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chore: import upstream snapshot with attribution
2026-07-13 13:35:45 +08:00

168 lines
6.6 KiB
Python

# Copyright 2025 Collate
# Licensed under the Collate Community License, Version 1.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
# 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.
"""
Sampler-level integration tests for MSSQL dynamic sampling.
Tests _get_asset_row_count accuracy and sampling query execution against a real SQL Server.
No OpenMetadata server required — only MSSQL container.
"""
from unittest.mock import MagicMock
import pytest
from sqlalchemy import Column, Integer, String, create_engine, text
from sqlalchemy.orm import DeclarativeBase
from testcontainers.mssql import SqlServerContainer
from metadata.generated.schema.entity.data.table import TableType
from metadata.generated.schema.type.basic import ProfileSampleType
from metadata.generated.schema.type.dynamicSamplingConfig import (
DynamicSamplingConfig,
Threshold,
)
from metadata.generated.schema.type.samplingConfig import (
ProfileSampleConfig,
SampleConfigType,
)
from metadata.ingestion.connections.session import create_and_bind_session
from metadata.profiler.orm.functions.table_metric_computer import (
MSSQLTableMetricComputer,
)
from metadata.profiler.processor.runner import QueryRunner
from metadata.sampler.config import resolve_static_sampling_config
class Base(DeclarativeBase):
pass
class MssqlSamplingTestTable(Base):
__tablename__ = "sampling_test"
__table_args__ = {"schema": "dbo"} # noqa: RUF012
id = Column(Integer, primary_key=True)
name = Column(String(256))
ROW_COUNT = 500
@pytest.fixture(scope="module")
def mssql_engine():
container = SqlServerContainer("mcr.microsoft.com/mssql/server:2022-latest", dbname="master")
with container as container:
url = "mssql+pytds://" + container.get_connection_url().split("://")[1]
engine = create_engine(url, connect_args={"autocommit": True})
with engine.connect() as conn:
conn.execute(text("CREATE TABLE dbo.sampling_test (id INT PRIMARY KEY, name NVARCHAR(256))"))
values = ", ".join(f"({i}, 'row_{i}')" for i in range(1, ROW_COUNT + 1))
conn.execute(text(f"INSERT INTO dbo.sampling_test (id, name) VALUES {values}"))
yield engine
with engine.connect() as conn:
conn.execute(text("DROP TABLE IF EXISTS dbo.sampling_test"))
engine.dispose()
@pytest.fixture(scope="module")
def mssql_session(mssql_engine):
session = create_and_bind_session(mssql_engine)
yield session
session.close()
class TestMSSQLDynamicSampling:
"""Sampler-level integration tests against a real SQL Server database."""
def test_row_count_via_metric_computer(self, mssql_session):
"""Verify MSSQLTableMetricComputer returns accurate row count."""
from metadata.profiler.metrics.registry import Metrics
runner = QueryRunner(
session=mssql_session,
dataset=MssqlSamplingTestTable,
raw_dataset=MssqlSamplingTestTable,
)
entity = MagicMock()
entity.tableType = TableType.Regular
entity.name = MagicMock()
entity.name.root = "sampling_test"
entity.databaseSchema = MagicMock()
entity.databaseSchema.name = "dbo"
computer = MSSQLTableMetricComputer(
runner=runner,
metrics=[Metrics.rowCount],
conn_config=MagicMock(),
entity=entity,
)
computer._set_table_and_schema_name()
result = computer.compute()
assert result is not None
assert result.rowCount == ROW_COUNT
def test_dynamic_smart_sampling_resolution(self, mssql_session):
"""With 500 rows, smart sampling should resolve to 100% (<=100K tier)."""
config = ProfileSampleConfig(
sampleConfigType=SampleConfigType.DYNAMIC,
config=DynamicSamplingConfig(smartSampling=True),
)
static = resolve_static_sampling_config(sample_config=config, row_count=ROW_COUNT)
assert static is not None
assert static.profileSample == 100
assert static.profileSampleType == ProfileSampleType.PERCENTAGE
def test_dynamic_threshold_resolution(self, mssql_session):
"""Custom threshold at 100 rows → 30% should apply for 500 rows."""
config = ProfileSampleConfig(
sampleConfigType=SampleConfigType.DYNAMIC,
config=DynamicSamplingConfig(
smartSampling=False,
thresholds=[
Threshold(rowCountThreshold=100, profileSample=30.0),
],
),
)
static = resolve_static_sampling_config(sample_config=config, row_count=ROW_COUNT)
assert static is not None
assert static.profileSample == 30.0
def test_tablesample_percent_executes(self, mssql_session):
"""MSSQL TABLESAMPLE with PERCENT should execute successfully."""
table = MssqlSamplingTestTable.__table__
# MSSQL TABLESAMPLE syntax: table TABLESAMPLE (N PERCENT)
result = mssql_session.execute(
text(f"SELECT * FROM {table.schema}.{table.name} TABLESAMPLE (50 PERCENT)")
).fetchall()
# MSSQL TABLESAMPLE is page-based, results are approximate
assert len(result) <= ROW_COUNT
def test_tablesample_rows_executes(self, mssql_session):
"""MSSQL TABLESAMPLE with ROWS should execute successfully."""
table = MssqlSamplingTestTable.__table__
result = mssql_session.execute(
text(f"SELECT * FROM {table.schema}.{table.name} TABLESAMPLE (100 ROWS)")
).fetchall()
assert len(result) <= ROW_COUNT
def test_dynamic_threshold_below_returns_none(self, mssql_session):
"""When row count is below all thresholds, resolve returns None."""
config = ProfileSampleConfig(
sampleConfigType=SampleConfigType.DYNAMIC,
config=DynamicSamplingConfig(
smartSampling=False,
thresholds=[
Threshold(rowCountThreshold=1000, profileSample=10.0),
],
),
)
static = resolve_static_sampling_config(sample_config=config, row_count=ROW_COUNT)
# 500 < 1000 threshold → no sampling
assert static is None