feat: harden long-range batch queries with redis+parquet caching

2026-03-02 21:04:18 +08:00
parent 2568fd836c
commit fb92579331
40 changed files with 5443 additions and 676 deletions
--- a/tests/test_resource_dataset_cache.py
+++ b/tests/test_resource_dataset_cache.py
@@ -0,0 +1,134 @@
+# -*- coding: utf-8 -*-
+"""Unit tests for resource_dataset_cache — engine integration (task 7.4)."""
+
+from __future__ import annotations
+
+import pandas as pd
+
+from mes_dashboard.services import resource_dataset_cache as cache_svc
+
+
+class TestResourceEngineDecomposition:
+    """7.4 — resource-history with long date range triggers engine."""
+
+    def test_long_range_triggers_engine(self, monkeypatch):
+        """90-day range → engine decomposition activated."""
+        import mes_dashboard.services.batch_query_engine as engine_mod
+
+        engine_calls = {"execute": 0, "merge": 0}
+
+        def fake_execute_plan(chunks, query_fn, **kwargs):
+            engine_calls["execute"] += 1
+            assert len(chunks) == 3  # 90 days / 31 = 3 chunks
+            return kwargs.get("query_hash", "fake_hash")
+
+        result_df = pd.DataFrame({
+            "HISTORYID": [1, 2],
+            "RESOURCEID": ["R1", "R2"],
+        })
+
+        def fake_merge_chunks(prefix, qhash, **kwargs):
+            engine_calls["merge"] += 1
+            return result_df
+
+        monkeypatch.setattr(engine_mod, "execute_plan", fake_execute_plan)
+        monkeypatch.setattr(engine_mod, "merge_chunks", fake_merge_chunks)
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_cached_df",
+            lambda _: None,
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._store_df",
+            lambda *a, **kw: None,
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._load_sql",
+            lambda name: "SELECT 1 FROM dual",
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_filtered_resources_and_lookup",
+            lambda **kw: (
+                [{"RESOURCEID": "R1", "RESOURCENAME": "Machine-1"}],
+                {"R1": {"RESOURCENAME": "Machine-1"}},
+                "h.HISTORYID IN (SELECT HISTORYID FROM RESOURCEHISTORY)",
+            ),
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_resource_lookup",
+            lambda: {},
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_workcenter_mapping",
+            lambda: {},
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._derive_summary",
+            lambda df, rl, wc, gran: {"total_hours": 100},
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._derive_detail",
+            lambda df, rl, wc: {"items": [], "pagination": {"total": 2}},
+        )
+
+        result = cache_svc.execute_primary_query(
+            start_date="2025-01-01",
+            end_date="2025-03-31",
+            workcenter_groups=["WB"],
+        )
+
+        assert engine_calls["execute"] == 1
+        assert engine_calls["merge"] == 1
+        assert result["query_id"] is not None
+
+    def test_short_range_skips_engine(self, monkeypatch):
+        """30-day range → direct path, no engine."""
+        engine_calls = {"execute": 0}
+
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_cached_df",
+            lambda _: None,
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._load_sql",
+            lambda name: "SELECT 1 FROM dual",
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache.read_sql_df",
+            lambda sql, params: pd.DataFrame({"HISTORYID": [1]}),
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._store_df",
+            lambda *a, **kw: None,
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_filtered_resources_and_lookup",
+            lambda **kw: (
+                [{"RESOURCEID": "R1"}],
+                {"R1": {"RESOURCENAME": "Machine-1"}},
+                "h.HISTORYID IN (SELECT HISTORYID FROM RESOURCEHISTORY)",
+            ),
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_resource_lookup",
+            lambda: {},
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._get_workcenter_mapping",
+            lambda: {},
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._derive_summary",
+            lambda df, rl, wc, gran: {},
+        )
+        monkeypatch.setattr(
+            "mes_dashboard.services.resource_dataset_cache._derive_detail",
+            lambda df, rl, wc: {"items": [], "pagination": {"total": 1}},
+        )
+
+        result = cache_svc.execute_primary_query(
+            start_date="2025-06-01",
+            end_date="2025-06-30",
+            workcenter_groups=["WB"],
+        )
+
+        assert engine_calls["execute"] == 0  # Engine NOT used