网站建设的难点在哪里,应用商店app下载安装,如何做公司网站百度推广,实力网站优化公司首选在服务器存储的测试中,经常需要看performance的性能曲线#xff0c;这样最能直接观察HDD或者SSD的性能曲线。 如下这是一个针对HDD跑Fio读写的iostat监控log,下面介绍一下分别用shell 和Python3 写画iostat图的方法 1 shell脚本 环境:linux OS gnuplot工具 第一步 :解析iosta…在服务器存储的测试中,经常需要看performance的性能曲线这样最能直接观察HDD或者SSD的性能曲线。 如下这是一个针对HDD跑Fio读写的iostat监控log,下面介绍一下分别用shell 和Python3 写画iostat图的方法 1 shell脚本 环境:linux OS gnuplot工具 第一步 :解析iostat log。提取要作图的一行
#!/bin/bash
hdd$1
cat ${hdd}_iostat.log |grep -i Device |head -1 ${hdd}_iostat.txt
cat ${hdd}_iostat.log |grep -i ${hdd} ${hdd}_iostat.txt第二步:把画图的列(监控读写的IOPS)求出来
#!/bin/bash
hdd$1
cat ${hdd}_iostat.log |grep -i Device |head -1 ${hdd}_iostat.txt
cat ${hdd}_iostat.log |grep -i ${hdd} ${hdd}_iostat.txt
num_read_iopshead -1 ${hdd}_iostat.txt | awk {for (i1;iNF;i) {if ($ir/s) {print i}}}
num_write_iopshead -1 ${hdd}_iostat.txt | awk {for (i1;iNF;i) {if ($iw/s) {print i}}}第三步:直接调用gnuplot工具作图
#!/bin/bash
hdd$1
cat ${hdd}_iostat.log |grep -i Device |head -1 ${hdd}_iostat.txt
cat ${hdd}_iostat.log |grep -i ${hdd} ${hdd}_iostat.txt
num_read_iopshead -1 ${hdd}_iostat.txt | awk {for (i1;iNF;i) {if ($ir/s) {print i}}}
num_write_iopshead -1 ${hdd}_iostat.txt | awk {for (i1;iNF;i) {if ($iw/s) {print i}}}
echo set terminal png set title Random_${hdd}_IOPSset output IOPS_${hdd}.pngset xlabel count:1sset ylabel IOPSset key right topplot ${hdd}_iostat.txt using :$num_write_iops title w/s with lines lw 1,\${hdd}_iostat.txt using :$num_read_iops title r/s with lines lw 1 | gnuplot运行 :bash gnuplot.sh sde 2 python 脚本 环境:python3 python库: sys(引用参数), re(正则匹配), pandas(做表格), matplotlib(画图工具) 第一步:解析iostat log
import sys
import re
import pandas as pd
from matplotlib import pyplot as plt
hdd sys.argv[1]
rs []
ws []
logfile open(f{hdd}_iostat.log,r)for log in logfile:if hdd in log:data re.sub( , , log)rs.append(data.split( )[3])ws.append(data.split( )[4])第二步:将需要作图的列(这次监控带宽)导入CSV
import sys
import re
import pandas as pd
from matplotlib import pyplot as plt
hdd sys.argv[1]
rs []
ws []
logfile open(f{hdd}_iostat.log,r)for log in logfile:if hdd in log:data re.sub( , , log)rs.append(data.split( )[3])ws.append(data.split( )[4])dic {read: rs, write: ws}
df pd.DataFrame(dic)
df.to_csv(f{hdd}_iostat.csv)
data pd.read_csv(f{hdd}_iostat.csv)
第三步:用matplotlib库直接作图
import sys
import re
import pandas as pd
from matplotlib import pyplot as plt
hdd sys.argv[1]
rs []
ws []
logfile open(f{hdd}_iostat.log,r)for log in logfile:if hdd in log:data re.sub( , , log)rs.append(data.split( )[3])ws.append(data.split( )[4])dic {read: rs, write: ws}
df pd.DataFrame(dic)
df.to_csv(f{hdd}_iostat.csv)
data pd.read_csv(f{hdd}_iostat.csv)fig plt.figure(figsize(10, 6), dpi300)
x data.iloc[:, 0]
y1 data.iloc[:, 1]
y2 data.iloc[:, 2]
plt.xlabel(utime (s), size10)
plt.ylabel(BW(kB/s))
plt.plot(x, y1, labelrKB/s, colororange, linestyle:)
plt.plot(x, y2, labelwKB/s, colorcyan, linestyle-.)
plt.legend(locupper right)
plt.title(f{hdd}_BW)
plt.grid(alpha0.4)
plt.savefig(str(hdd) .png)运行 :python3 plot.py sde
