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process_dstat_baseline_nomidd_2servers.py
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process_dstat_baseline_nomidd_2servers.py
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"""
ASL project - fall 2017
author: Jovan Nikolic
Processes aggregated logs generated by middleware
"""
import numpy as np
import csv
base_path = "data/baseline_nomidd_2servers/dstat_"
output_base_path = "plots/baseline_nomidd_2servers/"
machine_types = ["memtier", "memcached"]
virtual_clients_pt = [1, 5, 8, 13, 20, 27, 32, 42, 52, 64, 78, 96]
commands = ["r", "w"]
columns = ["user cpu", "system cpu", "net_received", "net_sent", "system csw"]
repetitions = 3
def read_csv(machine_type, cpt, command):
full_data = {}
for column in columns:
full_data[column] = []
if machine_type == machine_types[0]:
max_id = 1
elif machine_type == machine_types[1]:
max_id = 2
else:
max_id = 0
for rep in range(repetitions):
full_data_pr = {}
for column in columns:
full_data_pr[column] = []
current_rep = rep + 1
print(" rep: " + str(current_rep))
for i in range(max_id):
ID = i + 1
print(" id: " + str(ID))
path = base_path + machine_type + str(ID) + "_cpt" + str(cpt) + "_rep" + str(current_rep) + "_" + command + ".csv"
with open(path, 'r') as file:
data = file.readlines()
data = [x.strip() for x in data]
for k, line in enumerate(data):
if k < 7:
continue
parsed_line = line.split(',')
[x.strip() for x in parsed_line]
full_data_pr[columns[0]].append(float(parsed_line[0]))
full_data_pr[columns[1]].append(float(parsed_line[1]))
full_data_pr[columns[2]].append(float(parsed_line[18]))
full_data_pr[columns[3]].append(float(parsed_line[19]))
full_data_pr[columns[4]].append(float(parsed_line[25]))
full_data[columns[0]].append(np.mean(np.asarray(full_data_pr[columns[0]])))
full_data[columns[1]].append(np.mean(np.asarray(full_data_pr[columns[1]])))
full_data[columns[2]].append(np.mean(np.asarray(full_data_pr[columns[2]])))
full_data[columns[3]].append(np.mean(np.asarray(full_data_pr[columns[3]])))
full_data[columns[4]].append(np.mean(np.asarray(full_data_pr[columns[4]])))
full_data_means = {}
full_data_std = {}
for z, column in enumerate(columns):
if z == 2 or z == 3:
full_data_means[column] = np.mean(np.asarray(full_data[column]) / 1024)
full_data_std[column] = np.std(np.asarray(full_data[column]) / 1024)
else:
full_data_means[column] = np.mean(np.asarray(full_data[column]))
full_data_std[column] = np.std(np.asarray(full_data[column]))
return full_data_means, full_data_std
def print_csv(header, path, full_data_means, full_data_stds):
with open(path, 'w') as csv_file:
writer = csv.DictWriter(csv_file, fieldnames=header)
writer.writeheader()
for row in range(len(virtual_clients_pt)):
one_row = {}
i = 0
one_row[header[i]] = 2*virtual_clients_pt[row]
i += 1
for k in range(len(columns)):
one_row[header[i]] = full_data_means[commands[0]][virtual_clients_pt[row]][columns[k]]
i += 1
one_row[header[i]] = full_data_stds[commands[0]][virtual_clients_pt[row]][columns[k]]
i += 1
one_row[header[i]] = full_data_means[commands[1]][virtual_clients_pt[row]][columns[k]]
i += 1
one_row[header[i]] = full_data_stds[commands[1]][virtual_clients_pt[row]][columns[k]]
i += 1
writer.writerow(one_row)
csv_file.close()
def process():
for machine_type in machine_types:
print("Machine: " + machine_type)
full_data_means = {}
full_data_stds = {}
for command in commands:
print(" Command: " + command)
full_data_means[command] = {}
full_data_stds[command] = {}
for cpt in virtual_clients_pt:
print(" Clients: " + str(cpt))
means, stds = read_csv(machine_type, cpt, command)
full_data_means[command][cpt] = means
full_data_stds[command][cpt] = stds
header = ["#Clients",
"Mean User CPU - READ-ONLY", "Std User CPU - READ-ONLY",
"Mean User CPU - WRITE-ONLY", "Std User CPU - WRITE-ONLY",
"Mean System CPU - READ-ONLY", "Std System CPU - READ-ONLY",
"Mean System CPU - WRITE-ONLY", "Std System CPU - WRITE-ONLY",
"Mean Net-Received - READ-ONLY", "Std Net-Received - READ-ONLY",
"Mean Net-Received - WRITE-ONLY", "Std Net-Received - WRITE-ONLY",
"Mean Net-Sent - READ-ONLY", "Std Net-Sent - READ-ONLY",
"Mean Net-Sent - WRITE-ONLY", "Std Net-Sent - WRITE-ONLY",
"Mean Context Switches - READ-ONLY", "Std Context Switches - READ-ONLY",
"Mean Context Switches - WRITE-ONLY", "Std Context Switches - WRITE-ONLY"]
path = output_base_path + "dstat_" + machine_type + ".csv"
print_csv(header, path, full_data_means, full_data_stds)
def main():
process()
if __name__ == "__main__":
main()