Jmeter summariser report的设置在：bin/jmeter.properties
#---------------------------------------------------------------------------
# Summariser - Generate Summary Results - configuration (mainly applies to non-GUI mode)
#---------------------------------------------------------------------------
#
# Define the following property to automatically start a summariser with that name
# (applies to non-GUI mode only)
summariser.name=summary
#
# interval between summaries (in seconds) default 3 minutes
summariser.interval=180
#
# Write messages to log file
summariser.log=true
#
# Write messages to System.out
#summariser.out=true
以上设置每隔3分钟向jmeter.log中写入一行log
# Combined log file (for jmeter and jorphan)
log_file=jmeter.log
log的格式如下：
2017-11-21 15:49:14,389 INFO o.a.j.t.JMeterThread: Thread started: 线程组 1-100
2017-11-21 15:49:14,392 INFO o.a.j.p.h.s.HTTPHC4Impl: HTTP request retry count = 0
2017-11-21 15:49:14,408 INFO o.a.j.s.SampleResult: Note: Sample TimeStamps are START times
2017-11-21 15:49:14,411 INFO o.a.j.s.SampleResult: sampleresult.default.encoding is set to ISO-8859-1
2017-11-21 15:49:14,411 INFO o.a.j.s.SampleResult: sampleresult.useNanoTime=true
2017-11-21 15:49:14,411 INFO o.a.j.s.SampleResult: sampleresult.nanoThreadSleep=5000
2017-11-21 15:49:30,006 INFO o.a.j.r.Summariser: summary + 4857 in 00:00:16 = 308.1/s Avg: 258 Min: 22 Max: 7941 Err: 0 (0.00%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:50:00,002 INFO o.a.j.r.Summariser: summary + 11529 in 00:00:30 = 384.3/s Avg: 271 Min: 30 Max: 21225 Err: 0 (0.00%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:50:00,003 INFO o.a.j.r.Summariser: summary = 16386 in 00:00:46 = 358.1/s Avg: 267 Min: 22 Max: 21225 Err: 0 (0.00%)
2017-11-21 15:50:30,004 INFO o.a.j.r.Summariser: summary + 12104 in 00:00:30 = 403.5/s Avg: 233 Min: 43 Max: 15109 Err: 31 (0.26%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:50:30,005 INFO o.a.j.r.Summariser: summary = 28490 in 00:01:16 = 376.0/s Avg: 252 Min: 22 Max: 21225 Err: 31 (0.11%)
2017-11-21 15:51:00,002 INFO o.a.j.r.Summariser: summary + 12112 in 00:00:30 = 403.8/s Avg: 268 Min: 44 Max: 84469 Err: 51 (0.42%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:51:00,003 INFO o.a.j.r.Summariser: summary = 40602 in 00:01:46 = 383.9/s Avg: 257 Min: 22 Max: 84469 Err: 82 (0.20%)
2017-11-21 15:51:30,017 INFO o.a.j.r.Summariser: summary + 11994 in 00:00:30 = 399.6/s Avg: 245 Min: 40 Max: 17814 Err: 42 (0.35%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:51:30,018 INFO o.a.j.r.Summariser: summary = 52596 in 00:02:16 = 387.4/s Avg: 254 Min: 22 Max: 84469 Err: 124 (0.24%)
2017-11-21 15:52:00,003 INFO o.a.j.r.Summariser: summary + 12153 in 00:00:30 = 405.3/s Avg: 250 Min: 34 Max: 13470 Err: 26 (0.21%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:52:00,004 INFO o.a.j.r.Summariser: summary = 64749 in 00:02:46 = 390.6/s Avg: 254 Min: 22 Max: 84469 Err: 150 (0.23%)
2017-11-21 15:52:30,069 INFO o.a.j.r.Summariser: summary + 12318 in 00:00:30 = 409.7/s Avg: 234 Min: 40 Max: 14107 Err: 17 (0.14%) Active: 100 Started: 100 Finished: 0
2017-11-21 15:52:30,070 INFO o.a.j.r.Summariser: summary = 77067 in 00:03:16 = 393.5/s Avg: 250 Min: 22 Max: 84469 Err: 167 (0.22%)
2017-11-21 15:53:00,004 INFO o.a.j.r.Summariser: summary + 11864 in 00:00:30 = 396.3/s Avg: 253 Min: 39 Max: 25669 Err: 33 (0.28%) Active: 100 Started: 100 Finished: 0
summary +是这三分钟的数据，summary =是累计到当前时刻所有的数据
以黄色区域数据为例，4857是发出的请求数目，00:00:16是发出的时间， 308.1是每秒发出的请求，即吞吐量，Avg, Min, Max分别是平均响应时间，最小响应时间和最大响应时间，响应时间指的是从请求发出到收到响应的时间，Err后面跟的数据分别是错误数和错误比例。
对于summariser报告，可以通过写一个简单的脚本来解析并作图形化展示，下面是用python写的一个简单脚本，可以画平均时延和吞吐量，使用方法是
python summary.py test.log，下面是summary.py内容：
import matplotlib.pyplot as plt
import re
import sys avgtime_data=[]
mintime_data=[]
maxtime_data=[]
throughput_data=[] logfile=open(sys.argv[1])
try:
while True:
line=logfile.readline()
if line=='':
break
if line.startswith('summary ='):
result=re.split(r'\s+', line)
avgtime_data.append(result[8])
throughput=result[6]
throughputvalue=throughput[:-2]
throughput_data.append(throughputvalue)
finally:
logfile.close() plt.figure(figsize=(8,4))
plt.ylim(0,60)
plt.plot(avgtime_data,color="red",label="Avg ResponseTime (milliseconds)")
plt.plot(throughput_data,color="green",label="ThroughPut (/s)")
frame = plt.gca()
frame.axes.xaxis.set_ticklabels([])
plt.xlabel("Duration, 2013/06/25 16:30:00 -- 2013/06/28 6:00:00, about 60 hours")
plt.title("sundong Jmeter Test Report")
plt.legend()
plt.show()
注意里面用到了正则表达式，其实在log文件非常大的时候，每行都进行正则匹配，效率是很低的。分享下我们项目使用的切片方法写的rpc-server，效率要高出10几倍
import sys reload(sys)
sys.setdefaultencoding('utf8')
import zerorpc class RPCServer(object):
def getLogData(self,filename):
avgtime_data=[]
throughput_data=[]
tps_data=[]
tpsput_data=[]
with open(filename, 'r') as f:
for line in f:
if 'summary =' in line:
rs = line.split('Avg:')
avgtime_data.append(rs[1][0:6])
throughput_data.append(rs[0][-10:-3]) return avgtime_data,throughput_data s = zerorpc.Server(RPCServer())
s.bind("tcp://0.0.0.0:4242")
s.run()
通过rpc server获取jmeter master的log日志里的数据，应用通过rpc client进行调用
参考：
1、http://blog.csdn.net/just_lion/article/details/9209253