diff --git a/.idea/.name b/.idea/.name new file mode 100644 index 0000000000000000000000000000000000000000..e347a86c433b2ae0cc8e620d280a897a7d5ff770 --- /dev/null +++ b/.idea/.name @@ -0,0 +1 @@ +characterizationUseCase.py \ No newline at end of file diff --git a/README.md b/README.md index d65e2a09e9638c8addbcf1ae415a81f76626d37a..976b93e20a48a994f274efb63327c70ff7c2e7bd 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ #### **Seasonal study of user demand and IT system usage in datacenters artifact** + + **Brief presentation:** This directory contains the data and python files used to obtain the results of the study on the characterization of the seasonality of different time series from 6 HPC workloads and from the Wikipedia workload. The directory consists of the following elements: @@ -10,6 +12,8 @@ This directory contains the data and python files used to obtain the results of - The "characterizationUseCase.py" file allows you to run and obtain the results of the characterization use case example. +Python files were run using python 3. + **Packages needed:** @@ -23,7 +27,7 @@ This directory contains the data and python files used to obtain the results of - sktime (to use the TBATS forecasting method) - scipy (to use the periodogram, the Kruskal-Wallis test and the gaussian_kde method) - scikit_posthocs (to use the Conover-Iman test) -- statsmodels (to use the ADF test, the KPSS test and the lowess, MSTL and STL methods) +- statsmodels (to use the ADF test, the KPSS test and the LOWESS, MSTL and STL methods) diff --git a/characterizationUseCase.py b/characterizationUseCase.py index cb4b7fb0af976e5273db5fe21dd14ff0b6fc0b89..c528805281eb68703d44d2eed8662e17f5d6569b 100644 --- a/characterizationUseCase.py +++ b/characterizationUseCase.py @@ -60,9 +60,6 @@ m = Prophet(seasonality_mode = 'additive', daily_seasonality=True, weekly_seasonality=True, yearly_seasonality=False) - -# m.add_country_holidays(country_name = 'US') # Vacances du pays dans lequel a tourné le workload -# m.add_seasonality(name = 'monthly', period = 84, fourier_order = results[0][1]) # Autre saisonnalité m.fit(df[:-steps]) future = m.make_future_dataframe(periods = steps, freq = 'H') future['floor'] = 0 diff --git a/hpc_case/__pycache__/openTimeSeriesJson.cpython-310.pyc b/hpc_case/__pycache__/openTimeSeriesJson.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f2e34487c6c464ed94a0bac13afbdedb7eed42a1 Binary files /dev/null and b/hpc_case/__pycache__/openTimeSeriesJson.cpython-310.pyc differ diff --git a/hpc_case/openTimeSeriesJson.py b/hpc_case/openTimeSeriesJson.py index fb6e3ee25d84f4f61993b1f8a6fa3446192b1a62..d8798f0ba4bd4b64ceeb22b5cd371e1dbd0b112a 100644 --- a/hpc_case/openTimeSeriesJson.py +++ b/hpc_case/openTimeSeriesJson.py @@ -2,120 +2,120 @@ import json ### Maximum number of allocated cores by the system -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemAnlIntrepid.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemAnlIntrepid.json" with open(filename, 'r') as file: AllocatedCoresSystemAnlIntrepid = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemCiematEuler.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemCiematEuler.json" with open(filename, 'r') as file: AllocatedCoresSystemCiematEuler = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemMetacentrum.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemMetacentrum.json" with open(filename, 'r') as file: AllocatedCoresSystemMetacentrum = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemMetacentrumFiltered.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemMetacentrumFiltered.json" with open(filename, 'r') as file: AllocatedCoresSystemMetacentrumFiltered = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemPIKIPLEX.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemPIKIPLEX.json" with open(filename, 'r') as file: AllocatedCoresSystemPIKIPLEX = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemRICC.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemRICC.json" with open(filename, 'r') as file: AllocatedCoresSystemRICC = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresSystemUniLuGaia.json" +filename = "time_series_json_hpc_data/AllocatedCoresSystemUniLuGaia.json" with open(filename, 'r') as file: AllocatedCoresSystemUniLuGaia = json.load(file) ### Maximum number of requested cores by the users -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresAnlIntrepid.json" +filename = "time_series_json_hpc_data/AllocatedCoresAnlIntrepid.json" with open(filename, 'r') as file: AllocatedCoresAnlIntrepid = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresCiematEuler.json" +filename = "time_series_json_hpc_data/AllocatedCoresCiematEuler.json" with open(filename, 'r') as file: AllocatedCoresCiematEuler = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresMetacentrum.json" +filename = "time_series_json_hpc_data/AllocatedCoresMetacentrum.json" with open(filename, 'r') as file: AllocatedCoresMetacentrum = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresMetacentrumFiltered.json" +filename = "time_series_json_hpc_data/AllocatedCoresMetacentrumFiltered.json" with open(filename, 'r') as file: AllocatedCoresMetacentrumFiltered = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresPIKIPLEX.json" +filename = "time_series_json_hpc_data/AllocatedCoresPIKIPLEX.json" with open(filename, 'r') as file: AllocatedCoresPIKIPLEX = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresRICC.json" +filename = "time_series_json_hpc_data/AllocatedCoresRICC.json" with open(filename, 'r') as file: AllocatedCoresRICC = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/AllocatedCoresUniLuGaia.json" +filename = "time_series_json_hpc_data/AllocatedCoresUniLuGaia.json" with open(filename, 'r') as file: AllocatedCoresUniLuGaia = json.load(file) ### Workload mass -filename = "hpc_case/time_series_json_hpc_data/MassJobsAnlIntrepid.json" +filename = "time_series_json_hpc_data/MassJobsAnlIntrepid.json" with open(filename, 'r') as file: MassJobsAnlIntrepid = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/MassJobsCiematEuler.json" +filename = "time_series_json_hpc_data/MassJobsCiematEuler.json" with open(filename, 'r') as file: MassJobsCiematEuler = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/MassJobsMetacentrum.json" +filename = "time_series_json_hpc_data/MassJobsMetacentrum.json" with open(filename, 'r') as file: MassJobsMetacentrum = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/MassJobsMetacentrumFiltered.json" +filename = "time_series_json_hpc_data/MassJobsMetacentrumFiltered.json" with open(filename, 'r') as file: MassJobsMetacentrumFiltered = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/MassJobsPIKIPLEX.json" +filename = "time_series_json_hpc_data/MassJobsPIKIPLEX.json" with open(filename, 'r') as file: MassJobsPIKIPLEX = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/MassJobsRICC.json" +filename = "time_series_json_hpc_data/MassJobsRICC.json" with open(filename, 'r') as file: MassJobsRICC = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/MassJobsUniLuGaia.json" +filename = "time_series_json_hpc_data/MassJobsUniLuGaia.json" with open(filename, 'r') as file: MassJobsUniLuGaia = json.load(file) ### Number of jobs -filename = "hpc_case/time_series_json_hpc_data/NumberJobsAnlIntrepid.json" +filename = "time_series_json_hpc_data/NumberJobsAnlIntrepid.json" with open(filename, 'r') as file: NumberJobsAnlIntrepid = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/NumberJobsCiematEuler.json" +filename = "time_series_json_hpc_data/NumberJobsCiematEuler.json" with open(filename, 'r') as file: NumberJobsCiematEuler = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/NumberJobsMetacentrum.json" +filename = "time_series_json_hpc_data/NumberJobsMetacentrum.json" with open(filename, 'r') as file: NumberJobsMetacentrum = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/NumberJobsMetacentrumFiltered.json" +filename = "time_series_json_hpc_data/NumberJobsMetacentrumFiltered.json" with open(filename, 'r') as file: NumberJobsMetacentrumFiltered = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/NumberJobsPIKIPLEX.json" +filename = "time_series_json_hpc_data/NumberJobsPIKIPLEX.json" with open(filename, 'r') as file: NumberJobsPIKIPLEX = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/NumberJobsRICC.json" +filename = "time_series_json_hpc_data/NumberJobsRICC.json" with open(filename, 'r') as file: NumberJobsRICC = json.load(file) -filename = "hpc_case/time_series_json_hpc_data/NumberJobsUniLuGaia.json" +filename = "time_series_json_hpc_data/NumberJobsUniLuGaia.json" with open(filename, 'r') as file: NumberJobsUniLuGaia = json.load(file) \ No newline at end of file