refactor: align benchmark v2 workload protocol

scripts/phase1_eval.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python3
+
+import sys
+import pandas as pd
+
+
+def cv(series: pd.Series) -> float:
+    mean = float(series.mean())
+    if mean == 0:
+        return 0.0
+    return float(series.std(ddof=1) / mean * 100.0)
+
+
+def main() -> int:
+    if len(sys.argv) != 2:
+        print(f"Usage: {sys.argv[0]} <result_csv>")
+        return 1
+
+    result_csv = sys.argv[1]
+    df = pd.read_csv(result_csv)
+
+    needed = {
+        "engine",
+        "workload_id",
+        "key_size",
+        "value_size",
+        "threads",
+        "ops_per_sec",
+        "p99_us",
+    }
+    missing = needed - set(df.columns)
+    if missing:
+        raise ValueError(f"Missing columns: {sorted(missing)}")
+
+    sub = df[df["workload_id"].isin(["W1", "W3", "W6"])].copy()
+    if sub.empty:
+        print("No phase1 rows found in csv")
+        return 0
+
+    grp_cols = ["engine", "workload_id", "key_size", "value_size", "threads"]
+    agg = (
+        sub.groupby(grp_cols)
+        .agg(
+            repeats=("ops_per_sec", "count"),
+            throughput_cv=("ops_per_sec", cv),
+            p99_cv=("p99_us", cv),
+            throughput_median=("ops_per_sec", "median"),
+            p99_median=("p99_us", "median"),
+        )
+        .reset_index()
+    )
+    agg["stable"] = (agg["throughput_cv"] <= 10.0) & (agg["p99_cv"] <= 15.0)
+
+    stable_ratio = float(agg["stable"].mean() * 100.0) if len(agg) > 0 else 0.0
+
+    with pd.option_context("display.max_rows", None, "display.max_columns", None):
+        print(agg.to_string(index=False))
+    print(f"\nStable cases: {stable_ratio:.1f}% ({agg['stable'].sum()}/{len(agg)})")
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())