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bench_js.py
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bench_js.py
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#!/usr/bin/env python3
#
# Copyright (c) 2019 MagicStack Inc.
# All rights reserved.
#
# See LICENSE for details.
##
import json
import pathlib
import subprocess
import typing
import numpy as np
import _shared
class Result(typing.NamedTuple):
benchmark: str
queryname: str
nqueries: int
duration: int
min_latency: int
avg_latency: int
max_latency: int
latency_stats: typing.List[int]
samples: typing.List[str]
def print_result(ctx, result: Result):
print(f'== {result.benchmark} : {result.queryname} ==')
print(f'queries:\t{result.nqueries}')
print(f'qps:\t\t{result.nqueries // ctx.duration} q/s')
print(f'min latency:\t{result.min_latency / 100:.2f}ms')
print(f'avg latency:\t{result.avg_latency / 100:.2f}ms')
print(f'max latency:\t{result.max_latency / 100:.2f}ms')
print()
def run_query(ctx, benchmark, queryname):
dirn = pathlib.Path(__file__).resolve().parent
exe = dirn / 'jsbench.js'
opts = [
'--concurrency', ctx.concurrency,
'--duration', ctx.duration,
'--timeout', ctx.timeout,
'--warmup-time', ctx.warmup_time,
'--output-format', 'json',
'--host', ctx.db_host,
'--nsamples', 10,
'--number-of-ids', ctx.number_of_ids,
'--query', queryname,
]
if benchmark.startswith('edgedb'):
opts.extend(('--port', ctx.edgedb_port))
else:
opts.extend(('--port', ctx.pg_port))
# If we're running Prisma benchmark we need to update the `.env`
# file with the pool size and timeout info.
if benchmark == 'prisma_untuned':
with open('_prisma/.env', 'wt') as f:
f.write(
f'DATABASE_URL="postgresql://postgres_bench:edgedbbenchmark@'
f'localhost:15432/postgres_bench'
f'?schema=public'
f'&connection_limit={ctx.concurrency}'
f'&pool_timeout={ctx.timeout}"')
cmd = [str(c) for c in [exe] opts [benchmark]]
print("Running benchmark...")
print(' '.join(cmd))
try:
proc = subprocess.run(
cmd, text=True, capture_output=True, check=True,
)
except subprocess.CalledProcessError as e:
print(e.stderr)
raise
output = proc.stdout
data = json.loads(output)
avg_latency = np.average(
np.arange(len(data['latency_stats'])),
weights=data['latency_stats'])
return Result(
benchmark=benchmark,
queryname=queryname,
nqueries=data['nqueries'],
duration=data['duration'],
min_latency=data['min_latency'],
avg_latency=avg_latency,
max_latency=data['max_latency'],
latency_stats=data['latency_stats'],
samples=data['samples'],
)
def run_bench(ctx, benchmark):
results = []
for queryname in ctx.queries:
res = run_query(ctx, benchmark, queryname)
results.append(res)
print_result(ctx, res)
return results
def main():
ctx, _ = _shared.parse_args(
prog_desc='EdgeDB Databases Benchmark (JS drivers)',
out_to_json=True)
print('============ JS ============')
print(f'concurrency:\t{ctx.concurrency}')
print(f'warmup time:\t{ctx.warmup_time} seconds')
print(f'duration:\t{ctx.duration} seconds')
print(f'queries:\t{", ".join(q for q in ctx.queries)}')
print(f'benchmarks:\t{", ".join(b for b in ctx.benchmarks)}')
print()
data = []
for benchmark in ctx.benchmarks:
bench_desc = _shared.IMPLEMENTATIONS[benchmark]
if bench_desc.language != 'js':
continue
res = run_bench(ctx, benchmark)
data.append(res)
if ctx.json:
json_data = []
for results in data:
json_results = []
for r in results:
json_results.append({
'queryname': r.queryname,
'nqueries': r.nqueries,
'min_latency': r.min_latency,
'max_latency': r.max_latency,
'latency_stats': [int(i) for i in r.latency_stats],
'samples': r.samples,
})
json_data.append({
'benchmark': results[0].benchmark,
'duration': results[0].duration,
'queries': json_results,
})
data = json.dumps({
'language': 'js',
'concurrency': ctx.concurrency,
'warmup_time': ctx.warmup_time,
'duration': ctx.duration,
'data': json_data,
})
with open(ctx.json, 'wt') as f:
f.write(data)
if __name__ == '__main__':
main()