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Diffstat (limited to 'scripts/lib/build_perf/report.py')
| -rw-r--r-- | scripts/lib/build_perf/report.py | 339 |
1 files changed, 339 insertions, 0 deletions
diff --git a/scripts/lib/build_perf/report.py b/scripts/lib/build_perf/report.py new file mode 100644 index 0000000000..ab77424cc7 --- /dev/null +++ b/scripts/lib/build_perf/report.py @@ -0,0 +1,339 @@ +# +# Copyright (c) 2017, Intel Corporation. +# +# SPDX-License-Identifier: GPL-2.0-only +# +"""Handling of build perf test reports""" +from collections import OrderedDict, namedtuple +from collections.abc import Mapping +from datetime import datetime, timezone +from numbers import Number +from statistics import mean, stdev, variance + + +AggregateTestData = namedtuple('AggregateTestData', ['metadata', 'results']) + + +def isofmt_to_timestamp(string): + """Convert timestamp string in ISO 8601 format into unix timestamp""" + if '.' in string: + dt = datetime.strptime(string, '%Y-%m-%dT%H:%M:%S.%f') + else: + dt = datetime.strptime(string, '%Y-%m-%dT%H:%M:%S') + return dt.replace(tzinfo=timezone.utc).timestamp() + + +def metadata_xml_to_json(elem): + """Convert metadata xml into JSON format""" + assert elem.tag == 'metadata', "Invalid metadata file format" + + def _xml_to_json(elem): + """Convert xml element to JSON object""" + out = OrderedDict() + for child in elem.getchildren(): + key = child.attrib.get('name', child.tag) + if len(child): + out[key] = _xml_to_json(child) + else: + out[key] = child.text + return out + return _xml_to_json(elem) + + +def results_xml_to_json(elem): + """Convert results xml into JSON format""" + rusage_fields = ('ru_utime', 'ru_stime', 'ru_maxrss', 'ru_minflt', + 'ru_majflt', 'ru_inblock', 'ru_oublock', 'ru_nvcsw', + 'ru_nivcsw') + iostat_fields = ('rchar', 'wchar', 'syscr', 'syscw', 'read_bytes', + 'write_bytes', 'cancelled_write_bytes') + + def _read_measurement(elem): + """Convert measurement to JSON""" + data = OrderedDict() + data['type'] = elem.tag + data['name'] = elem.attrib['name'] + data['legend'] = elem.attrib['legend'] + values = OrderedDict() + + # SYSRES measurement + if elem.tag == 'sysres': + for subel in elem: + if subel.tag == 'time': + values['start_time'] = isofmt_to_timestamp(subel.attrib['timestamp']) + values['elapsed_time'] = float(subel.text) + elif subel.tag == 'rusage': + rusage = OrderedDict() + for field in rusage_fields: + if 'time' in field: + rusage[field] = float(subel.attrib[field]) + else: + rusage[field] = int(subel.attrib[field]) + values['rusage'] = rusage + elif subel.tag == 'iostat': + values['iostat'] = OrderedDict([(f, int(subel.attrib[f])) + for f in iostat_fields]) + elif subel.tag == 'buildstats_file': + values['buildstats_file'] = subel.text + else: + raise TypeError("Unknown sysres value element '{}'".format(subel.tag)) + # DISKUSAGE measurement + elif elem.tag == 'diskusage': + values['size'] = int(elem.find('size').text) + else: + raise Exception("Unknown measurement tag '{}'".format(elem.tag)) + data['values'] = values + return data + + def _read_testcase(elem): + """Convert testcase into JSON""" + assert elem.tag == 'testcase', "Expecting 'testcase' element instead of {}".format(elem.tag) + + data = OrderedDict() + data['name'] = elem.attrib['name'] + data['description'] = elem.attrib['description'] + data['status'] = 'SUCCESS' + data['start_time'] = isofmt_to_timestamp(elem.attrib['timestamp']) + data['elapsed_time'] = float(elem.attrib['time']) + measurements = OrderedDict() + + for subel in elem.getchildren(): + if subel.tag == 'error' or subel.tag == 'failure': + data['status'] = subel.tag.upper() + data['message'] = subel.attrib['message'] + data['err_type'] = subel.attrib['type'] + data['err_output'] = subel.text + elif subel.tag == 'skipped': + data['status'] = 'SKIPPED' + data['message'] = subel.text + else: + measurements[subel.attrib['name']] = _read_measurement(subel) + data['measurements'] = measurements + return data + + def _read_testsuite(elem): + """Convert suite to JSON""" + assert elem.tag == 'testsuite', \ + "Expecting 'testsuite' element instead of {}".format(elem.tag) + + data = OrderedDict() + if 'hostname' in elem.attrib: + data['tester_host'] = elem.attrib['hostname'] + data['start_time'] = isofmt_to_timestamp(elem.attrib['timestamp']) + data['elapsed_time'] = float(elem.attrib['time']) + tests = OrderedDict() + + for case in elem.getchildren(): + tests[case.attrib['name']] = _read_testcase(case) + data['tests'] = tests + return data + + # Main function + assert elem.tag == 'testsuites', "Invalid test report format" + assert len(elem) == 1, "Too many testsuites" + + return _read_testsuite(elem.getchildren()[0]) + + +def aggregate_metadata(metadata): + """Aggregate metadata into one, basically a sanity check""" + mutable_keys = ('pretty_name', 'version_id') + + def aggregate_obj(aggregate, obj, assert_str=True): + """Aggregate objects together""" + assert type(aggregate) is type(obj), \ + "Type mismatch: {} != {}".format(type(aggregate), type(obj)) + if isinstance(obj, Mapping): + assert set(aggregate.keys()) == set(obj.keys()) + for key, val in obj.items(): + aggregate_obj(aggregate[key], val, key not in mutable_keys) + elif isinstance(obj, list): + assert len(aggregate) == len(obj) + for i, val in enumerate(obj): + aggregate_obj(aggregate[i], val) + elif not isinstance(obj, str) or (isinstance(obj, str) and assert_str): + assert aggregate == obj, "Data mismatch {} != {}".format(aggregate, obj) + + if not metadata: + return {} + + # Do the aggregation + aggregate = metadata[0].copy() + for testrun in metadata[1:]: + aggregate_obj(aggregate, testrun) + aggregate['testrun_count'] = len(metadata) + return aggregate + + +def aggregate_data(data): + """Aggregate multiple test results JSON structures into one""" + + mutable_keys = ('status', 'message', 'err_type', 'err_output') + + class SampleList(list): + """Container for numerical samples""" + pass + + def new_aggregate_obj(obj): + """Create new object for aggregate""" + if isinstance(obj, Number): + new_obj = SampleList() + new_obj.append(obj) + elif isinstance(obj, str): + new_obj = obj + else: + # Lists and and dicts are kept as is + new_obj = obj.__class__() + aggregate_obj(new_obj, obj) + return new_obj + + def aggregate_obj(aggregate, obj, assert_str=True): + """Recursive "aggregation" of JSON objects""" + if isinstance(obj, Number): + assert isinstance(aggregate, SampleList) + aggregate.append(obj) + return + + assert type(aggregate) == type(obj), \ + "Type mismatch: {} != {}".format(type(aggregate), type(obj)) + if isinstance(obj, Mapping): + for key, val in obj.items(): + if not key in aggregate: + aggregate[key] = new_aggregate_obj(val) + else: + aggregate_obj(aggregate[key], val, key not in mutable_keys) + elif isinstance(obj, list): + for i, val in enumerate(obj): + if i >= len(aggregate): + aggregate[key] = new_aggregate_obj(val) + else: + aggregate_obj(aggregate[i], val) + elif isinstance(obj, str): + # Sanity check for data + if assert_str: + assert aggregate == obj, "Data mismatch {} != {}".format(aggregate, obj) + else: + raise Exception("BUG: unable to aggregate '{}' ({})".format(type(obj), str(obj))) + + if not data: + return {} + + # Do the aggregation + aggregate = data[0].__class__() + for testrun in data: + aggregate_obj(aggregate, testrun) + return aggregate + + +class MeasurementVal(float): + """Base class representing measurement values""" + gv_data_type = 'number' + + def gv_value(self): + """Value formatting for visualization""" + if self != self: + return "null" + else: + return self + + +class TimeVal(MeasurementVal): + """Class representing time values""" + quantity = 'time' + gv_title = 'elapsed time' + gv_data_type = 'timeofday' + + def hms(self): + """Split time into hours, minutes and seconeds""" + hhh = int(abs(self) / 3600) + mmm = int((abs(self) % 3600) / 60) + sss = abs(self) % 60 + return hhh, mmm, sss + + def __str__(self): + if self != self: + return "nan" + hh, mm, ss = self.hms() + sign = '-' if self < 0 else '' + if hh > 0: + return '{}{:d}:{:02d}:{:02.0f}'.format(sign, hh, mm, ss) + elif mm > 0: + return '{}{:d}:{:04.1f}'.format(sign, mm, ss) + elif ss > 1: + return '{}{:.1f} s'.format(sign, ss) + else: + return '{}{:.2f} s'.format(sign, ss) + + def gv_value(self): + """Value formatting for visualization""" + if self != self: + return "null" + hh, mm, ss = self.hms() + return [hh, mm, int(ss), int(ss*1000) % 1000] + + +class SizeVal(MeasurementVal): + """Class representing time values""" + quantity = 'size' + gv_title = 'size in MiB' + gv_data_type = 'number' + + def __str__(self): + if self != self: + return "nan" + if abs(self) < 1024: + return '{:.1f} kiB'.format(self) + elif abs(self) < 1048576: + return '{:.2f} MiB'.format(self / 1024) + else: + return '{:.2f} GiB'.format(self / 1048576) + + def gv_value(self): + """Value formatting for visualization""" + if self != self: + return "null" + return self / 1024 + +def measurement_stats(meas, prefix=''): + """Get statistics of a measurement""" + if not meas: + return {prefix + 'sample_cnt': 0, + prefix + 'mean': MeasurementVal('nan'), + prefix + 'stdev': MeasurementVal('nan'), + prefix + 'variance': MeasurementVal('nan'), + prefix + 'min': MeasurementVal('nan'), + prefix + 'max': MeasurementVal('nan'), + prefix + 'minus': MeasurementVal('nan'), + prefix + 'plus': MeasurementVal('nan')} + + stats = {'name': meas['name']} + if meas['type'] == 'sysres': + val_cls = TimeVal + values = meas['values']['elapsed_time'] + elif meas['type'] == 'diskusage': + val_cls = SizeVal + values = meas['values']['size'] + else: + raise Exception("Unknown measurement type '{}'".format(meas['type'])) + stats['val_cls'] = val_cls + stats['quantity'] = val_cls.quantity + stats[prefix + 'sample_cnt'] = len(values) + + mean_val = val_cls(mean(values)) + min_val = val_cls(min(values)) + max_val = val_cls(max(values)) + + stats[prefix + 'mean'] = mean_val + if len(values) > 1: + stats[prefix + 'stdev'] = val_cls(stdev(values)) + stats[prefix + 'variance'] = val_cls(variance(values)) + else: + stats[prefix + 'stdev'] = float('nan') + stats[prefix + 'variance'] = float('nan') + stats[prefix + 'min'] = min_val + stats[prefix + 'max'] = max_val + stats[prefix + 'minus'] = val_cls(mean_val - min_val) + stats[prefix + 'plus'] = val_cls(max_val - mean_val) + + return stats + |