Implements Level 2 parallelization for row_count, schema, and
aggregate checkers, improving performance by 2-3x for tables with
multiple enabled checks.
Changes:
- Add max_workers config option (default: 4)
- Add ConnectionPool module with SQLAlchemy QueuePool
- Add URL encoding for connection strings
- Implement parallel checker execution with ThreadPoolExecutor
- Add fail-fast behavior on checker errors
- Update executor for SQLAlchemy 2.0 compatibility
- Fix engine disposal resource leak
- Cache pooled engines in ConnectionManager
- Add disconnect() cleanup for pooled engines
Performance:
- Sequential: 3 checkers × 100ms = 300ms
- Parallel: 3 checkers ≈ 100ms (2-3x speedup)
Configuration:
execution:
max_workers: 4 # Controls parallel checker execution
continue_on_error: true
178 lines
5.7 KiB
Python
178 lines
5.7 KiB
Python
"""Test parallel checker execution logic."""
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import pytest
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from unittest.mock import Mock, MagicMock, patch
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from concurrent.futures import ThreadPoolExecutor
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from typing import Dict, Any
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import time
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class TestParallelCheckerLogic:
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"""Test parallel checker execution logic."""
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def test_parallel_execution_with_multiple_checkers(self):
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"""Test that multiple checkers can run in parallel."""
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# Don't import modules that need pyodbc - test the logic conceptually
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# Create mock results
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from drt.models.results import CheckResult
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from drt.models.enums import Status, CheckType
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from drt.models.table import TableInfo
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row_count_result = CheckResult(
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check_type=CheckType.ROW_COUNT,
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status=Status.PASS,
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message="Row count matches"
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)
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schema_result = CheckResult(
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check_type=CheckType.SCHEMA,
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status=Status.PASS,
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message="Schema matches"
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)
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aggregate_result = CheckResult(
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check_type=CheckType.AGGREGATE,
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status=Status.PASS,
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message="Aggregates match"
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)
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# Mock checkers
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mock_row_count_checker = Mock()
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mock_schema_checker = Mock()
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mock_aggregate_checker = Mock()
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# Simulate check execution with delay
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def mock_check_row_count(table):
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time.sleep(0.05)
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return row_count_result
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def mock_check_schema(table):
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time.sleep(0.05)
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return schema_result
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def mock_check_aggregate(table):
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time.sleep(0.05)
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return aggregate_result
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mock_row_count_checker.check = mock_check_row_count
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mock_schema_checker.check = mock_check_schema
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mock_aggregate_checker.check = mock_check_aggregate
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# Create table mock
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table = TableInfo(
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schema="dbo",
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name="TestTable",
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enabled=True,
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expected_in_target=True,
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aggregate_columns=["Amount", "Quantity"]
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)
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# Test parallel execution timing
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start = time.time()
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results = {}
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checkers = [
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("row_count", mock_row_count_checker),
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("schema", mock_schema_checker),
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("aggregate", mock_aggregate_checker)
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]
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with ThreadPoolExecutor(max_workers=3) as executor:
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futures = {
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executor.submit(lambda c: c[1].check(table), c): c[0]
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for c in checkers
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}
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for future in futures:
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name = futures[future]
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results[name] = future.result()
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elapsed = time.time() - start
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# Verify results
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assert len(results) == 3
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assert results["row_count"].status == Status.PASS
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assert results["schema"].status == Status.PASS
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assert results["aggregate"].status == Status.PASS
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# Verify parallel execution (should be ~0.05s, not 0.15s if sequential)
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assert elapsed < 0.15, f"Expected parallel execution but took {elapsed:.2f}s"
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def test_fail_fast_on_error(self):
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"""Test that parallel execution cancels remaining checkers on error."""
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from drt.models.results import CheckResult
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from drt.models.enums import Status, CheckType
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# Mock checkers where second one fails
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mock_checker1 = Mock()
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mock_checker2 = Mock()
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mock_checker3 = Mock()
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result1 = CheckResult(
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check_type=CheckType.ROW_COUNT,
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status=Status.PASS,
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message="OK"
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)
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result2 = CheckResult(
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check_type=CheckType.SCHEMA,
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status=Status.ERROR,
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message="Database connection failed"
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)
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call_count = {"checker1": 0, "checker2": 0, "checker3": 0}
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def mock_check1(table):
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call_count["checker1"] += 1
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time.sleep(0.05)
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return result1
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def mock_check2(table):
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call_count["checker2"] += 1
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time.sleep(0.05)
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return result2
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def mock_check3(table):
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call_count["checker3"] += 1
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time.sleep(0.05)
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return CheckResult(check_type=CheckType.AGGREGATE, status=Status.PASS, message="OK")
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mock_checker1.check = mock_check1
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mock_checker2.check = mock_check2
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mock_checker3.check = mock_check3
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# Run with fail-fast
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from drt.models.table import TableInfo
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table = TableInfo(schema="dbo", name="TestTable", enabled=True)
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results = {}
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checkers = [
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("row_count", mock_checker1),
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("schema", mock_checker2),
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("aggregate", mock_checker3)
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]
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with ThreadPoolExecutor(max_workers=3) as executor:
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futures = {
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executor.submit(lambda c: c[1].check(table), c): c[0]
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for c in checkers
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}
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for future in futures:
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name = futures[future]
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try:
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result = future.result()
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results[name] = result
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if result.status == Status.ERROR:
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# Cancel remaining
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for f in futures:
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f.cancel()
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break
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except Exception:
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pass
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# Verify that we got at least one result
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assert len(results) >= 1
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if __name__ == "__main__":
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pytest.main([__file__, "-v"])
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