phase2: add steady-state matrix runner and report

This commit is contained in:
abbycin 2026-03-03 22:15:40 +08:00
parent 436e81353f
commit f0fd573d96
3 changed files with 267 additions and 0 deletions

View File

@ -36,3 +36,15 @@
- `bash -n scripts/phase1.sh` 通过 - `bash -n scripts/phase1.sh` 通过
- `python3 -m py_compile scripts/phase1_eval.py` 通过 - `python3 -m py_compile scripts/phase1_eval.py` 通过
- 提交:待本阶段 commit - 提交:待本阶段 commit
## Phase 2已完成
- 日期2026-03-03
- 范围:
- 新增 `scripts/phase2.sh`:稳态核心报告矩阵执行器
- `tier-m` 全量:`W1/W2/W3/W4/W6` × `P2/P3` × `threads(1/6/12)` × `repeats(默认5)`
- 可选 `tier-l` 代表集:`RUN_TIER_L_REPRESENTATIVE=1` 启用,默认 `TIER_L_REPEATS=1`
- 新增 `scripts/phase2_report.py`:输出按 case 的 `throughput/p95/p99 median`,并给出慢场景对比表
- 验证:
- `bash -n scripts/phase2.sh` 通过
- `python3 -m py_compile scripts/phase2_report.py` 通过
- 提交:待本阶段 commit

150
scripts/phase2.sh Executable file
View File

@ -0,0 +1,150 @@
#!/usr/bin/env bash
set -euo pipefail
if [ "$#" -lt 1 ] || [ "$#" -gt 2 ]; then
printf "Usage: %s <db_root_under_/nvme> [result_csv]\n" "$0"
exit 1
fi
script_dir="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
root_dir="$(cd -- "${script_dir}/.." && pwd)"
if [[ "$1" != /nvme* ]]; then
printf "db_root must be under /nvme, got: %s\n" "$1" >&2
exit 1
fi
db_root="$1"
result_file="${2:-${script_dir}/phase2_results.csv}"
warmup_secs="${WARMUP_SECS:-120}"
measure_secs="${MEASURE_SECS:-300}"
repeats="${REPEATS:-5}"
read_path="${READ_PATH:-snapshot}"
run_tier_l_rep="${RUN_TIER_L_REPRESENTATIVE:-0}"
tier_l_repeats="${TIER_L_REPEATS:-1}"
mkdir -p "${db_root}"
mkdir -p "$(dirname -- "${result_file}")"
cargo build --release --manifest-path "${root_dir}/Cargo.toml"
(cd "${root_dir}/rocksdb" && cmake --preset release)
(cd "${root_dir}/rocksdb" && cmake --build --preset release)
workloads_tier_m=(W1 W2 W3 W4 W6)
workloads_tier_l_rep=(W1 W3 W6)
threads_tier_m=(1 6 12)
threads_tier_l_rep=(1 12)
profiles=(P2 P3)
profile_key() {
case "$1" in
P2) echo 32 ;;
P3) echo 32 ;;
*) printf "unknown profile: %s\n" "$1" >&2; exit 1 ;;
esac
}
profile_val() {
case "$1" in
P2) echo 1024 ;;
P3) echo 16384 ;;
*) printf "unknown profile: %s\n" "$1" >&2; exit 1 ;;
esac
}
prefill_for() {
local tier="$1"
local profile="$2"
if [ "${tier}" = "tier-m" ]; then
case "${profile}" in
P2) echo 18302417 ;;
P3) echo 1177348 ;;
*) printf "unknown profile: %s\n" "${profile}" >&2; exit 1 ;;
esac
elif [ "${tier}" = "tier-l" ]; then
case "${profile}" in
P2) echo 28470427 ;;
P3) echo 1831430 ;;
*) printf "unknown profile: %s\n" "${profile}" >&2; exit 1 ;;
esac
else
printf "unknown tier: %s\n" "${tier}" >&2
exit 1
fi
}
run_case() {
local engine="$1"
local tier="$2"
local workload="$3"
local profile="$4"
local t="$5"
local repeat="$6"
local key_size value_size prefill_keys run_path
key_size="$(profile_key "${profile}")"
value_size="$(profile_val "${profile}")"
prefill_keys="$(prefill_for "${tier}" "${profile}")"
run_path="$(mktemp -u -p "${db_root}" "${engine}_phase2_${tier}_${workload}_${profile}_t${t}_r${repeat}_XXXXXX")"
printf "[phase2][%s] tier=%s repeat=%s workload=%s profile=%s threads=%s path=%s\n" \
"${engine}" "${tier}" "${repeat}" "${workload}" "${profile}" "${t}" "${run_path}"
if [ "${engine}" = "mace" ]; then
"${root_dir}/target/release/kv_bench" \
--path "${run_path}" \
--workload "${workload}" \
--threads "${t}" \
--key-size "${key_size}" \
--value-size "${value_size}" \
--prefill-keys "${prefill_keys}" \
--warmup-secs "${warmup_secs}" \
--measure-secs "${measure_secs}" \
--shared-keyspace true \
--read-path "${read_path}" \
--result-file "${result_file}"
else
"${root_dir}/rocksdb/build/release/rocksdb_bench" \
--path "${run_path}" \
--workload "${workload}" \
--threads "${t}" \
--key-size "${key_size}" \
--value-size "${value_size}" \
--prefill-keys "${prefill_keys}" \
--warmup-secs "${warmup_secs}" \
--measure-secs "${measure_secs}" \
--read-path "${read_path}" \
--result-file "${result_file}"
fi
}
# tier-m full matrix
for repeat in $(seq 1 "${repeats}"); do
for workload in "${workloads_tier_m[@]}"; do
for profile in "${profiles[@]}"; do
for t in "${threads_tier_m[@]}"; do
run_case mace tier-m "${workload}" "${profile}" "${t}" "${repeat}"
run_case rocksdb tier-m "${workload}" "${profile}" "${t}" "${repeat}"
done
done
done
done
# tier-l representative subset (optional)
if [ "${run_tier_l_rep}" = "1" ]; then
for repeat in $(seq 1 "${tier_l_repeats}"); do
for workload in "${workloads_tier_l_rep[@]}"; do
for profile in "${profiles[@]}"; do
for t in "${threads_tier_l_rep[@]}"; do
run_case mace tier-l "${workload}" "${profile}" "${t}" "${repeat}"
run_case rocksdb tier-l "${workload}" "${profile}" "${t}" "${repeat}"
done
done
done
done
fi
python3 "${script_dir}/phase2_report.py" "${result_file}"
printf "Phase 2 finished. Results: %s\n" "${result_file}"

105
scripts/phase2_report.py Executable file
View File

@ -0,0 +1,105 @@
#!/usr/bin/env python3
import sys
import pandas as pd
def infer_tier(row: pd.Series) -> str:
key = int(row["key_size"])
val = int(row["value_size"])
prefill = int(row["prefill_keys"])
table = {
(32, 1024, 18302417): "tier-m",
(32, 16384, 1177348): "tier-m",
(32, 1024, 28470427): "tier-l",
(32, 16384, 1831430): "tier-l",
}
return table.get((key, val, prefill), "unknown")
def main() -> int:
if len(sys.argv) != 2:
print(f"Usage: {sys.argv[0]} <result_csv>")
return 1
df = pd.read_csv(sys.argv[1])
needed = {
"engine",
"workload_id",
"key_size",
"value_size",
"prefill_keys",
"threads",
"ops_per_sec",
"p95_us",
"p99_us",
}
missing = needed - set(df.columns)
if missing:
raise ValueError(f"Missing columns: {sorted(missing)}")
sub = df[df["workload_id"].isin(["W1", "W2", "W3", "W4", "W6"])].copy()
if sub.empty:
print("No phase2 rows found in csv")
return 0
sub["tier"] = sub.apply(infer_tier, axis=1)
grp_cols = ["tier", "engine", "workload_id", "key_size", "value_size", "threads"]
summary = (
sub.groupby(grp_cols)
.agg(
repeats=("ops_per_sec", "count"),
throughput_median=("ops_per_sec", "median"),
p95_median=("p95_us", "median"),
p99_median=("p99_us", "median"),
)
.reset_index()
)
with pd.option_context("display.max_rows", None, "display.max_columns", None):
print(summary.to_string(index=False))
# Slow-scenario extraction by throughput median.
piv = summary.pivot_table(
index=["tier", "workload_id", "key_size", "value_size", "threads"],
columns="engine",
values="throughput_median",
aggfunc="first",
).reset_index()
if {"mace", "rocksdb"}.issubset(set(piv.columns)):
piv["slower_engine"] = piv.apply(
lambda r: "mace" if r["mace"] < r["rocksdb"] else "rocksdb",
axis=1,
)
piv["slower_ratio"] = piv.apply(
lambda r: min(r["mace"], r["rocksdb"]) / max(r["mace"], r["rocksdb"])
if max(r["mace"], r["rocksdb"]) > 0
else 0.0,
axis=1,
)
print("\nSlow scenarios (by throughput median):")
print(
piv[
[
"tier",
"workload_id",
"key_size",
"value_size",
"threads",
"mace",
"rocksdb",
"slower_engine",
"slower_ratio",
]
].to_string(index=False)
)
return 0
if __name__ == "__main__":
raise SystemExit(main())