mirror of
https://github.com/open-metadata/OpenMetadata.git
synced 2025-10-31 02:29:03 +00:00
NiharDoshi99
GitHub
parent
4e02cb1c54
commit
3f78e072e1
@ -26,6 +26,7 @@ _type_map.update(
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"binary": types.BINARY,
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"char": types.CHAR,
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"varchar": types.VARCHAR,
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"decimal": types.DECIMAL,
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}
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)
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@ -61,6 +62,8 @@ def get_columns(
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if attype == "decimal":
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prec, scale = charlen.split(",")
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args = (int(prec), int(scale))
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elif attype.startswith("struct"):
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args = []
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else:
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args = (int(charlen),)
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coltype = coltype(*args)
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411
ingestion/tests/unit/topology/database/test_hive.py
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411
ingestion/tests/unit/topology/database/test_hive.py
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@ -0,0 +1,411 @@
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# Copyright 2021 Collate
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Test Hive using the topology
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"""
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import types
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from unittest import TestCase
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from unittest.mock import patch
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from sqlalchemy.types import INTEGER, VARCHAR, Integer, String
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import metadata.ingestion.source.database.hive.utils as hive_dialect
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from metadata.generated.schema.api.data.createDatabase import CreateDatabaseRequest
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from metadata.generated.schema.api.data.createDatabaseSchema import (
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CreateDatabaseSchemaRequest,
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)
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from metadata.generated.schema.api.data.createTable import CreateTableRequest
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from metadata.generated.schema.entity.data.database import Database
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from metadata.generated.schema.entity.data.databaseSchema import DatabaseSchema
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from metadata.generated.schema.entity.data.table import (
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Column,
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ColumnName,
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DataType,
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TableType,
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)
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from metadata.generated.schema.entity.services.databaseService import (
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DatabaseConnection,
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DatabaseService,
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DatabaseServiceType,
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)
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from metadata.generated.schema.metadataIngestion.workflow import (
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OpenMetadataWorkflowConfig,
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)
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from metadata.generated.schema.type.basic import EntityName, FullyQualifiedEntityName
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from metadata.generated.schema.type.entityReference import EntityReference
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from metadata.ingestion.source.database.hive.metadata import HiveSource
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mock_hive_config = {
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"source": {
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"type": "hive",
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"serviceName": "sample_hive",
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"serviceConnection": {
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"config": {
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"type": "Hive",
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"databaseSchema": "test_database_schema",
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"username": "username",
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"hostPort": "localhost:1466",
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}
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},
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"sourceConfig": {"config": {"type": "DatabaseMetadata"}},
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},
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"sink": {"type": "metadata-rest", "config": {}},
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"workflowConfig": {
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"openMetadataServerConfig": {
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"hostPort": "http://localhost:8585/api",
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"authProvider": "openmetadata",
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"securityConfig": {
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"jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGc"
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"iOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE"
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"2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXB"
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"iEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fN"
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"r3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3u"
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"d-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
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},
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}
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},
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}
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MOCK_DATABASE_SERVICE = DatabaseService(
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id="c3eb265f-5445-4ad3-ba5e-797d3a3071bb",
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name="hive_source_test",
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connection=DatabaseConnection(),
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serviceType=DatabaseServiceType.Hive,
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)
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MOCK_DATABASE = Database(
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id="a58b1856-729c-493b-bc87-6d2269b43ec0",
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name="sample_database",
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fullyQualifiedName="hive_source_test.sample_database",
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displayName="sample_database",
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description="",
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service=EntityReference(
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id="85811038-099a-11ed-861d-0242ac120002", type="databaseService"
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),
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)
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MOCK_DATABASE_SCHEMA = DatabaseSchema(
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id="c3eb265f-5445-4ad3-ba5e-797d3a3071bb",
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name="sample_schema",
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fullyQualifiedName="hive_source_test.sample_database.sample_schema",
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service=EntityReference(id="c3eb265f-5445-4ad3-ba5e-797d3a3071bb", type="database"),
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database=EntityReference(
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id="a58b1856-729c-493b-bc87-6d2269b43ec0",
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type="database",
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),
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)
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MOCK_COLUMN_VALUE = [
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{
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"name": "sample_col_1",
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"type": VARCHAR(),
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"nullable": True,
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"default": None,
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"autoincrement": False,
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"system_data_type": "varchar(50)",
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"comment": None,
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},
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{
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"name": "sample_col_2",
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"type": INTEGER(),
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"nullable": True,
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"default": None,
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"autoincrement": False,
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"system_data_type": "int",
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"comment": None,
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},
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{
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"name": "sample_col_3",
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"type": VARCHAR(),
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"nullable": True,
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"default": None,
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"autoincrement": False,
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"system_data_type": "varchar(50)",
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"comment": None,
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},
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{
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"name": "sample_col_4",
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"type": VARCHAR(),
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"nullable": True,
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"default": None,
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"autoincrement": False,
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"comment": None,
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"system_data_type": "varchar(50)",
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},
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]
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EXPECTED_DATABASE = [
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CreateDatabaseRequest(
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name=EntityName(__root__="sample_database"),
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displayName=None,
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description=None,
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tags=None,
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owner=None,
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service=FullyQualifiedEntityName(__root__="hive_source_test"),
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dataProducts=None,
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default=False,
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retentionPeriod=None,
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extension=None,
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sourceUrl=None,
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domain=None,
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lifeCycle=None,
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sourceHash=None,
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)
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]
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EXPECTED_DATABASE_SCHEMA = [
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CreateDatabaseSchemaRequest(
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name=EntityName(__root__="sample_schema"),
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displayName=None,
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description=None,
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owner=None,
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database=FullyQualifiedEntityName(__root__="hive_source_test.sample_database"),
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dataProducts=None,
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tags=None,
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retentionPeriod=None,
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extension=None,
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sourceUrl=None,
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domain=None,
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lifeCycle=None,
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sourceHash=None,
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)
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]
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EXPECTED_TABLE = [
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CreateTableRequest(
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name=EntityName(__root__="sample_table"),
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displayName=None,
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description=None,
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tableType=TableType.Regular.name,
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columns=[
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Column(
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name=ColumnName(__root__="sample_col_1"),
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displayName=None,
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dataType=DataType.VARCHAR.name,
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arrayDataType=None,
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dataLength=1,
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precision=None,
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scale=None,
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dataTypeDisplay="varchar(50)",
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description=None,
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fullyQualifiedName=None,
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tags=None,
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constraint="NULL",
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ordinalPosition=None,
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jsonSchema=None,
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children=None,
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profile=None,
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customMetrics=None,
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),
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Column(
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name=ColumnName(__root__="sample_col_2"),
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displayName=None,
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dataType=DataType.INT.name,
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arrayDataType=None,
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dataLength=1,
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precision=None,
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scale=None,
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dataTypeDisplay="int",
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description=None,
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fullyQualifiedName=None,
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tags=None,
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constraint="NULL",
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ordinalPosition=None,
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jsonSchema=None,
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children=None,
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profile=None,
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customMetrics=None,
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),
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Column(
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name=ColumnName(__root__="sample_col_3"),
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displayName=None,
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dataType=DataType.VARCHAR.name,
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arrayDataType=None,
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dataLength=1,
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precision=None,
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scale=None,
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dataTypeDisplay="varchar(50)",
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description=None,
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fullyQualifiedName=None,
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tags=None,
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constraint="NULL",
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ordinalPosition=None,
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jsonSchema=None,
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children=None,
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profile=None,
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customMetrics=None,
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),
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Column(
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name=ColumnName(__root__="sample_col_4"),
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displayName=None,
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dataType=DataType.VARCHAR.name,
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arrayDataType=None,
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dataLength=1,
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precision=None,
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scale=None,
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dataTypeDisplay="varchar(50)",
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description=None,
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fullyQualifiedName=None,
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tags=None,
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constraint="NULL",
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ordinalPosition=None,
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jsonSchema=None,
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children=None,
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profile=None,
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customMetrics=None,
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),
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],
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tableConstraints=[],
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tablePartition=None,
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tableProfilerConfig=None,
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owner=None,
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databaseSchema=FullyQualifiedEntityName(
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__root__="hive_source_test.sample_database.sample_schema"
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),
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tags=None,
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viewDefinition=None,
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retentionPeriod=None,
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extension=None,
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sourceUrl=None,
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domain=None,
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dataProducts=None,
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fileFormat=None,
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lifeCycle=None,
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sourceHash=None,
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)
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]
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EXPECTED_COMPLEX_COL_TYPE = [
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{
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"name": "id",
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"type": Integer,
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"comment": None,
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"nullable": True,
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"default": None,
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"system_data_type": "int",
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"is_complex": False,
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},
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{
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"name": "data",
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"type": String(),
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"comment": None,
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"nullable": True,
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"default": None,
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"system_data_type": "struct<a:struct<b:decimal(20,0)>>",
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"is_complex": True,
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},
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{
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"name": "data2",
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"type": String(),
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"comment": None,
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"nullable": True,
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"default": None,
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"system_data_type": "struct<colll:decimal(20,0)>",
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"is_complex": True,
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},
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]
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class HiveUnitTest(TestCase):
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"""
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Implements the necessary methods to extract
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Hive Unit Test
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"""
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@patch(
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"metadata.ingestion.source.database.common_db_source.CommonDbSourceService.test_connection"
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)
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def __init__(
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self,
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methodName,
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test_connection,
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) -> None:
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super().__init__(methodName)
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test_connection.return_value = False
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self.config = OpenMetadataWorkflowConfig.parse_obj(mock_hive_config)
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self.hive = HiveSource.create(
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mock_hive_config["source"],
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self.config.workflowConfig.openMetadataServerConfig,
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)
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self.hive.context.__dict__[
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"database_service"
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] = MOCK_DATABASE_SERVICE.name.__root__
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self.hive.inspector = types.SimpleNamespace()
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self.hive.inspector.get_pk_constraint = lambda table_name, schema_name: []
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self.hive.inspector.get_unique_constraints = lambda table_name, schema_name: []
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self.hive.inspector.get_foreign_keys = lambda table_name, schema_name: []
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def test_yield_database(self):
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assert EXPECTED_DATABASE == [
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either.right for either in self.hive.yield_database(MOCK_DATABASE.name)
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]
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self.hive.context.__dict__[
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"database_service"
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] = MOCK_DATABASE_SERVICE.name.__root__
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self.hive.context.__dict__["database"] = MOCK_DATABASE.name.__root__
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def test_yield_schema(self):
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assert EXPECTED_DATABASE_SCHEMA == [
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either.right
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for either in self.hive.yield_database_schema(
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schema_name=MOCK_DATABASE_SCHEMA.name.__root__
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)
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]
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self.hive.context.__dict__[
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"database_schema"
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] = MOCK_DATABASE_SCHEMA.name.__root__
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def test_yield_table(self):
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self.hive.inspector.get_columns = (
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lambda table_name, schema_name, db_name: MOCK_COLUMN_VALUE
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)
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assert EXPECTED_TABLE == [
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either.right
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for either in self.hive.yield_table(("sample_table", "Regular"))
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]
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def test_col_data_type(self):
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"""
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Test different col type ingested as expected
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"""
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table_columns = [
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("id", "int", ""),
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("data", "struct<a:struct<b:decimal(20,0)>>", ""),
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("data2", "struct<colll:decimal(20,0)>", ""),
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]
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hive_dialect._get_table_columns = ( # pylint: disable=protected-access
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lambda connection, table_name, schema_name: table_columns
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)
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col_list = list(
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hive_dialect.get_columns(
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self=hive_dialect,
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connection=mock_hive_config["source"],
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table_name="sample_table",
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schema="sample_schema",
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)
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)
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for _, (expected, original) in enumerate(
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zip(EXPECTED_COMPLEX_COL_TYPE, col_list)
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):
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def custom_eq(self, __value: object) -> bool:
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return (
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self.length == __value.length
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and self.collation == __value.collation
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)
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String.__eq__ = custom_eq
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self.assertEqual(expected, original)
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