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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-05-04 14:31:17 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-05-04 14:31:17 +0000 |
commit | 8020f71afd34d7696d7933659df2d763ab05542f (patch) | |
tree | 2fdf1b5447ffd8bdd61e702ca183e814afdcb4fc /collectors/python.d.plugin/changefinder/changefinder.chart.py | |
parent | Initial commit. (diff) | |
download | netdata-upstream.tar.xz netdata-upstream.zip |
Adding upstream version 1.37.1.upstream/1.37.1upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'collectors/python.d.plugin/changefinder/changefinder.chart.py')
-rw-r--r-- | collectors/python.d.plugin/changefinder/changefinder.chart.py | 185 |
1 files changed, 185 insertions, 0 deletions
diff --git a/collectors/python.d.plugin/changefinder/changefinder.chart.py b/collectors/python.d.plugin/changefinder/changefinder.chart.py new file mode 100644 index 0000000..c18e560 --- /dev/null +++ b/collectors/python.d.plugin/changefinder/changefinder.chart.py @@ -0,0 +1,185 @@ +# -*- coding: utf-8 -*- +# Description: changefinder netdata python.d module +# Author: andrewm4894 +# SPDX-License-Identifier: GPL-3.0-or-later + +from json import loads +import re + +from bases.FrameworkServices.UrlService import UrlService + +import numpy as np +import changefinder +from scipy.stats import percentileofscore + +update_every = 5 +disabled_by_default = True + +ORDER = [ + 'scores', + 'flags' +] + +CHARTS = { + 'scores': { + 'options': [None, 'ChangeFinder', 'score', 'Scores', 'scores', 'line'], + 'lines': [] + }, + 'flags': { + 'options': [None, 'ChangeFinder', 'flag', 'Flags', 'flags', 'stacked'], + 'lines': [] + } +} + +DEFAULT_PROTOCOL = 'http' +DEFAULT_HOST = '127.0.0.1:19999' +DEFAULT_CHARTS_REGEX = 'system.*' +DEFAULT_MODE = 'per_chart' +DEFAULT_CF_R = 0.5 +DEFAULT_CF_ORDER = 1 +DEFAULT_CF_SMOOTH = 15 +DEFAULT_CF_DIFF = False +DEFAULT_CF_THRESHOLD = 99 +DEFAULT_N_SCORE_SAMPLES = 14400 +DEFAULT_SHOW_SCORES = False + + +class Service(UrlService): + def __init__(self, configuration=None, name=None): + UrlService.__init__(self, configuration=configuration, name=name) + self.order = ORDER + self.definitions = CHARTS + self.protocol = self.configuration.get('protocol', DEFAULT_PROTOCOL) + self.host = self.configuration.get('host', DEFAULT_HOST) + self.url = '{}://{}/api/v1/allmetrics?format=json'.format(self.protocol, self.host) + self.charts_regex = re.compile(self.configuration.get('charts_regex', DEFAULT_CHARTS_REGEX)) + self.charts_to_exclude = self.configuration.get('charts_to_exclude', '').split(',') + self.mode = self.configuration.get('mode', DEFAULT_MODE) + self.n_score_samples = int(self.configuration.get('n_score_samples', DEFAULT_N_SCORE_SAMPLES)) + self.show_scores = int(self.configuration.get('show_scores', DEFAULT_SHOW_SCORES)) + self.cf_r = float(self.configuration.get('cf_r', DEFAULT_CF_R)) + self.cf_order = int(self.configuration.get('cf_order', DEFAULT_CF_ORDER)) + self.cf_smooth = int(self.configuration.get('cf_smooth', DEFAULT_CF_SMOOTH)) + self.cf_diff = bool(self.configuration.get('cf_diff', DEFAULT_CF_DIFF)) + self.cf_threshold = float(self.configuration.get('cf_threshold', DEFAULT_CF_THRESHOLD)) + self.collected_dims = {'scores': set(), 'flags': set()} + self.models = {} + self.x_latest = {} + self.scores_latest = {} + self.scores_samples = {} + + def get_score(self, x, model): + """Update the score for the model based on most recent data, flag if it's percentile passes self.cf_threshold. + """ + + # get score + if model not in self.models: + # initialise empty model if needed + self.models[model] = changefinder.ChangeFinder(r=self.cf_r, order=self.cf_order, smooth=self.cf_smooth) + # if the update for this step fails then just fallback to last known score + try: + score = self.models[model].update(x) + self.scores_latest[model] = score + except Exception as _: + score = self.scores_latest.get(model, 0) + score = 0 if np.isnan(score) else score + + # update sample scores used to calculate percentiles + if model in self.scores_samples: + self.scores_samples[model].append(score) + else: + self.scores_samples[model] = [score] + self.scores_samples[model] = self.scores_samples[model][-self.n_score_samples:] + + # convert score to percentile + score = percentileofscore(self.scores_samples[model], score) + + # flag based on score percentile + flag = 1 if score >= self.cf_threshold else 0 + + return score, flag + + def validate_charts(self, chart, data, algorithm='absolute', multiplier=1, divisor=1): + """If dimension not in chart then add it. + """ + if not self.charts: + return + + for dim in data: + if dim not in self.collected_dims[chart]: + self.collected_dims[chart].add(dim) + self.charts[chart].add_dimension([dim, dim, algorithm, multiplier, divisor]) + + for dim in list(self.collected_dims[chart]): + if dim not in data: + self.collected_dims[chart].remove(dim) + self.charts[chart].del_dimension(dim, hide=False) + + def diff(self, x, model): + """Take difference of data. + """ + x_diff = x - self.x_latest.get(model, 0) + self.x_latest[model] = x + x = x_diff + return x + + def _get_data(self): + + # pull data from self.url + raw_data = self._get_raw_data() + if raw_data is None: + return None + + raw_data = loads(raw_data) + + # filter to just the data for the charts specified + charts_in_scope = list(filter(self.charts_regex.match, raw_data.keys())) + charts_in_scope = [c for c in charts_in_scope if c not in self.charts_to_exclude] + + data_score = {} + data_flag = {} + + # process each chart + for chart in charts_in_scope: + + if self.mode == 'per_chart': + + # average dims on chart and run changefinder on that average + x = [raw_data[chart]['dimensions'][dim]['value'] for dim in raw_data[chart]['dimensions']] + x = [x for x in x if x is not None] + + if len(x) > 0: + + x = sum(x) / len(x) + x = self.diff(x, chart) if self.cf_diff else x + + score, flag = self.get_score(x, chart) + if self.show_scores: + data_score['{}_score'.format(chart)] = score * 100 + data_flag[chart] = flag + + else: + + # run changefinder on each individual dim + for dim in raw_data[chart]['dimensions']: + + chart_dim = '{}|{}'.format(chart, dim) + + x = raw_data[chart]['dimensions'][dim]['value'] + x = x if x else 0 + x = self.diff(x, chart_dim) if self.cf_diff else x + + score, flag = self.get_score(x, chart_dim) + if self.show_scores: + data_score['{}_score'.format(chart_dim)] = score * 100 + data_flag[chart_dim] = flag + + self.validate_charts('flags', data_flag) + + if self.show_scores & len(data_score) > 0: + data_score['average_score'] = sum(data_score.values()) / len(data_score) + self.validate_charts('scores', data_score, divisor=100) + + data = {**data_score, **data_flag} + + return data |