memgraph/tests/mgbench/compare_results.py

207 lines
7.0 KiB
Python
Executable File

#!/usr/bin/env python3
# Copyright 2021 Memgraph Ltd.
#
# Use of this software is governed by the Business Source License
# included in the file licenses/BSL.txt; by using this file, you agree to be bound by the terms of the Business Source
# License, and you may not use this file except in compliance with the Business Source License.
#
# As of the Change Date specified in that file, in accordance with
# the Business Source License, use of this software will be governed
# by the Apache License, Version 2.0, included in the file
# licenses/APL.txt.
import argparse
import json
FIELDS = [
{
"name": "throughput",
"positive_diff_better": True,
"scaling": 1,
"unit": "QPS",
"diff_treshold": 0.05, # 5%
},
{
"name": "duration",
"positive_diff_better": False,
"scaling": 1,
"unit": "s",
},
{
"name": "parsing_time",
"positive_diff_better": False,
"scaling": 1000,
"unit": "ms",
},
{
"name": "planning_time",
"positive_diff_better": False,
"scaling": 1000,
"unit": "ms",
},
{
"name": "plan_execution_time",
"positive_diff_better": False,
"scaling": 1000,
"unit": "ms",
},
{
"name": "memory",
"positive_diff_better": False,
"scaling": 1 / 1024 / 1024,
"unit": "MiB",
"diff_treshold": 0.02, # 2%
},
]
def load_results(fname):
with open(fname) as f:
return json.load(f)
def compute_diff(value_from, value_to):
if value_from is None:
return {"value": value_to}
diff = (value_to - value_from) / value_from
return {"value": value_to, "diff": diff}
def recursive_get(data, *args, value=None):
for arg in args:
if arg not in data:
return value
data = data[arg]
return data
def compare_results(results_from, results_to, fields, ignored):
ret = {}
for dataset, variants in results_to.items():
for variant, groups in variants.items():
for group, scenarios in groups.items():
if group == "__import__":
continue
for scenario, summary_to in scenarios.items():
if scenario in ignored:
continue
summary_from = recursive_get(results_from, dataset, variant, group, scenario, value={})
if (
len(summary_from) > 0
and summary_to["count"] != summary_from["count"]
or summary_to["num_workers"] != summary_from["num_workers"]
):
raise Exception("Incompatible results!")
testcode = "/".join(
[
dataset,
variant,
group,
scenario,
"{:02d}".format(summary_to["num_workers"]),
]
)
row = {}
performance_changed = False
for field in fields:
key = field["name"]
if key in summary_to:
row[key] = compute_diff(summary_from.get(key, None), summary_to[key])
elif key in summary_to["database"]:
row[key] = compute_diff(
recursive_get(summary_from, "database", key, value=None),
summary_to["database"][key],
)
else:
row[key] = compute_diff(
recursive_get(summary_from, "metadata", key, "average", value=None),
summary_to["metadata"][key]["average"],
)
if "diff" not in row[key] or (
"diff_treshold" in field and abs(row[key]["diff"]) >= field["diff_treshold"]
):
performance_changed = True
if performance_changed:
ret[testcode] = row
return ret
def generate_remarkup(fields, data):
ret = "==== Benchmark summary: ====\n\n"
if len(data) > 0:
ret += "<table>\n"
ret += " <tr>\n"
ret += " <th>Testcode</th>\n"
ret += (
"\n".join(
map(
lambda x: " <th>{}</th>".format(x["name"].replace("_", " ").capitalize()),
fields,
)
)
+ "\n"
)
ret += " </tr>\n"
for testcode in sorted(data.keys()):
ret += " <tr>\n"
ret += " <td>{}</td>\n".format(testcode)
for field in fields:
result = data[testcode][field["name"]]
value = result["value"] * field["scaling"]
if "diff" in result:
diff = result["diff"]
arrow = "arrow-up" if diff >= 0 else "arrow-down"
if not (field["positive_diff_better"] ^ (diff >= 0)):
color = "green"
else:
color = "red"
sign = "{{icon {} color={}}}".format(arrow, color)
ret += ' <td bgcolor="{}">{:.3f}{} ({:+.2%})</td>\n'.format(color, value, field["unit"], diff)
else:
ret += '<td bgcolor="blue">{:.3f}{} //(new)// </td>\n'.format(value, field["unit"])
ret += " </tr>\n"
ret += "</table>\n"
else:
ret += "No performance change detected.\n"
return ret
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Compare results of multiple benchmark runs.")
parser.add_argument(
"--compare",
action="append",
nargs=2,
metavar=("from", "to"),
help="compare results between `from` and `to` files",
)
parser.add_argument("--output", default="", help="output file name")
# file is read line by line, each representing one test name
parser.add_argument("--exclude_tests_file", help="file listing test names to be excluded")
args = parser.parse_args()
if args.compare is None or len(args.compare) == 0:
raise Exception("You must specify at least one pair of files!")
if args.exclude_tests_file:
with open(args.exclude_tests_file, "r") as f:
ignored = [line.rstrip("\n") for line in f]
else:
ignored = []
data = {}
for file_from, file_to in args.compare:
results_from = load_results(file_from)
results_to = load_results(file_to)
data.update(compare_results(results_from, results_to, FIELDS, ignored))
remarkup = generate_remarkup(FIELDS, data)
if args.output:
with open(args.output, "w") as f:
f.write(remarkup)
else:
print(remarkup, end="")