e2e-examples/gcs/benchmark_analysis/analyze_peer.py (77 lines of code) (raw):
#!/usr/bin/env python3
# Copyright 2022 gRPC authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import csv
import json
import re
import sys
import datetime
from dataclasses import dataclass, field, asdict
def clean_json(s):
s = re.sub(",[ \t\r\n]+}", "}", s)
s = re.sub(",[ \t\r\n]+\]", "]", s)
return s
@dataclass
class PeerData:
start_time: datetime.datetime = datetime.datetime(1900, 1, 1)
end_time: datetime.datetime = datetime.datetime(1900, 1, 1)
read_count: int = 0
read_bytes: int = 0
time_map: dict = field(default_factory=dict)
@dataclass
class TimeData:
read_count: int = 0
read_bytes: int = 0
def apply_chunks(d, chunks):
tset = set()
for c in chunks:
t = datetime.datetime.fromisoformat(c["time"][:19])
tset.add(t)
b = c["bytes"]
d.read_bytes += b
d.time_map.setdefault(t, TimeData()).read_bytes += b
d.read_count += 1
for t in tset:
d.time_map[t].read_count += 1
def transform(args):
peer_map = {}
with open(args.file) as f:
j = json.loads(clean_json(f.read()), strict=False)
for op in j["operations"]:
status = op["status"]
if status != 0:
continue
peer = op["peer"]
d = peer_map.setdefault(peer, PeerData())
apply_chunks(d, op["chunks"])
rows = []
ts = min(min(v.time_map.keys()) for v in peer_map.values())
te = max(max(v.time_map.keys()) for v in peer_map.values())
tc = ts
while tc <= te:
row = { "Time": tc.isoformat()}
total_count = 0
total_bytes = 0
for i, p in enumerate(peer_map.values()):
td = p.time_map.get(tc, None)
if td:
row["c" + str(i + 1)] = td.read_count
row["t" + str(i + 1)] = td.read_bytes
total_count += td.read_count
total_bytes += td.read_bytes
row["c_all"] = total_count
row["t_all"] = total_bytes
rows.append(row)
tc += datetime.timedelta(seconds=1)
fields = ['Time', 'c_all', 't_all']
for i in range(len(peer_map)):
fields.append("c" + str(i + 1))
fields.append("t" + str(i + 1))
w = csv.DictWriter(sys.stdout, fields, delimiter='\t')
w.writeheader()
w.writerows(rows)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("file", help="the path of report file")
args = parser.parse_args()
transform(args)
if __name__ == "__main__":
main()