diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..a81c8ee121952cf06bfaf9ff9988edd8cded763c --- /dev/null +++ b/.gitignore @@ -0,0 +1,138 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ diff --git a/.idea/time-series-data.iml b/.idea/time-series-data.iml new file mode 100644 index 0000000000000000000000000000000000000000..8a05c6ed5f0c89c2998d9aee8978f53136f7649a --- /dev/null +++ b/.idea/time-series-data.iml @@ -0,0 +1,12 @@ + + + + + + + + + + \ No newline at end of file diff --git a/time-series-data/7bulls_predictions.md b/time-series-data/7bulls_predictions.md new file mode 100644 index 0000000000000000000000000000000000000000..83e463b95f37ce00993ac9b5fc56342a97042524 --- /dev/null +++ b/time-series-data/7bulls_predictions.md @@ -0,0 +1,123 @@ +# Time series prediction - results + +1. FCR - average response time + * fcr_2020-10-29 to 2020-10-30 + * time series + ![Alt text](images/fcr_2020-10-29 to 2020-10-30_ts.png?raw=true "Title") + Average spike length: 151 seconds + Median spike length: 120.0 seconds (2 points) + * prediction (tft) + ![Alt text](images/fcr_2020-10-29 to 2020-10-30_1_preds.png?raw=true "Title") + * prediction with fake added points (2s)(tft) + ![Alt text](images/fcr_fake_points.png?raw=true "Title") + + * fcr_2020-11-27 to 2020-11-27 + * time series + ![Alt text](images/fcr_2020-11-27 to 2020-11-27_1.png?raw=true "Title") + Average spike length: 377 seconds + Median spike length: 180.0 seconds + * prediction (tft) + ![Alt text](images/fcr_2020-11-27 to 2020-11-27_1_preds_res.png?raw=true "Title") + + * fcr_2020-12-09 to 2020-12-09 + * time series + ![Alt text](images/fcr_2020-12-09 to 2020-12-09_1.png?raw=true "Title") + Average peak length is 10.57 seconds + Median peak length is 10 seconds (2 points) + * prediction + ![Alt text](images/fcr_2020-12-09 to 2020-12-09_1_preds.png?raw=true "Title") + * fcr_2020-12-15 to 2020-12-15 + * time series + ![Alt text](images/fcr_2020-12-15 to 2020-12-15_1.png?raw=true "Title") + Average peak length is 10.67 seconds + Median peak length is 10 seconds (2 points) + + ![Alt text](images/fcr_2020-12-15 to 2020-12-15_1_preds.png?raw=true "Title") + + + * fcr_2021-01-18 to 2021-01-19 + * TODO + * comments + * predictions are saved with format: predictions_{METHOD_NAME}.csv + * fcr average repsonse time - forecast with 1 min horizon + * fcr average response time series is aggregated over 60 seconds + * TODO + + +2. FCR - requests + * fcr_2020-10-29 to 2020-10-30 + * prediction (tft) + * 1 minute + ![Alt text](images/fcr_2020-10-29 to 2020-10-30_1_preds_0.png?raw=true "Title") + * 2 minutes + ![Alt text](images/fcr_2020-10-29 to 2020-10-30_1_preds_res.png?raw=true "Title") + * 3 minutes + ![Alt text](images/fcr_2020-10-29 to 2020-10-30_1_preds_2.png?raw=true "Title") + * prediction (n-beats) + * 1 minute + ![Alt text](images/nbeats_pred_0.png?raw=true "Title") + * 2 minutes + ![Alt text](images/nbeats_pred_1.png?raw=true "Title") + * 3 minutes + ![Alt text](images/nbeats_pred_2.png?raw=true "Title") + + * experiments with ensembles + 25 models (n-betas, tft) with different: predictions length, context length, + loss functions (rmse, mae, dilate, quantileloss), model architecture + * simple lasso regression (averaged 5 minutes prediction) + ![Alt text](images/preds_ens_lasso.png?raw=true "Title") + * lgbm (overfitting) (averaged 5 minutes prediction) + ![Alt text](images/preds_ens_lgbm.png?raw=true "Title") + + * prediction (es-rnn) + TODO + * comments + * predictions for longer horizonts (egz. 10 minutes are also avaliable) + * Requests were aggregated over 60 seconds + * predictions are saved with format: predictions_{METHOD_NAME}{STEP}.csv + * TODO + +3. Genome + * 2020-12-02 to 2020-12-02 + * MinimumCoresContext prediction (tft) + * 1 minute + ![Alt text](images/genome_preds_0.png?raw=true "Title") + * 2 minutes + ![Alt text](images/genome_preds_1.png?raw=true "Title") + * 3 minutes + ![Alt text](images/genome_preds_2.png?raw=true "Title") + * 4 minutes + ![Alt text](images/genome_preds_3.png?raw=true "Title") + * 5 minutes + ![Alt text](images/genome_preds_4.png?raw=true "Title") + + * MinimumCoresContext prediction (n-beats) + * TODO + * MinimumCoresContext prediction (es-rnn) + * TODO + + * feature importance + * ETPercentile + + ![Alt text](images/etpercentile_features.png?raw=true "Title") + * MinimumCoresContext + ![Alt text](images/minimumcorescontext_features.png?raw=true "Title") + * Experiments with ensembles + 15 models with different: predictions length (5-20 min), context length, + loss functions (rmse, mae, dilate, quantileloss), model architecture and metrics, + scores for single models are avaliable on neptune + * ETPercentile (averaged 5 minutes prediction) + * simple lasso regression + ![Alt text](images/ETPercentile_preds_ens_lasso.png?raw=true "Title") + * lgbm (overfitting) + ![Alt text](images/ETPercentile_preds_ens_lgbm.png?raw=true "Title") + * MinimumCoresContext (averaged 5 minutes prediction) + * simple lasso regression + ![Alt text](images/preds_ens_lasso_mini.png?raw=true "Title") + + + + * comments + * predictions are saved with format: {METRIC_NAME}_{METHOD_NAME}_preds{STEP}.csv + * TODO + diff --git a/time-series-data/benchmark_datasets/README.md b/time-series-data/benchmark_datasets/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8bfd0d074f47aecda6f7dbf1889f9eca8c83f56e --- /dev/null +++ b/time-series-data/benchmark_datasets/README.md @@ -0,0 +1,66 @@ +# Time series prediction - benchmark datasets and results comparision + +## Benchmark datasets + +1. FCR (secure-document) +- benchmark_datasets/secure-document/deployment-reconfiguration-range-1-to-1/ (without reconfiguration) +- benchmark_datasets/secure-document/deployment-reconfiguration-range-1-to-20/ (with reconfiguration) + +Metrics to predict: AvgResponseTimeTable (AvgResponseTimeTable.csv, value column), Requests (jmeterResults.csv, timeStamp column) + +2. Genome +- benchmark_datasets/deployment-reconfiguration-range-1-to-1 (without reconfiguration) +- benchmark_datasets/deployment-reconfiguration-range-1-to-10 (with reconfiguration) + +metrics to predict: metrics from data.csv (already preprocessed with dataset_maker.py) + + +Each dataset is divided into train and test (ratio 9:1). Information about the split can be found in 'split' column. + + +## Experiments +Experiments for methods comparision should be saved in Neptune with following tags: + +- method name +- dataset path (relative path from time-series-data ) +- predicted metric + +(e.g tft, secure-documnet/deployment-reconfiguration-range-1-to-1/2021-02-04 to 2021-02-04, Requests). + +Prediction horizon should cover 20 minutes, data granularity should be the same as in original data (except requests - no frequency, requests data should be then aggreagted with the same frequency as AvgReponseTimeTable data). + +TODO + +Discuss what exactly should be looged into neptune (e.g preprocessed data, model, predictions, metrics) + +## Predictions + +Predictions for results comparision should be saved with following format: +{DATASET_PATH}/{METRIC}/{METOD_NAME}_{NEPTUNE_EXPERIMENT_NAME}.csv + +(e.g secure-document/deployment-reconfiguration-range-1-to-1/2021-02-04 to 2021-02-04/v1.0 raw data/tft_FORESHYBRD-404.csv) + +csv prediction filw should contain: + + - prediction (predicted metrics value) + - time (timestamp for which prediction is created) + - step (integer, prediction step) + + fields. + +TODO +Maybe prediction csv file should have similar structure to Forecasting Methods/Prediction Orchestrator Events Format (https://confluence.7bulls.eu/display/MOR/Forecasting+Mechanism+Sub-components+Communication) + +## Evaluation + +One script will be used to evaluate all predictions ensuring that all metrics parameters (e.g epsilons preventing division by 0) are exactly the same. + + + + + + + + + + diff --git a/time-series-data/benchmark_datasets/genome/deployment-reconfiguration-range-1-to-1/2021-02-12 to 2021-02-13/v1.0 - raw data/ETPercentile.csv b/time-series-data/benchmark_datasets/genome/deployment-reconfiguration-range-1-to-1/2021-02-12 to 2021-02-13/v1.0 - raw data/ETPercentile.csv new file mode 100644 index 0000000000000000000000000000000000000000..9af6e43cadbb3b07ec906bf27a54331769f461b4 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a/time-series-data/benchmark_datasets/genome/deployment-reconfiguration-range-1-to-1/2021-02-12 to 2021-02-13/v1.0 - raw data/MinimumCoresContext.csv b/time-series-data/benchmark_datasets/genome/deployment-reconfiguration-range-1-to-1/2021-02-12 to 2021-02-13/v1.0 - raw data/MinimumCoresContext.csv new file mode 100644 index 0000000000000000000000000000000000000000..9afd70884604be6acbac80daf44c12f576a3ef6e --- /dev/null +++ b/time-series-data/benchmark_datasets/genome/deployment-reconfiguration-range-1-to-1/2021-02-12 to 2021-02-13/v1.0 - raw data/MinimumCoresContext.csv @@ -0,0 +1,2178 @@ +name,time,countryCode,ipAddress,level,producer,value +MinimumCoresContext,2021-02-12T12:03:57.99Z,IN,52.66.218.93,3,52.66.218.93,10 +MinimumCoresContext,2021-02-12T12:04:27.99Z,IN,52.66.218.93,3,52.66.218.93,10 +MinimumCoresContext,2021-02-12T12:04:57.99Z,IN,52.66.218.93,3,52.66.218.93,10 +MinimumCoresContext,2021-02-12T12:05:27.99Z,IN,52.66.218.93,3,52.66.218.93,10 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