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# Copyright 2022-2023 ETSI TeraFlowSDN - TFS OSG (https://tfs.etsi.org/)
#
# 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.
from typing import Dict, List, Optional, Tuple
from .tools.FileSystem import create_folders
from .tools.HistogramData import HistogramData
from .tools.Plotter import plot_histogram
from .tools.Prometheus import get_prometheus_range, get_prometheus_series_names
from .tools.Histogram import results_to_histograms, save_histograms, unaccumulate_histograms
##### EXPERIMENT SETTINGS ##############################################################################################
from .experiments.scenario_1.Emu_Onboard import EXPERIMENT_NAME, EXPERIMENT_ID, TIME_START, TIME_END
#from .experiments.scenario_1.L2NM_EMU_Service import EXPERIMENT_NAME, EXPERIMENT_ID, TIME_START, TIME_END
#from .experiments.scenario_1.L3NM_EMU_Service import EXPERIMENT_NAME, EXPERIMENT_ID, TIME_START, TIME_END
TIME_STEP = '1m'
LABEL_FILTERS = {}
##### ENVIRONMENT SETTINGS #############################################################################################
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PROM_PORT = 9090
OUT_FOLDER = 'data/perf/'
##### PLOT-SPECIFIC CUSTOMIZATIONS #####################################################################################
EXPERIMENT_ID += '/component-rpcs'
SERIES_MATCH = 'tfs_.+_rpc_.+_histogram_duration_bucket'
RE_SERIES_NAME = re.compile(r'^tfs_(.+)_rpc_(.+)_histogram_duration_bucket$')
SERIES_LABELS = []
SUBSYSTEMS_MAPPING = {
'context': {
'context' : 'context',
'topolog' : 'topology',
'device' : 'device',
'endpoint' : 'device',
'link' : 'link',
'service' : 'service',
'slice' : 'slice',
'policyrule': 'policyrule',
'connection': 'connection',
}
}
def get_subsystem(component : str, rpc_method : str) -> Optional[str]:
return next(iter([
subsystem
for pattern,subsystem in SUBSYSTEMS_MAPPING.get(component, {}).items()
if pattern in rpc_method
]), None)
def update_keys(component : str, rpc_method : str) -> Tuple[Tuple, Tuple]:
subsystem = get_subsystem(component, rpc_method)
collection_keys = (component, subsystem)
histogram_keys = (rpc_method,)
return collection_keys, histogram_keys
def get_plot_specs(folders : Dict[str, str], component : str, subsystem : Optional[str]) -> Tuple[str, str]:
if subsystem is None:
title = '{:s} - RPC Methods [{:s}]'.format(component.title(), EXPERIMENT_NAME)
filepath = '{:s}/{:s}.png'.format(folders['png'], component)
else:
title = '{:s} - RPC Methods - {:s} [{:s}]'.format(component.title(), subsystem.title(), EXPERIMENT_NAME)
filepath = '{:s}/{:s}-{:s}.png'.format(folders['png'], component, subsystem)
return title, filepath
##### AUTOMATED CODE ###################################################################################################
def get_series_names(folders : Dict[str, str]) -> List[str]:
series_names = get_prometheus_series_names(
PROM_ADDRESS, PROM_PORT, SERIES_MATCH, TIME_START, TIME_END,
raw_json_filepath='{:s}/_series.json'.format(folders['json'])
)
return series_names
def get_histogram_data(series_name : str, folders : Dict[str, str]) -> Dict[Tuple, HistogramData]:
m = RE_SERIES_NAME.match(series_name)
if m is None:
# pylint: disable=broad-exception-raised
raise Exception('Unparsable series name: {:s}'.format(str(series_name)))
extra_labels = m.groups()
results = get_prometheus_range(
PROM_ADDRESS, PROM_PORT, series_name, LABEL_FILTERS, TIME_START, TIME_END, TIME_STEP,
raw_json_filepath='{:s}/_raw_{:s}.json'.format(folders['json'], series_name)
)
histograms = results_to_histograms(results, SERIES_LABELS, extra_labels=extra_labels)
unaccumulate_histograms(histograms, process_bins=True, process_timestamps=False)
save_histograms(histograms, folders['csv'])
return histograms
def main() -> None:
histograms_collection : Dict[Tuple, Dict[Tuple, HistogramData]] = dict()
folders = create_folders(OUT_FOLDER, EXPERIMENT_ID)
series_names = get_series_names(folders)
for series_name in series_names:
histograms = get_histogram_data(series_name, folders)
for histogram_keys, histogram_data in histograms.items():
collection_keys,histogram_keys = update_keys(*histogram_keys)
histograms = histograms_collection.setdefault(collection_keys, dict())
histograms[histogram_keys] = histogram_data
for histogram_keys,histograms in histograms_collection.items():
title, filepath = get_plot_specs(folders, *histogram_keys)
plot_histogram(histograms, filepath, title=title)
if __name__ == '__main__':
main()