Commit b3f16d30 authored by Ryan Randles Jones's avatar Ryan Randles Jones
Browse files

changed user to jobs per user

parent 871025b9
%% Cell type:markdown id: tags:
# Notebook Setup
%% Cell type:code id: tags:
```
# must run
import sqlite3
import slurm2sql
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
import plotly.express as px
import matplotlib.ticker as ticker
```
%% Cell type:code id: tags:
```
from RC_styles import rc_styles as style
```
%% Cell type:code id: tags:
```
# must run
# creates database of info from March 2020 using sqlite 3
db = sqlite3.connect('/data/rc/rc-team/slurm-since-March.sqlite3')
```
%% Cell type:code id: tags:
```
# must run
# df is starting database
df = pd.read_sql('SELECT * FROM slurm', db)
```
%% Cell type:code id: tags:
```
# voluntary
# for displaying all available column options
pd.set_option('display.max_columns', None)
df.head(5)
```
%% Cell type:code id: tags:
```
# must run
# converts units in ReqMemCPU column from bytes to gigs
df['ReqMemCPU'] = df['ReqMemCPU'].div(1024**3)
```
%% Cell type:code id: tags:
```
# must run
# df_completed is dataframe of all completed jobs
df_completed = df[df.State.str.contains('COMPLETED')]
#df_completed.head(5)
```
%% Cell type:code id: tags:
```
# must run
# df_batch is df with only batch jobs
df_batch = df[df.JobName.str.contains('batch')]
#df_batch.head(5)
```
%% Cell type:markdown id: tags:
# Average RAM per CPU Requested by User
%% Cell type:code id: tags:
```
# must run
# df_2 is database of completed jobs with only User and ReqMemCpu
# it is used for the user dataframes
df_2 = df_completed.loc[:,['User','ReqMemCPU']]
#df_2.head(5)
```
%% Cell type:code id: tags:
```
# must run
# fills empty strings in User column with NaN and then filters them out to give a dataset of users with no empty strings
nan_value = float("NaN")
df_2.replace("", nan_value, inplace=True)
df_2.dropna(subset = ["User"], inplace=True)
#df_2.head(5)
```
%% Cell type:code id: tags:
```
# must run
# count = count of jobs per user
# mean,std,min,25%,50%,75%, and max refers to the gigs of memory per cpu requested by that user for all their jobs
df_user = df_2.groupby('User')['ReqMemCPU'].describe().reset_index()
#df_user.head(5)
```
%% Cell type:code id: tags:
```
# must run
# creates user number column of strings of numbers from 0 to the total number of users
# used in graphs in place of usernames
usernames = df_user['User']
user_numbers = [str(i) for i in range(len(usernames))]
df_user['User Number'] = user_numbers
df_user.head(5)
```
%% Cell type:code id: tags:
```
# voluntary
# description of number of jobs run per user - can be used to choose the Upper Limit Job Count
df_user['count'].describe()
```
%% Cell type:code id: tags:
```
# must run
# variable for to be used in names of plots to describe the max job count per user
# max = 367257
UpperlimitJobCount = 50
```
%% Cell type:code id: tags:
```
# must run
# creates database from df_user that returns all jobs per user up to the UpperlimitJobCount defined above
jobscount_cutoff = df_user[(df_user['count'] <= UpperlimitJobCount)]
jobscount_cutoff.head(5)
```
%% Cell type:code id: tags:
```
# must run
# df_user_graph is df_user sorted in ascending order by count for easy readibility of graph
df_user_graph = jobscount_cutoff.sort_values(by='count', ascending=True)
df_user_graph.head(5)
```
%% Cell type:code id: tags:
```
style.default_axes_and_ticks()
style.figsize()
user_graph1 = sns.scatterplot(x="count", y="mean",data=df_user_graph)
plt.title('Average Requested RAM per CPU by User for all Users Running %i Jobs or less'%UpperlimitJobCount)
plt.xlabel('Job Count Per User')
plt.ylabel('Average Requested RAM per CPU (Gigs)')
plt.show()
```
%% Cell type:code id: tags:
```
style.default_axes_and_ticks()
style.figsize()
user_graph = sns.barplot(x="count", y="mean", data= df_user_graph, color = 'blue')
#user_graph.set_xscale('log')
#user_graph.set_xscale('log')
user_graph.xaxis.set_major_locator(ticker.MultipleLocator(2))
user_graph.xaxis.set_major_formatter(ticker.ScalarFormatter())
plt.title('Average Requested RAM per CPU by User for all Users Running %i Jobs or less'%UpperlimitJobCount)
plt.xlabel('Job Count')
plt.ylabel('Average Requested RAM per CPU (Gigs)')
plt.show()
```
%% Cell type:code id: tags:
```
# bar graph for jobs run per user - shows average requested RAM per CPU for all jobs by user
user_graph2 = px.bar(df_user_graph, x='count', y='mean', color = 'count',
hover_data=['max','count'],
labels={'mean':'Average Requested RAM per CPU (Gigs)'},
height=400)
user_graph2.update_layout(
xaxis_type = 'category',
title={
'text': "Average Requested RAM per CPU by User for all Users",
'y':0.9,
'x':0.5,
'xanchor': 'center',
'yanchor': 'top'})
user_graph2.show()
```
%% Cell type:markdown id: tags:
# Average RAM per CPU by Job
%% Cell type:code id: tags:
```
# must run
# df_4 is database with only JobStep, User, JobName, ReqMemCpu, ArrayJob, and ArrayTaskID
# it is used to pull out needed information and create separate datasets to compare
df_4 = df_batch.loc[:,['JobStep','ReqMemCPU','ArrayJobID']]
#df_4.head(5)
```
%% Cell type:code id: tags:
```
# must run
# variable for to be used in names of plots to describe the max gigs measured
UpperlimitGB = 5
# variable for max gigs of RAM requested - Charts range from 0 to upperRAMlimit gigs
upperRAMlimit = UpperlimitGB * 10e+10 # 5 gigs
```
%% Cell type:code id: tags:
```
# must run
# creates database from df_4 that returns all RAM per CPU requested up to the UpperRAMlimit defined above
batch_cutoff = df_4[(df_4.ReqMemCPU <= upperRAMlimit)]
#batch_cutoff.head(5)
```
%% Cell type:code id: tags:
```
# must run
# df_user_graph is df_user sorted in decending order by mean for easy readibility of graph
batch_cutoff_graph = batch_cutoff.sort_values(by='ReqMemCPU', ascending=False)
#batch_cutoff_graph.head(5)
```
%% Cell type:code id: tags:
```
style.default_axes_and_ticks()
style.figsize()
# shows the number of jobs requesting cpu memory for all jobs (array and non array jobs)
Jobs_fig = sns.distplot(batch_cutoff['ReqMemCPU'], kde=False, label='Number of Jobs Requesting RAM per CPU for all Jobs', color = "green")
Jobs_fig.set_yscale('log')
plt.legend(prop={'size': 12},loc='upper right',bbox_to_anchor=(2.25, 1.0),ncol=1)
plt.title('Number of Jobs Requesting RAM per CPU for all Jobs %i gigs or less'%UpperlimitGB)
plt.xlabel('Requested Gigs of RAM')
plt.ylabel('Number of Jobs Requesting')
```
%% Cell type:code id: tags:
```
```
......
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