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Commit 6f6039fd authored by dlandre2's avatar dlandre2
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maj

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characterizationUseCase.py
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#### **Seasonal study of user demand and IT system usage in datacenters artifact** #### **Seasonal study of user demand and IT system usage in datacenters artifact**
**Brief presentation:** **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: 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 ...@@ -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. - 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:** **Packages needed:**
...@@ -23,7 +27,7 @@ This directory contains the data and python files used to obtain the results of ...@@ -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) - sktime (to use the TBATS forecasting method)
- scipy (to use the periodogram, the Kruskal-Wallis test and the gaussian_kde method) - scipy (to use the periodogram, the Kruskal-Wallis test and the gaussian_kde method)
- scikit_posthocs (to use the Conover-Iman test) - 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)
......
...@@ -60,9 +60,6 @@ m = Prophet(seasonality_mode = 'additive', ...@@ -60,9 +60,6 @@ m = Prophet(seasonality_mode = 'additive',
daily_seasonality=True, daily_seasonality=True,
weekly_seasonality=True, weekly_seasonality=True,
yearly_seasonality=False) 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]) m.fit(df[:-steps])
future = m.make_future_dataframe(periods = steps, freq = 'H') future = m.make_future_dataframe(periods = steps, freq = 'H')
future['floor'] = 0 future['floor'] = 0
......
File added
...@@ -2,120 +2,120 @@ import json ...@@ -2,120 +2,120 @@ import json
### Maximum number of allocated cores by the system ### 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: with open(filename, 'r') as file:
AllocatedCoresSystemAnlIntrepid = json.load(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: with open(filename, 'r') as file:
AllocatedCoresSystemCiematEuler = json.load(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: with open(filename, 'r') as file:
AllocatedCoresSystemMetacentrum = json.load(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: with open(filename, 'r') as file:
AllocatedCoresSystemMetacentrumFiltered = json.load(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: with open(filename, 'r') as file:
AllocatedCoresSystemPIKIPLEX = json.load(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: with open(filename, 'r') as file:
AllocatedCoresSystemRICC = json.load(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: with open(filename, 'r') as file:
AllocatedCoresSystemUniLuGaia = json.load(file) AllocatedCoresSystemUniLuGaia = json.load(file)
### Maximum number of requested cores by the users ### 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: with open(filename, 'r') as file:
AllocatedCoresAnlIntrepid = json.load(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: with open(filename, 'r') as file:
AllocatedCoresCiematEuler = json.load(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: with open(filename, 'r') as file:
AllocatedCoresMetacentrum = json.load(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: with open(filename, 'r') as file:
AllocatedCoresMetacentrumFiltered = json.load(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: with open(filename, 'r') as file:
AllocatedCoresPIKIPLEX = json.load(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: with open(filename, 'r') as file:
AllocatedCoresRICC = json.load(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: with open(filename, 'r') as file:
AllocatedCoresUniLuGaia = json.load(file) AllocatedCoresUniLuGaia = json.load(file)
### Workload mass ### 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: with open(filename, 'r') as file:
MassJobsAnlIntrepid = json.load(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: with open(filename, 'r') as file:
MassJobsCiematEuler = json.load(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: with open(filename, 'r') as file:
MassJobsMetacentrum = json.load(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: with open(filename, 'r') as file:
MassJobsMetacentrumFiltered = json.load(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: with open(filename, 'r') as file:
MassJobsPIKIPLEX = json.load(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: with open(filename, 'r') as file:
MassJobsRICC = json.load(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: with open(filename, 'r') as file:
MassJobsUniLuGaia = json.load(file) MassJobsUniLuGaia = json.load(file)
### Number of jobs ### 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: with open(filename, 'r') as file:
NumberJobsAnlIntrepid = json.load(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: with open(filename, 'r') as file:
NumberJobsCiematEuler = json.load(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: with open(filename, 'r') as file:
NumberJobsMetacentrum = json.load(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: with open(filename, 'r') as file:
NumberJobsMetacentrumFiltered = json.load(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: with open(filename, 'r') as file:
NumberJobsPIKIPLEX = json.load(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: with open(filename, 'r') as file:
NumberJobsRICC = json.load(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: with open(filename, 'r') as file:
NumberJobsUniLuGaia = json.load(file) NumberJobsUniLuGaia = json.load(file)
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