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import matplotlib.pyplot as plt
import numpy as np
import csv
import sys
def load_data(filename):
data = {}
with open(filename) as f:
reader = csv.reader(f)
next(reader, None)
for row in reader:
data[row[0]] = float(row[1])
return data
BAR_WIDTH=0.25
labels_for_data=['PING_INLINE', 'PING_MBULK', 'SET', 'GET', 'INCR', 'LPUSH', 'RPUSH', 'LPOP', 'RPOP', 'SADD', 'HSET', 'SPOP', 'ZADD', 'ZPOPMIN', 'LPUSH (needed to benchmark LRANGE)', 'LRANGE_100 (first 100 elements)', 'LRANGE_300 (first 300 elements)', 'LRANGE_500 (first 500 elements)', 'LRANGE_600 (first 600 elements)', 'MSET (10 keys)', 'XADD']
labels=['PING\n_INLINE', 'PING\n_MBULK', 'SET', 'GET', 'INCR', 'LPUSH', 'RPUSH', 'LPOP', 'RPOP', 'SADD', 'HSET', 'SPOP', 'ZADD', 'ZPOPMIN', 'LPUSH', 'LRANGE\n_100', 'LRANGE\n_300', 'LRANGE\n_500', 'LRANGE\n_600', 'MSET\n(10 keys)', 'XADD']
plt.rcParams["figure.figsize"] = (20,4)
plt.ylabel("Request / seconds")
data_num = len(sys.argv)-2
factor = (data_num+1) * BAR_WIDTH
for i in range(0, data_num):
filename = sys.argv[1+i]
data_csv = load_data(filename)
value = []
for l in labels_for_data:
value.append(data_csv[l])
plt.bar([x*factor+(BAR_WIDTH*i) for x in range(0, len(labels))], value, align="edge", edgecolor="black", linewidth=1, width=BAR_WIDTH, label=filename)
plt.legend()
plt.xlim(0, (len(labels)-1)*factor+BAR_WIDTH*data_num)
plt.xticks([x*factor+BAR_WIDTH*data_num/2 for x in range(0, len(labels))], labels)
plt.savefig(sys.argv[1+data_num])
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