread suggestion

* Update all the ingestion sources to use the new ContextManager

* Fix missing wraps on decorator

* Fix Unittests

* Fix linters

* Fix linters

* Fix BigQuery UnitTests

* Add UnitTests to the newly created code

* Fix unittest

* change the threads from table to schemas

* Update README.md

* Small change suggested by Sonar

* Slight change to test a different way to multithread over tables

* Debug changes

* More multithread tests

* Remove uneeded wait time

* Testing

* refactor code based on removal of time.sleep

* Fix wrong paste

* Improve ExecutionTimeContextManager

* Fix missing .get() and unit tests

* Fix conflicting changes

* Update Multithread logic with the incremental extraction

* Fix linters

* Fix unittest

* Remove commented code

* Fix Unittests

* Fix checkstyle

* Change default to threads = 1
2024-03-25 18:20:40 +01:00

150 lines
5.9 KiB
Python

# Copyright 2021 Collate
# 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.
"""
Test fivetran using the topology
"""
import json
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch
from metadata.generated.schema.api.data.createPipeline import CreatePipelineRequest
from metadata.generated.schema.entity.data.pipeline import Pipeline, Task
from metadata.generated.schema.entity.services.pipelineService import (
PipelineConnection,
PipelineService,
PipelineServiceType,
)
from metadata.generated.schema.metadataIngestion.workflow import (
OpenMetadataWorkflowConfig,
)
from metadata.generated.schema.type.basic import FullyQualifiedEntityName, SourceUrl
from metadata.generated.schema.type.entityReference import EntityReference
from metadata.ingestion.source.pipeline.fivetran.metadata import (
FivetranPipelineDetails,
FivetranSource,
)
mock_file_path = (
Path(__file__).parent.parent.parent / "resources/datasets/fivetran_dataset.json"
)
with open(mock_file_path) as file:
mock_data: dict = json.load(file)
mock_fivetran_config = {
"source": {
"type": "fivetran",
"serviceName": "fivetran_source",
"serviceConnection": {
"config": {
"type": "Fivetran",
"apiKey": "sample_api_key",
"apiSecret": "sample_api_secret",
}
},
"sourceConfig": {"config": {"type": "PipelineMetadata"}},
},
"sink": {"type": "metadata-rest", "config": {}},
"workflowConfig": {
"openMetadataServerConfig": {
"hostPort": "http://localhost:8585/api",
"authProvider": "openmetadata",
"securityConfig": {
"jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
},
}
},
}
EXPECTED_FIVETRAN_DETAILS = FivetranPipelineDetails(
source=mock_data.get("source"),
destination=mock_data.get("destination"),
group=mock_data.get("group"),
)
EXPECTED_CREATED_PIPELINES = CreatePipelineRequest(
name="wackiness_remote_aiding_pointless",
displayName="test <> postgres_rds",
tasks=[
Task(
name="wackiness_remote_aiding_pointless",
displayName="test <> postgres_rds",
)
],
service=FullyQualifiedEntityName(__root__="fivetran_source"),
sourceUrl=SourceUrl(
__root__="https://fivetran.com/dashboard/connectors/aiding_pointless/status?groupId=wackiness_remote&service=postgres_rds"
),
)
MOCK_PIPELINE_SERVICE = PipelineService(
id="85811038-099a-11ed-861d-0242ac120002",
name="fivetran_source",
fullyQualifiedName=FullyQualifiedEntityName(__root__="fivetran_source"),
connection=PipelineConnection(),
serviceType=PipelineServiceType.Fivetran,
)
MOCK_PIPELINE = Pipeline(
id="2aaa012e-099a-11ed-861d-0242ac120002",
name="wackiness_remote_aiding_pointless",
fullyQualifiedName="fivetran_source.wackiness_remote_aiding_pointless",
displayName="test <> postgres_rds",
tasks=[
Task(
name="wackiness_remote_aiding_pointless",
displayName="test <> postgres_rds",
)
],
service=EntityReference(
id="85811038-099a-11ed-861d-0242ac120002", type="pipelineService"
),
)
class FivetranUnitTest(TestCase):
@patch(
"metadata.ingestion.source.pipeline.pipeline_service.PipelineServiceSource.test_connection"
)
@patch("metadata.ingestion.source.pipeline.fivetran.connection.get_connection")
def __init__(self, methodName, fivetran_client, test_connection) -> None:
super().__init__(methodName)
test_connection.return_value = False
config = OpenMetadataWorkflowConfig.parse_obj(mock_fivetran_config)
self.fivetran = FivetranSource.create(
mock_fivetran_config["source"],
config.workflowConfig.openMetadataServerConfig,
)
self.fivetran.context.get().__dict__["pipeline"] = MOCK_PIPELINE.name.__root__
self.fivetran.context.get().__dict__[
"pipeline_service"
] = MOCK_PIPELINE_SERVICE.name.__root__
self.client = fivetran_client.return_value
self.client.list_groups.return_value = [mock_data.get("group")]
self.client.list_group_connectors.return_value = [mock_data.get("source")]
self.client.get_destination_details.return_value = mock_data.get("destination")
self.client.get_connector_details.return_value = mock_data.get("source")
def test_pipeline_list(self):
assert list(self.fivetran.get_pipelines_list())[0] == EXPECTED_FIVETRAN_DETAILS
def test_pipeline_name(self):
assert (
self.fivetran.get_pipeline_name(EXPECTED_FIVETRAN_DETAILS)
== f'{mock_data.get("group").get("id")}_{mock_data.get("source").get("id")}'
)
def test_pipelines(self):
pipline = list(self.fivetran.yield_pipeline(EXPECTED_FIVETRAN_DETAILS))[0].right
assert pipline == EXPECTED_CREATED_PIPELINES