|
讲真python在处理数据的时候还是很方便的，但是安装以及他的不兼容性觉得有点无奈 lit lit_freq1 lit_freq2 lit_freq3 lit_freq4 lit_freq5 online offline
cpu0 11.08% 0.11% 0.24% 0.08% 5.83% 17.33% 82.67%
cpu1 9.13% 0.09% 0.20% 0.06% 4.81% 14.29% 85.71%
cpu2 5.28% 0.05% 0.12% 0.04% 2.78% 8.26% 91.74%
cpu3 5.13% 0.05% 0.11% 0.04% 2.70% 8.03% 91.97%
xxxxx 63.89% 0.62% 1.41% 0.45% 33.63%
big big_freq1 big_freq2 big_freq3 big_freq4 big_freq5 big_freq6 online offline
cpu4 5.30% 0.15% 0.16% 0.13% 0.04% 0.16% 5.94% 94.06%
cpu5 0.84% 0.02% 0.03% 0.02% 0.01% 0.02% 0.95% 99.05%
cpu6 1.92% 0.06% 0.06% 0.05% 0.01% 0.06% 2.15% 97.85%
cpu7 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.00%
yyyyy 89.17% 2.59% 2.76% 2.25% 0.60% 2.63%
这里考虑的CPU分为两个cluster，其中CPU0\CPU1\CPU2\CPU3属于cluster0 CPU4\CPU5\CPU6\CPU7属于cluster1
比如我现在需要计算每个cluster横行和每个纵行的数据的和 #!/usr/bin/python
# coding=utf-8
from collections import OrderedDict
import os
import sys
file_path = sys.argv[1]
def open_file_get_time_data(file_name, dic_data,order_dic_freq={}):
lit_freq = [lit_freq1, lit_freq2, lit_freq3, lit_freq4, lit_freq5]
big_freq = [big_freq1, big_freq2, big_freq3, big_freq5, big_freq5, big_freq6]
try:
with open ( file_name, "r", encoding="UTF-8", errors='ignore' ) as file_obj:
lines = file_obj.readlines()
for content in lines:
if(content.split()):
list = content.split()
#print(list)
if(list[0]=="cpu0" or list[0]=="cpu1" or\
list[0]=="cpu2" or list[0]=="cpu3"):
i = 1
for freq in lit_freq:
dic_data["lit_"+list[0]][freq] = float(list[i].replace("%",""))
#print(dic_data["lit_"+list[0]][freq])
i = i+1
if (list[0] == "cpu4" or list[0] == "cpu5" or \
list[0] == "cpu6" or list[0] == "cpu7"):
i = 1
for freq in big_freq:
dic_data["big_"+list[0]][freq] = float(list[i].replace("%",""))
#print ( dic_data["lit"][freq] )
i = i + 1
except:
print ( "there is some wrong during open" + file_name )
if __name__ == '__main__':
cpu_result = file_path
order_dic_cpu_result = OrderedDict()
dic_sum = OrderedDict()
dic_sum["lit"]=0
dic_sum["big"]=0
order_dic_cpu_result["lit_cpu0"] = OrderedDict ()
order_dic_cpu_result["lit_cpu1"] = OrderedDict ()
order_dic_cpu_result["lit_cpu2"] = OrderedDict ()
order_dic_cpu_result["lit_cpu3"] = OrderedDict ()
order_dic_cpu_result["big_cpu4"] = OrderedDict ()
order_dic_cpu_result["big_cpu5"] = OrderedDict ()
order_dic_cpu_result["big_cpu6"] = OrderedDict ()
order_dic_cpu_result["big_cpu7"] = OrderedDict ()
open_file_get_time_data ( cpu_result, order_dic_cpu_result)
total = 0
for cluster in dic_sum:
print(cluster)
print("%-10s"%"SUM",end="")
for dict_cluster in order_dic_cpu_result:
if cluster in dict_cluster:
for freq in order_dic_cpu_result[dict_cluster]:
dic_sum[cluster] = dic_sum[cluster]+order_dic_cpu_result[dict_cluster][freq]/100*freq
print(dic_sum[cluster])
total = total +dic_sum[cluster]
print("%-10s"%"TOTAL",end="")
print(total)
计算显示结果如下 lit
SUM x
big
SUM y
TOTAL x+y 具体可以参考：https://github.com/feifeiyuan/features/tree/master/python/calculate_sum 同时也有相关代码如下： https://github.com/feifeiyuan/features/blob/master/python/time_in_state%E8%AE%A1%E7%AE%97cpu_loading/tool/cpu_data_compute.py
| 
转播
