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#!/usr/bin/env python
# Given a JSON file output by pytest-benchmark, this script compares the
# results of a test session with the results stored in elasticsearch.
#
# - iterate through test results in pytest-benchmark JSON file.
#
# - for each one, get mean and stddev of the mean of last 20 results from
# master branch.
#
# - compare the result in the file with the results in elastic.
#
# - if there are bad outliers, exit with status code given in command line.
import argparse
import copy
import json
import requests
import sys
URL = "https://moose.leap.se:9200/benchmark/_search"
BLOCK_SIZE = 20
MULTIPLIER = 1.5
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
'file',
help='The file with JSON results of pytest-benchmark')
parser.add_argument(
'--status-code', type=int, default=0,
help='The status code to exit with in case bad outliers are detected.')
return parser.parse_args()
def parse_file(file):
data = None
tests = []
with open(file) as f:
data = json.loads(f.read())
for test in data['benchmarks']:
name = test['name']
mean = test['stats']['mean']
extra = test['extra_info']
tests.append((name, mean, extra))
return tests
base_query = {
"query": {
"bool": {
"must": [
{"term": {"machine_info.host": "weasel"}},
{"term": {"commit_info.branch": "master"}},
{"term": {"commit_info.project": "soledad"}},
{"exists": {"field": "extra_info"}},
{"exists": {"field": "extra_info.cpu_percent"}}
],
"must_not": [
],
},
},
"aggs": {
"commit_id_time": {
"terms": {
"field": "commit_info.id",
"size": BLOCK_SIZE,
"order": {"commit_info_time": "desc"},
},
"aggs": {
"commit_info_time": {"max": {"field": "commit_info.time"}},
}
}
},
}
def get_time_cpu_stats(test):
query = copy.deepcopy(base_query)
query['query']['bool']['must'].append({
'term': {'name': test}})
query['query']['bool']['must_not'].append(
{'exists': {'field': "extra_info.memory_percent"}})
query['aggs']['commit_id_time']['aggs']['time'] = \
{"stats": {"field": "stats.mean"}}
query['aggs']['commit_id_time']['aggs']['cpu'] = \
{"stats": {"field": "extra_info.cpu_percent"}}
response = requests.get("%s?size=0" % URL, data=json.dumps(query))
data = response.json()
time = []
cpu = []
buckets = data['aggregations']['commit_id_time']['buckets']
for bucket in buckets:
time.append(bucket['time']['avg'])
cpu.append(bucket['cpu']['avg'])
return time, cpu
def get_mem_stats(test):
query = copy.deepcopy(base_query)
query['query']['bool']['must'].append({
'term': {'name': test}})
query['query']['bool']['must'].append(
{'exists': {'field': "extra_info.memory_percent"}})
query['aggs']['commit_id_time']['aggs']['mem'] = \
{"stats": {"field": "extra_info.memory_percent.stats.max"}}
response = requests.get("%s?size=0" % URL, data=json.dumps(query))
data = response.json()
mem = []
buckets = data['aggregations']['commit_id_time']['buckets']
for bucket in buckets:
mem.append(bucket['mem']['avg'])
return mem
def _mean(l):
return float(sum(l)) / len(l)
def _std(l):
if len(l) <= 1:
return 0
mean = _mean(l)
squares = [(x - mean) ** 2 for x in l]
return (sum(squares) / (len(l) - 1)) ** 0.5
def detect_bad_outlier(test, mean, extra):
bad = False
if 'memory_percent' in extra:
mem = get_mem_stats(test)
value = extra['memory_percent']['stats']['max']
bad |= _detect_outlier(test, 'mem', value, mem) > 0
else:
time, cpu = get_time_cpu_stats(test)
value = mean
bad |= _detect_outlier(test, 'time', value, time) > 0
value = extra['cpu_percent']
bad |= _detect_outlier(test, 'cpu', value, cpu) > 0
return bad
def _detect_outlier(test, name, value, list):
if not list:
return 0
mean = _mean(list)
std = _std(list)
result = 0
print "Checking %s (%s):" % (test, name)
print " value: %f" % (value,)
print " lower limit: %f" % (mean - (MULTIPLIER * std))
print " upper limit: %f" % (mean + (MULTIPLIER * std))
if value < mean - MULTIPLIER * std:
print " => good outlier detected!"
result = -1
elif value > mean + MULTIPLIER * std:
print " => bad outlier detected!"
result = 1
return result
if __name__ == '__main__':
args = parse_args()
tests = parse_file(args.file)
print "Checking %d test results for outliers..." % len(tests)
failed = False
for test, mean, extra in tests:
failed |= detect_bad_outlier(test, mean, extra)
if failed:
print "Tests have bad outliers! o_O"
sys.exit(args.status_code)
else:
print "All good, no outliers were detected. :-)"
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