c6269ad3dd
The subscriber was pinned to DEBUG, so RUST_LOG=warn was ignored and sqlx logged every statement to stderr in production. Now an EnvFilter defaults to info with sqlx at warn; RUST_LOG=debug restores the query log. Three benchmarks, so the hosting numbers come from measurement rather than guesswork: scripts/bench.py for latency and throughput, bench_write.py for the autosave and submit path under concurrent students, and bench_scale.py which builds a database at the real bank's size (10,905 questions, 2,000 students, 12,000 papers, 900k answers) to report disk cost and query timings.
68 lines
No EOL
1.9 KiB
Python
Executable file
68 lines
No EOL
1.9 KiB
Python
Executable file
#!/usr/bin/env python3
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"""Load check for the PYQ server.
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scripts/bench.py <base-url> [requests] [concurrency]
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Reports latency percentiles per route and sustained throughput under load.
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"""
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import http.cookiejar
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import statistics
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import sys
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import time
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import urllib.request
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from concurrent.futures import ThreadPoolExecutor
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BASE = sys.argv[1] if len(sys.argv) > 1 else "http://127.0.0.1:8171"
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N = int(sys.argv[2]) if len(sys.argv) > 2 else 300
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CONC = int(sys.argv[3]) if len(sys.argv) > 3 else 20
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jar = http.cookiejar.CookieJar()
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opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(jar))
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def sign_in():
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body = b"name=Bench&email=bench@example.com&next=/build"
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req = urllib.request.Request(f"{BASE}/student", data=body, method="POST")
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opener.open(req).read()
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def timed(path):
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t0 = time.perf_counter()
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with opener.open(BASE + path) as r:
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r.read()
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return (time.perf_counter() - t0) * 1000
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def percentile(values, p):
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s = sorted(values)
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return s[min(int(len(s) * p), len(s) - 1)]
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def report(path, samples):
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print(
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f" {path:<22} n={len(samples):<5} "
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f"p50={statistics.median(samples):6.2f}ms "
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f"p95={percentile(samples, .95):6.2f}ms "
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f"max={max(samples):6.2f}ms"
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)
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def load(path, concurrency):
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t0 = time.perf_counter()
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with ThreadPoolExecutor(max_workers=concurrency) as pool:
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list(pool.map(lambda _: timed(path), range(N)))
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return N / (time.perf_counter() - t0)
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sign_in()
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print(f"=== {BASE} | {N} requests | {CONC} parallel ===")
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print("sequential latency")
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for p in ["/", "/static/style.css", "/build", "/dashboard", "/history"]:
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report(p, [timed(p) for _ in range(min(N, 50))])
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print(f"throughput at {CONC} concurrent")
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for p in ["/", "/build"]:
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warm = [timed(p) for _ in range(CONC * 2)]
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rps = load(p, CONC)
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report(p, warm)
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print(f" -> {p:<20} {rps:,.0f} req/s sustained") |