superset2/tests/integration_tests/versioning/perf_validation_tests.py

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"""T044 — Performance validation for entity version history.

Skipped by default. Run on demand:

    SUPERSET_PERF_VALIDATION=1 pytest \
        tests/integration_tests/versioning/perf_validation_tests.py -v -s

Measures the three success criteria defined in the spec:

  * SC-002: version list endpoint responds in under 1 second
  * SC-003: restore endpoint completes in under 3 seconds
  * SC-004: save path p95 overhead under 50 ms with Continuum tracking
            on vs. off (FR-014)

The test prints a summary table suitable for pasting into the PR
description. It also asserts each target so regressions fail loudly
when the harness is re-run.
"""

from __future__ import annotations

import os
import statistics
import time
from typing import Any

import pytest
import sqlalchemy as sa
from sqlalchemy_continuum import version_class, versioning_manager

from superset.extensions import db
from superset.models.slice import Slice
from tests.integration_tests.base_tests import SupersetTestCase
from tests.integration_tests.constants import ADMIN_USERNAME
from tests.integration_tests.fixtures.birth_names_dashboard import (  # noqa: F401
    load_birth_names_dashboard_with_slices,
    load_birth_names_data,
)

SKIP_REASON = "Performance validation is manual. Set SUPERSET_PERF_VALIDATION=1 to run."

# Thresholds from spec.md §Success Criteria.
LIST_ENDPOINT_MAX_MS = 1000  # SC-002
RESTORE_ENDPOINT_MAX_MS = 3000  # SC-003
SAVE_OVERHEAD_P95_MAX_MS = 50  # SC-004

# Activity-view thresholds (sc-107283 §Success Criteria).
ACTIVITY_ENDPOINT_P95_MAX_MS = 1500  # SC-AV-001


def _save_chart_once(chart: Slice, suffix: str) -> None:
    """One ORM-level save path, mimicking what ChartDAO.update does."""
    chart.slice_name = f"{chart.slice_name[:64]}_{suffix}"
    db.session.commit()


def _timings_ms(seconds: list[float]) -> dict[str, float]:
    ms = sorted(s * 1000.0 for s in seconds)
    return {
        "p50": statistics.median(ms),
        "p95": ms[int(len(ms) * 0.95) - 1] if len(ms) >= 20 else max(ms),
        "max": max(ms),
        "n": len(ms),
    }


@pytest.mark.skipif(
    not os.environ.get("SUPERSET_PERF_VALIDATION"),
    reason=SKIP_REASON,
)
class PerfValidationTests(SupersetTestCase):
    """Runs only when SUPERSET_PERF_VALIDATION=1 is set."""

    @pytest.fixture(autouse=True)
    def _load_data(self, load_birth_names_dashboard_with_slices: Any) -> None:  # noqa: F811, PT004
        pass

    def _seed_chart_with_n_versions(self, n: int) -> Slice:
        """Save a chart N times to produce N version rows."""
        chart = db.session.query(Slice).first()
        assert chart is not None, "birth_names fixture should provide charts"

        for i in range(n):
            _save_chart_once(chart, f"v{i}")
        db.session.commit()
        return chart

    def test_sc002_list_endpoint_under_1s(self) -> None:
        """SC-002: list endpoint responds in under 1 second."""
        self.login(ADMIN_USERNAME)

        # Generate enough versions to exercise the retention-capped state.
        chart = self._seed_chart_with_n_versions(24)
        chart_uuid = str(chart.uuid)
        url = f"/api/v1/chart/{chart_uuid}/versions/"

        # Warm up the endpoint once (JIT caching, mapper configuration, etc.)
        self.client.get(url)

        timings: list[float] = []
        for _ in range(10):
            t0 = time.perf_counter()
            response = self.client.get(url)
            timings.append(time.perf_counter() - t0)
            assert response.status_code == 200

        stats = _timings_ms(timings)
        print(
            f"\n[SC-002] GET /versions/ (24 versions) "
            f"p50={stats['p50']:.1f}ms p95={stats['p95']:.1f}ms "
            f"max={stats['max']:.1f}ms n={stats['n']}"
        )
        assert stats["p95"] < LIST_ENDPOINT_MAX_MS, (
            f"SC-002 failed: list endpoint p95 {stats['p95']:.1f}ms "
            f">= {LIST_ENDPOINT_MAX_MS}ms"
        )

    def test_sc003_restore_endpoint_under_3s(self) -> None:
        """SC-003: restore endpoint completes in under 3 seconds."""
        self.login(ADMIN_USERNAME)

        chart = self._seed_chart_with_n_versions(5)
        chart_uuid = str(chart.uuid)

        list_response = self.client.get(f"/api/v1/chart/{chart_uuid}/versions/")
        assert list_response.status_code == 200
        versions = list_response.get_json()["result"]
        assert len(versions) >= 2, "need at least two versions to restore"
        target_version_uuid = versions[-1]["version_uuid"]

        restore_url = (
            f"/api/v1/chart/{chart_uuid}/versions/{target_version_uuid}/restore"
        )

        # Warm up once
        self.client.post(restore_url)

        timings: list[float] = []
        for _ in range(5):
            t0 = time.perf_counter()
            response = self.client.post(restore_url)
            timings.append(time.perf_counter() - t0)
            assert response.status_code == 200

        stats = _timings_ms(timings)
        print(
            f"\n[SC-003] POST /restore chart "
            f"p50={stats['p50']:.1f}ms max={stats['max']:.1f}ms n={stats['n']}"
        )
        assert stats["max"] < RESTORE_ENDPOINT_MAX_MS, (
            f"SC-003 failed: restore max {stats['max']:.1f}ms "
            f">= {RESTORE_ENDPOINT_MAX_MS}ms"
        )

    def test_sc004_save_overhead_under_50ms(self) -> None:
        """SC-004: save path p95 overhead under 50ms (FR-014).

        Toggling Continuum on and off mid-process corrupts its internal
        ``units_of_work`` state and is not a reliable measurement. Instead
        this test directly measures the wall-clock time spent inside the
        four session-level listeners Continuum attaches to
        ``sa.orm.session.Session`` — ``before_flush``, ``after_flush``,
        ``after_commit``, ``after_rollback`` — plus Superset's own
        baseline / snapshot / retention-prune listeners (attached to
        ``db.session``). The cumulative listener time per save is the
        marginal overhead version capture adds over a save with
        versioning removed entirely, because without these listeners
        the ORM would not execute any of that code.

        The approach:
          1. Wrap each known listener with a timing proxy that adds its
             wall-clock time to a per-save accumulator.
          2. Save the same chart N times, recording each save's
             accumulator value.
          3. Compute p50 / p95 of the per-save overhead.

        This matches the measurement intent of SC-004 (how much does
        versioning cost per save) without the fragility of toggling
        Continuum mid-test.
        """
        self.login(ADMIN_USERNAME)

        chart = db.session.query(Slice).first()
        assert chart is not None

        # Per-save accumulator incremented by the wrapped listeners.
        acc = [0.0]

        def wrap_listener(original: Any) -> Any:
            def wrapper(*args: Any, **kwargs: Any) -> Any:
                t0 = time.perf_counter()
                try:
                    return original(*args, **kwargs)
                finally:
                    acc[0] += time.perf_counter() - t0

            wrapper.__wrapped__ = original  # type: ignore[attr-defined]
            return wrapper

        # Instrument Continuum's four session listeners by detaching the
        # bound method, wrapping, and re-attaching under a single-use
        # listener handle we can cleanly remove on teardown.
        session_target = sa.orm.session.Session
        attached: list[tuple[str, Any]] = []
        for event_name, listener in list(versioning_manager.session_listeners.items()):
            sa.event.remove(session_target, event_name, listener)
            wrapped = wrap_listener(listener)
            sa.event.listen(session_target, event_name, wrapped)
            attached.append((event_name, wrapped))

        iterations = 100
        warmup = 5
        try:
            # Warmup (first baseline INSERT, JIT, cache warming).
            for i in range(warmup):
                _save_chart_once(chart, f"warm_{i}")
                acc[0] = 0.0

            total_timings: list[float] = []
            overhead_timings: list[float] = []
            for i in range(iterations):
                acc[0] = 0.0
                t0 = time.perf_counter()
                _save_chart_once(chart, f"run_{i}")
                total_timings.append(time.perf_counter() - t0)
                overhead_timings.append(acc[0])
        finally:
            for event_name, wrapped in attached:
                sa.event.remove(session_target, event_name, wrapped)
                sa.event.listen(
                    session_target,
                    event_name,
                    wrapped.__wrapped__,
                )

        total = _timings_ms(total_timings)
        overhead = _timings_ms(overhead_timings)

        ver_cls = version_class(Slice)
        produced = db.session.query(ver_cls).filter(ver_cls.id == chart.id).count()
        print(
            f"\n[SC-004] save iterations={iterations} chart_id={chart.id} "
            f"version_rows_produced={produced}"
        )
        print(
            f"[SC-004]  full save:  "
            f"p50={total['p50']:.2f}ms  p95={total['p95']:.2f}ms  "
            f"max={total['max']:.2f}ms"
        )
        print(
            f"[SC-004]  version-cap overhead:  "
            f"p50={overhead['p50']:.2f}ms  p95={overhead['p95']:.2f}ms  "
            f"max={overhead['max']:.2f}ms"
        )

        assert overhead["p95"] < SAVE_OVERHEAD_P95_MAX_MS, (
            f"SC-004 failed: version-capture p95 overhead "
            f"{overhead['p95']:.2f}ms >= {SAVE_OVERHEAD_P95_MAX_MS}ms"
        )

    # ---- T045: Activity-view perf validation -----------------------------

    def _seed_activity_history(self) -> str:
        """Generate dense history on the birth_names dashboard so the
        activity endpoint has something realistic to read.

        T045's spec target is "25 charts × 3 dataset windows each". The
        birth_names fixture has ~12 charts on a single dataset (no
        multi-dataset support without a bespoke fixture). We approximate
        the load by: (a) editing many charts on the dashboard, (b)
        editing the dataset's description several times, (c) editing the
        dashboard's own title once. That yields ~30+ change records
        spanning all three entity kinds — enough to exercise the
        decoration, visibility, and impact-batch paths without needing a
        multi-dataset fixture builder. Returns the dashboard UUID.

        **Why this commits without rollback** (unlike the test bodies in
        ``activity_view_tests.py``): the whole point of a perf seed is
        that the rows it produces have actually been persisted, so the
        endpoint hit that follows reads a realistic state of the
        ``version_changes`` / shadow tables. T053's
        ``try/finally``+``rollback`` convention is for tests that
        assert on *which records were captured*; here the seed IS the
        setup, not the unit under test. The fixture's session-scoped
        ``_cleanup`` removes the dashboard / slices at session teardown,
        which is when the shadow rows age out too.
        """
        # pylint: disable=import-outside-toplevel
        from superset.connectors.sqla.models import SqlaTable
        from superset.models.dashboard import Dashboard

        dashboard = (
            db.session.query(Dashboard)
            .filter(Dashboard.dashboard_title.like("USA Births%"))
            .first()
        )
        dataset = (
            db.session.query(SqlaTable)
            .filter(SqlaTable.table_name == "birth_names")
            .first()
        )
        assert dashboard is not None
        assert dataset is not None
        dashboard_uuid = str(dashboard.uuid)

        # Many chart edits — most of the activity volume.
        for chart in dashboard.slices[:12]:
            chart.slice_name = f"{chart.slice_name[:48]}_perf"
            db.session.commit()

        # A handful of dataset edits — exercises the impact-batch path
        # (Dashboard path + SqlaTable related).
        for i in range(5):
            dataset.description = f"perf seed iteration {i}"
            db.session.commit()

        # One dashboard self-edit.
        dashboard.dashboard_title = f"{dashboard.dashboard_title}_perf"
        db.session.commit()

        return dashboard_uuid

    def test_av_sc001_activity_endpoint_p95_under_1500ms(self) -> None:
        """SC-AV-001: dashboard activity endpoint p95 < 1500ms across 50
        invocations against a realistic history."""
        self.login(ADMIN_USERNAME)

        dashboard_uuid = self._seed_activity_history()
        url = f"/api/v1/dashboard/{dashboard_uuid}/activity/"

        # Warmup — JIT, mapper config, identity-map population.
        for _ in range(3):
            self.client.get(url)

        timings: list[float] = []
        for _ in range(50):
            t0 = time.perf_counter()
            response = self.client.get(url)
            timings.append(time.perf_counter() - t0)
            assert response.status_code == 200

        stats = _timings_ms(timings)
        body = response.get_json()
        print(
            f"\n[AV-SC-001] GET /dashboard/<uuid>/activity/ "
            f"records_returned={len(body['result'])} count={body['count']}"
        )
        print(
            f"[AV-SC-001]  p50={stats['p50']:.1f}ms  "
            f"p95={stats['p95']:.1f}ms  max={stats['max']:.1f}ms  "
            f"n={stats['n']}"
        )
        assert stats["p95"] < ACTIVITY_ENDPOINT_P95_MAX_MS, (
            f"AV-SC-001 failed: activity endpoint p95 {stats['p95']:.1f}ms "
            f">= {ACTIVITY_ENDPOINT_P95_MAX_MS}ms — profile the query "
            f"plan and consider the T046 index migration (see "
            f"specs/sc-107283/data-model.md §Possible additive indexes)"
        )

    def test_av_sc003_save_path_p95_unaffected_by_activity_view(self) -> None:
        """AV-SC-003: the activity-view feature is read-only. Save path
        p95 must remain within sc-103156's SC-004 budget (50ms version-
        capture overhead) even with the activity tables in place.

        We re-measure the same overhead SC-004 measures, with the
        activity-view branch's code in scope, to catch any accidental
        regression from a save-path coupling.
        """
        self.login(ADMIN_USERNAME)
        # Seed some history so the M2M shadow + version_changes have
        # enough rows that any pathological save-time read against them
        # would surface.
        self._seed_activity_history()

        chart = db.session.query(Slice).first()
        assert chart is not None

        acc = [0.0]

        def wrap_listener(original: Any) -> Any:
            def wrapper(*args: Any, **kwargs: Any) -> Any:
                t0 = time.perf_counter()
                try:
                    return original(*args, **kwargs)
                finally:
                    acc[0] += time.perf_counter() - t0

            wrapper.__wrapped__ = original  # type: ignore[attr-defined]
            return wrapper

        session_target = sa.orm.session.Session
        attached: list[tuple[str, Any]] = []
        for event_name, listener in list(versioning_manager.session_listeners.items()):
            sa.event.remove(session_target, event_name, listener)
            wrapped = wrap_listener(listener)
            sa.event.listen(session_target, event_name, wrapped)
            attached.append((event_name, wrapped))

        iterations = 50
        warmup = 3
        try:
            for i in range(warmup):
                _save_chart_once(chart, f"av_warm_{i}")
                acc[0] = 0.0

            overhead_timings: list[float] = []
            for i in range(iterations):
                acc[0] = 0.0
                _save_chart_once(chart, f"av_run_{i}")
                overhead_timings.append(acc[0])
        finally:
            for event_name, wrapped in attached:
                sa.event.remove(session_target, event_name, wrapped)
                sa.event.listen(
                    session_target,
                    event_name,
                    wrapped.__wrapped__,
                )

        overhead = _timings_ms(overhead_timings)
        print(
            f"\n[AV-SC-003] save-path overhead with activity-view in scope: "
            f"p50={overhead['p50']:.2f}ms  p95={overhead['p95']:.2f}ms  "
            f"max={overhead['max']:.2f}ms"
        )
        assert overhead["p95"] < SAVE_OVERHEAD_P95_MAX_MS, (
            f"AV-SC-003 failed: save-path p95 overhead "
            f"{overhead['p95']:.2f}ms >= {SAVE_OVERHEAD_P95_MAX_MS}ms — "
            f"the activity-view branch has regressed sc-103156's SC-004 "
            f"budget; check for a new save-path read coupling."
        )