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PERF: Speed up output-converter batching and add CI coverage - #852
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Jahnvi Thakkar (jahnvi480) wants to merge 2 commits into
Open
Jahnvi Thakkar (jahnvi480) wants to merge 2 commits into
Jahnvi Thakkar (jahnvi480) wants to merge 2 commits into
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Co-authored-by: Copilot App <223556219+Copilot@users.noreply.github.com>
PR Performance Report✅ Performance improved2 database tasks consistently improved across 2 measured environments. No consistent slowdowns were detected. 2 IMPROVEMENTS 0 SLOWDOWNS 2/2 ENVIRONMENTS Signal fingerprint
Coverage: 2 of 2 environments completed. Advisory result; does not block merging. Measured timings
Performance diagnosticsPhase times are inclusive diagnostics and must not be added together. They identify where measured time changed, not why it changed. Unix / SQL Server 202210,000 output-converted rows / fetchall(): py::fetchall::row_wrap -7.447 ms; ddbc::FetchBatchData::SQLFetchScroll_call -0.258 ms; py::fetchall::cpp_call -0.182 ms. Unix / SQL Server 202510,000 output-converted rows / fetchall(): py::fetchall::row_wrap -7.737 ms; ddbc::FetchBatchData::SQLFetchScroll_call -0.208 ms; py::fetchall::cpp_call -0.201 ms. All database tasks and timingsUnix / SQL Server 2022
Unix / SQL Server 2025
Build and measurement detailsPR head:
A consistent change requires more than 20% median paired movement, at least 1 ms between the median runtimes, and at least 80% of pairs exceeding the relative threshold in the same direction. A slowdown without enough pair agreement is reported as inconsistent. The displayed change is the median of paired before-and-after ratios. It is not recalculated from the two displayed median runtimes. Both revisions use profiling-enabled builds on the same agent and database, with alternating order and discarded warmups. Results are diagnostic and do not represent production-wheel latency. Raw samples and logs are attached to the ADO run as |
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🔵 Needs a closer look
Native ownership and dispatch changes require human review, with performance qualification on HOLD and cross-platform validation still limited.
No open issues 🎉
What changed in this PR
Optimizes output-converter fetching across the Python and native driver layers and adds CI benchmark coverage. The change remains draft-only and performance qualification is on HOLD.
Changes:
- Retains owned UTF-16LE bytes and adds guarded native Row construction.
- Adds converter correctness, fallback, mutation, ownership, and dispatch tests.
- Adds two converter-fetch benchmarks, expanding the registry to 24 tasks without changing comparison thresholds.
| File | Description |
|---|---|
| tests/test_output_converter_bytes.py | Tests converter semantics, ownership, and native dispatch. |
| tests/test_036_profiler_ci.py | Tests benchmark boundaries, cleanup, and reporting. |
| mssql_python/row.py | Delegates list-based conversion to native code. |
| mssql_python/pybind/output_converter.hpp | Implements owned text, conversion, and guarded Row construction. |
| mssql_python/pybind/ddbc_bindings.h | Adds deferred text handling to column processors. |
| mssql_python/pybind/ddbc_bindings.cpp | Passes converter maps through fetches and exposes helpers. |
| mssql_python/cursor.py | Integrates native converter paths and fallbacks. |
| eng/profiler_benchmarks/workloads.py | Adds fetchall and fetchmany converter workloads. |
| eng/profiler_benchmarks/report.py | Adds readable benchmark report labels. |
| eng/profiler_benchmarks/README.md | Documents workloads and measurement boundaries. |
Review effort: Balanced
📊 Code Coverage Report
Diff CoverageDiff: main...HEAD, staged and unstaged changes
Summary
mssql_python/pybind/ddbc_bindings.cppLines 3642-3650 3642 py::object text;
3643 if (OutputConverters::enabled(converters, i - 1))
3644 text = OutputConverters::text(textData, textSize);
3645 row.append(text ? text
! 3646 : FetchText::from_utf16_native(textData, textSize));
3647 LOG("SQLGetData: CHAR column %d fetched as WCHAR, "
3648 "length=%lu",
3649 i, (unsigned long)numCharsInData);
3650 } else {Lines 3822-3835 3822 // omits the terminator.
3823 const char* textData =
3824 reinterpret_cast<const char*>(dataBuffer.data());
3825 Py_ssize_t textSize =
! 3826 static_cast<Py_ssize_t>(numCharsInData * sizeof(SQLWCHAR));
! 3827 py::object text;
! 3828 if (dataType != SQL_SS_VARIANT &&
! 3829 OutputConverters::enabled(converters, i - 1))
! 3830 text = OutputConverters::text(textData, textSize);
! 3831 row.append(text ? text
3832 : FetchText::from_utf16_native(textData, textSize));
3833 LOG("SQLGetData: Appended NVARCHAR string "
3834 "length=%lu for column %d",
3835 (unsigned long)numCharsInData, i);Lines 4481-4489 4481 SQLRETURN FetchBatchData(SQLHSTMT hStmt, ColumnBuffers& buffers, const Metadata& columnNames,
4482 py::list& rows, SQLUSMALLINT numCols, SQLULEN& numRowsFetched,
4483 const std::vector<SQLUSMALLINT>& lobColumns,
4484 const std::string& charEncoding = "utf-16le", int charCtype = SQL_C_WCHAR,
! 4485 py::handle messages = {}, py::handle converters = {}) {
4486 PERF_TIMER("FetchBatchData");
4487 LOG("FetchBatchData: Fetching data in batches");
4488 SQLRETURN ret;
4489 {mssql_python/pybind/output_converter.hppLines 62-70 62 for (Py_ssize_t i = 0; i < PyList_GET_SIZE(values.ptr()); ++i) {
63 if (raw_text(PyList_GET_ITEM(values.ptr(), i))) {
64 py::object value = original(py::handle(PyList_GET_ITEM(values.ptr(), i)));
65 if (PyList_SetItem(values.ptr(), i, value.release().ptr()) < 0)
! 66 throw py::error_already_set();
67 }
68 }
69 return values;
70 }Lines 108-116 108 if (!replaced && i < PyList_GET_SIZE(result.ptr()) &&
109 raw_text(PyList_GET_ITEM(result.ptr(), i))) {
110 py::object restored = original(py::handle(PyList_GET_ITEM(result.ptr(), i)));
111 if (PyList_SetItem(result.ptr(), i, restored.release().ptr()) < 0)
! 112 throw py::error_already_set();
113 }
114 }
115 for (; i < PyList_GET_SIZE(result.ptr()); ++i) {
116 if (raw_text(PyList_GET_ITEM(result.ptr(), i))) {Lines 115-123 115 for (; i < PyList_GET_SIZE(result.ptr()); ++i) {
116 if (raw_text(PyList_GET_ITEM(result.ptr(), i))) {
117 py::object restored = original(py::handle(PyList_GET_ITEM(result.ptr(), i)));
118 if (PyList_SetItem(result.ptr(), i, restored.release().ptr()) < 0)
! 119 throw py::error_already_set();
120 }
121 }
122 return py::reinterpret_borrow<py::list>(result);
123 }Lines 201-211 201 return false;
202 PyObject* current_apply = PyDict_GetItemWithError(
203 PyModule_GetDict(bindings_.ptr()), apply_name_.ptr());
204 if (!current_apply) {
! 205 if (PyErr_Occurred()) throw py::error_already_set();
! 206 return false;
! 207 }
208 if (current_apply != apply_.ptr()) return false;
209 // Changing function.__code__ does not invalidate the owning type's tag.
210 for (size_t i = 0; i < code_.size(); ++i) {
211 if (code_[i] && PyFunction_GetCode(hooks_[i].ptr()) != code_[i].ptr())Lines 240-254 240 for (Py_ssize_t i = 0; i < PyList_GET_SIZE(rows_data.ptr()); ++i) {
241 py::object values = borrow(PyList_GET_ITEM(rows_data.ptr(), i));
242 PyObject* selected = PyDict_GetItemWithError(cursor_globals.ptr(), row_name_.ptr());
243 if (!selected) {
! 244 if (!PyErr_Occurred()) PyErr_SetString(PyExc_NameError, "name 'Row' is not defined");
! 245 throw py::error_already_set();
! 246 }
247 py::object row_class = borrow(selected);
248 py::object names = cursor.attr("_cached_result_columns");
249 if (!PyList_Check(values.ptr()))
! 250 throw py::type_error("native converter rows must contain lists");
251 result.append(construct(py::reinterpret_borrow<py::list>(values), row_class, converters,
252 column_map, cursor, uuid_indices, lower_map, names));
253 }
254 return result;📋 Files Needing Attention📉 Files with overall lowest coverage (click to expand)mssql_python.pybind.performance_counter.hpp: 0.7%
mssql_python.pybind.logger_bridge.cpp: 57.9%
mssql_python.pybind.ddbc_bindings.h: 65.1%
mssql_python.pybind.logger_bridge.hpp: 70.8%
mssql_python.pybind.ddbc_bindings.cpp: 80.1%
mssql_python.pybind.connection.connection_pool.cpp: 81.3%
mssql_python.pybind.connection.connection.cpp: 82.5%
mssql_python.logging.py: 86.2%
mssql_python.pooling.py: 90.1%
mssql_python.pybind.fetch_temporal.hpp: 92.1%🔗 Quick Links
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Jahnvi Thakkar (jahnvi480)
marked this pull request as ready for review
October 19, 2026 05:17
Jahnvi Thakkar (jahnvi480)
changed the title
Contributor
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🔵 Needs a closer look
The intertwined native allocation, ownership, and fetch changes require rebuilt-extension, native lifetime, and live SQL Server validation across supported Python/platform combinations, which could not be performed in this review environment.
No open issues 🎉
Review effort: Balanced
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Work Item / Issue Reference
Summary
Reduces the overhead of fetching rows with output converters, without changing the public API.
Rowbehavior.fetchall()andfetchmany(1000).Local profiling-OFF benchmarks showed about 33% lower batch-fetch time than pinned main. The
fetchone()improvement target and faster-than-pyodbc target remain unmet.